Review ArticleAccelerometer Sensor Specifications to Predict HydrocarbonUsing Passive Seismic Technique

M H Md Khir1 Atul Kumar1 and Wan Ismail Wan Yusoff2

1Department of Electrical and Electronic Engineering Universiti Teknologi PETRONAS Bandar Seri Iskandar31750 Tronoh Perak Malaysia2Department of Geosciences Universiti Teknologi PETRONAS Bandar Seri Iskandar 31750 Tronoh Perak Malaysia

Correspondence should be addressed to M H Md Khir hariskpetronascommy

Received 18 December 2015 Revised 14 April 2016 Accepted 26 April 2016

Academic Editor Rui Tang

Copyright copy 2016 M H Md Khir et alThis is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

The ambient seismic ground noise has been investigated in several surveys worldwide in the last 10 years to verify the correlationbetween observed seismic energy anomalies at the surface and the presence of hydrocarbon reserves beneath This is due to thepremise that anomalies provide information about the geology and potential presence of hydrocarbon However a technology gapmanifested in nonoptimal detection of seismic signals of interest is observed This is due to the fact that available sensors are notdesigned on the basis of passive seismic signal attributes andmainly in terms of amplitude and bandwidthThis is because of that factthat passive seismic acquisition requires greater instrumentation sensitivity noise immunity and bandwidth with active seismicacquisition where vibratory or impulsive sources were utilized to receive reflections through geophones Therefore in the case ofpassive seismic acquisition it is necessary to select the best monitoring equipment for its success or failure Hence concerningsensors performance this paper highlights the technological gap and motivates developing dedicated sensors for optimal solutionat lower frequenciesThus the improved passive seismic recording helps in oil and gas industry to perform better fracture mappingand identify more appropriate stratigraphy at low frequencies

1 Introduction

An increasing demand and supply of oil and gas requirethe industries to increase the survey for identifying reservoirfield Convention technique has been utilized for determiningthe petrophysical properties of reservoir but at a frequencyrange of 10ndash300Hz [1] Due to limited seismic bandwidthsensors are unable to determine the complete informationof a reservoir Therefore passive seismic wavefield that ismicrotremors is utilized as reservoir indicator to determinethe petrophysical properties of rock at low frequency rangeof less than 10Hz [2 3] Natural occurring seismic noisefrom the subsurface may act as a hydrocarbon-indicatingsignal Spectral analysis using rock-physics mechanisms isperformed for determining these signals below and above thehydrocarbon reservoir frequency range [4]

According to passive seismic technique the key observa-tion for identifying hydrocarbon reservoir is accurate sensing

of seismic energy at lower frequency range of approximately1ndash6Hz [5]

For better stratigraphy it is important to measure thespectral energy of a hydrocarbon signal both near and awayfrom the well log However observed seismic energy fordetermining hydrocarbon reservoir may have wider rangeOn the contrary geoscientists may consider a range of 1ndash6Hzas a typical noise trough in the background spectrum whichis the only frequency window for hydrocarbon-indicatingsignal [6 7]

Furthermore the research study of seismic energy atsubsurface identifies some independent spectral attributes[8] These attributes help in computing the spectral ratiobetween horizontal and vertical components of formationSuch ratio indicates the presence of hydrocarbon if theldquoGoodrdquo event of P-wave and S-wave arrives in the timedomain (discussed in Section 4) Accurate arrival of sourcewave becomes a primary source and key indicator of low

Hindawi Publishing CorporationJournal of SensorsVolume 2016 Article ID 4378540 28 pageshttpdxdoiorg10115520164378540

2 Journal of Sensors

Figure 1 Accelerometer example Digital Sensor Unit (DSU1) [18]

frequency microtremors in helping locating the presence ofhydrocarbon reserves [1]

A time-reverse wave-propagation method is used fordetermining the ldquoGoodrdquo event of source wave in depthdomain near the well log This is because well log dataprovides better characteristics of the rocks to distinguish thehydrocarbon reserves accurately [1 2 21]

Based on the literatures and different levels of surveysit is clear that current emerging and effective data analysistechnique is passive seismic wavefield that is microtremorsat low frequency for identifying hydrocarbon reserves accu-rately [22] Since for real data analysis there must be a needfor considering production noise in themeasured data basedon this consideration the data analysis using microtremorsrequires some careful assumptions such as the following

(a) reservoir heterogeneity may cause misinterpretationof anomalies which is caused by noise

(b) high noise (or high signal-to-noise ratio) duringexploration may overwhelm seismic signals

On the other hand one inquiry likewise emerges amidinvestigation whether microtremors can attain to the bettercorrelation for both homogenous and heterogeneous kind ofreservoir or not The answer is conceivable to achievable byinvestigating the passive seismic data and its overview all themore obviously and precisely It is a direct result of the waythat passive seismic is the location of the earth encompassingseismic waves without the utilization of controlled source[18 23] MEMS based accelerometers such as 1C (DSU1)or 3C versions (DSU3) are adept in order to sense variousenvironments (eg transition zone or seabed) depicted inFigure 1They can receive extensive attention because of theirability to give rich subsurface information at low cost and inenvironmentally friendly manner [24]

The use of passive seismic as a direct hydrocarbon indi-cator (DHI) has valuable promising advantages in reducingdrilling risks well positioning and enhancing oil recovery[22] The premise of the technique is the empirical observa-tions of unique seismic energy anomalies over hydrocarbon-bearing reservoirs Existing studies attributed this phe-nomenon to the oscillation of hydrocarbon in pores driven bythe omnipresent ambient seismic waves Some mathematicalmodels interpreting the phenomenon have been developedfor example hydrocarbon microtremor analysis (HyMAS)Navier-Stokes model (NSM) and the linear harmonic oscil-lator model (LHOM) [21] On the other hand late studies

uncovered results contradicting indisputably the correlationbetween the perceptions of tremor-like signs and the pres-ence of hydrocarbon underneath [24 29 41] Thereforethis overview proposed the thought of reservoir geology inrelating watched microtremors-like signals to hydrocarbonvicinity Accordingly the principle critical concern of passiveseismic studies is to get high resolution seismic informationThis is because of the way that available sensors were notdesigned on the basis of passive seismic signal attributesmainly in terms of amplitude and bandwidth Concerningsensors performance this paper highlights the technologicalgap and motivates developing dedicated sensors for optimalsolutions

2 Technical Infrastructure (Design andModeling of Accelerometer)

A fundamental test in simulating and designing MEMSdevice is the adjacent coupling between electrical mechan-ical optical and diverse frameworks dynamic in all MEMSdevices Furthermore a primary query concerning the cou-pling of the noise is identified that signifies processing withvariant physical or dynamic components in any of the existingMEMS devices [9] That is does the vicinity of electronicnoise say Johnson (thermal) noise influence mechanical(Brownian) noise which can influence the little masses inMEMS devices and the other way around Correspondinglythermal adsorption and desorption noise has mechanicalbehavior on a subatomic level but can incorporate electroniceffects when ions are incorporated [9]

Mechanical noise for example microphonics and vibra-tions is regularly extrinsic However Brownian motion aprincipal of intrinsic mechanical noise mechanism existswhich may appear due to the dynamic unbalanced forceshappening due to the random impacts of atoms on a small ionparticle or structure Subsequently it is likewise called ldquoran-dom walkrdquo noise Brownian movement turns out to be morecritical as the span of a structure diminishes for instance theproof mass in MEMS accelerometer Adsorption-desorptioncommotion is firmly identified with the Brownianmovementbecause of random arrival and departure of distinct atomsandmolecules on the surface ofMEMSdevice Table 1 impliesthe essentialmechanical noise source for the device due to theBrownianmotion of the gas particles encompassing the proofmass and the proof mass suspension or stays In this mannerthe aggregate noise equivalent acceleration (TNEA)ms2 [42]is

TNEA =radic

4119896119861119879119887

119898

(1)

Here (1) clearly signifies that to decrease the mechanicalnoise the quality factor and proof mass must be incre-mented Since the paper involves designing the MEMS basedaccelerometer it is very much important to understand andidentify the factor causing the mechanical noise [42] Itmainly occurred due the proof mass itself which leads to theequivalent acceleration noise Such noise is dominating and

Journal of Sensors 3

Table 1 A Comparative analysis on the characterization and noise analysis of MEMS device [9]

Paper Device or structure Focus Characterization

Gabrielson [10] Accelerometers pressure sensorscapacitive microphones

Mechanical-thermalnoise Theory

Djuric [11] Accelerometers infrared thermaldetector microbeams Several mechanisms Theory

Djuric et al [12] Microcantilevers and microresonators Several mechanisms Theory andcomputations

Greiner and Korvink[13] Micro bars Mechanical noise Theory

Vig and Kim [14] Resonators (microbeams) Several mechanisms Theory andcomputations

Leland [15] Gyroscopes Mechanical-thermalnoise Theory

limiting the performance of MEMS devices especially whenoperating under low acceleration conditions

21 Principle Design of MEMS Based Accelerometer Amechanical design of Microelectromechanical System(MEMS) based accelerometer consists of proof mass 119898effective spring (with constant 119896) and damper (with coeffi-cient 119887) affecting the dynamic motion of the mass producedby the air-structure interaction as depicted in Figure 2

The operation of the accelerometer can be modeled as asecond-order mechanical system When force is acted uponon the accelerometer themass develops a forcewhich is givenby DrsquoAlembertrsquos inertial force equation 119865 = 119898 lowast 119886 This forcedisplaces the spring by a distance 119909 Hence the total forceexternally is balanced by the sum of internal forces given by[42]

119865external = 119865inertial + 119865damping + 119865spring (2)

based on the mechanical design of MEM accelerometervibration along the 119909 direction that showed the mechanicalbehavior of the system can be given by the differentialequation [42]

119898

120597

2119909

120597119905

+ 120573

120597119909

120597119905

+ 119896119909 = 119865ext = 119898119886(3)

where 119898 is effective mass 119909 is displacement 120573 is dampingcoefficient 119896 is spring stiffness 119865 is force at the moving massand 119860 is acceleration of the moving mass

Also the transfer function in Laplace domain havingdisplacement of 119909 can be represented as [42]

119909 (119904)

119886 (119904)

=

1

119904

2+ (119887119898) 119904 + 119896119898

(4)

or

119909 (119904)

119886 (119904)

=

1

119904

2+ (120596119899119876) 119904 + 120596

2

119899

(5)

where 120596119899= radic119896119898 the resonant frequency and 119876 = 120596

119899119898119887

the quality factor

Damperb

Proof massM

x

Springk

Figure 2 Mechanical design of MEMS accelerometer [9 34 42]

However the device response time has been dictatedprincipally by the natural frequency of the proofmassThuslyto accomplish critically damped acceleration damping limi-tations must be necessary to take into consideration whichpermits getting the minimum amplitude distortion [34]Thismeans 119876 = 2

radic2 Therefore

119887

2119898120596119899

=

1

radic2

(6)

But in order to characterize the damping solving thedominatorrsquos equation by estimatingΔ of the transfer functionin (4) is needed

119904

2+

119887

119898

119904 +

119896

119898

= 0

Δ = (

119887

119898

)

2

minus 4

119896

119898

(7)

For Δ = 0 thus 119887 = 2radic119896119898 a damping coefficient

Based on (6) and (7) three different cases must beconsidered in order to determine the variation in designingthe bandwidth such as the following

(i) Underdamped system where 119887 lt 2radic119896119898

(ii) Critically damped system where 119887 = 2radic119896119898

(iii) Overdamped system where 119887 gt 2radic119896119898

4 Journal of Sensors

Disp

lace

men

t

Time

UnderdampedCritically damped

Overdamped

120587

2wr

Figure 3 Step response of the accelerometer as a second-ordermechanical system [42]

However critical damping is essential for achieving max-imum bandwidth Since the absence of damping permittedvery high levels of sensor resonant amplification it is fur-thermore recognizable that mass must be sufficiently huge toacquire the desired sensitivity with weak spring as shown inFigure 3 In thismanner themechanical resonance frequencyof suspended mass is given by

120596119899=

radic

119896

119898

(8)

Such expansion and the analysis imply that in an openloop circuiting a high sensitivity of the device yields a smallbandwidth while in closed loop circuiting the resonancepeak has been suppressed by the control circuit It is alsoclear that the mechanical resonance of the sensor does notlimit the bandwidth of the device but it is limited by thetransition frequency of the control circuit [44] Howeverdue to mechanical noise Brownian motion noise comes intoaccount which has been utilized to indicate the unwantedsignal as noise in the form of acceleration noise (see Table 1)Brownian noise has significant impact on both bulk andsurface micromachined capacitive accelerometers The mea-surement of the signal produced by the noise source andunsolicited signals is noise floor therefore it is clear that thereal signal cannot be detectable if the measured signal hasa value below this noise floor Nonetheless the variation inthe frequency causes the change in the noise floor valuesconsidering theBrowniannoise having noise floor between 10and 100 120583grtHz Such noise generates the random force withBrownian motion of air molecules which occurred becauseof the damping effect applied directly to the seismic massTherefore the Power Spectral Density (PSD) of the Browniannoise force is depicted as [45]

119865

2

119861(119891) = 4119896

119861119879119887

(9a)

where 119865119861is Brownian noise force 119896

119861is Boltzmann constant

119879 is absolute temperature and 119887 is damping coefficientHere it is clear that the damping coefficient (119887) is directly

proportional to Brownian noise such that the larger the valueof damping coefficient is the higher the noise will be or viceversa as depicted in (9a) Therefore reduction in the noisevalue requires anticipating the smaller value of the damping

W A

L

dd + Δ

L

Figure 4 Capacitance change due to variation in plate separation[33]

coefficient and hence results in a smaller damping ratio[44 45] Such ratio helps in modeling MEMS accelerometerrunning at underdamped condition having an oscillatingmess in the designed accelerometer Hence to measure theaccelerometerrsquos noise performance an acceleration-referrednoise floor has been estimated by using Newtonrsquos law as [45]

119886

2

119861(119891) =

119865

2

119861

119898

2=

radic4119896119861119879119887

98

2119898

2g2Hz (9b)

Since the thermal-mechanical Brownian noise floor iswithin 10sim100 120583grtHz it might influence the processing andthe device performance where the noise is considered asprocess noise Hence the minimum detectable acceleration isgiven by

119886min = radic

8120587119896119861119879119891119899119861

119876119898

(10a)

or

119886min =radic

4119896119861119879119887119861

119898

(10b)

However from (5) and (8) the mathematical computationidentifies that the bandwidth of an accelerometer sensingelement is directly proportional to its sensitivity (119878) duringthe design it must be considered Sensitivity of capacitiveaccelerometer is defined as the ratio of the difference ofvariation in the capacitance to the difference in variation inthe displacement which is depicted as

1198780=

119860119898120576

119896119889

2=

1198620119898

119896119889

(11)

where 120576 is the electric permittivity of air119860 is the overlap areaof electrodes and 119889 is the gap between the electrodes

The most well-known utilization of capacitive detectionfor sensors depends on signals which are coupled to changesin the electrode partition 119889 Let us consider a couple ofelectrodes with area119860 and separation 119889 depicted in Figure 4[33] A physical signal causes the partition to increment by asmall amount Δ The capacitance changes

from1205761205760

119889

to1205761205760

119889 + Δ

(12a)

Journal of Sensors 5

Here the correlation between the displacement andchange in capacitance is not linear but for a small change inthe division the capacitance can be estimated by utilizing aTaylor series expansion Generally any function 119865(119889) can beapproximated in the neighborhood of some nominal valued119889(0) as follows [33]

119865 (1198890+ Δ) = 119865 (119889

0) + Δ

120597119865 (1198890)

120597119889

+

Δ

2

2

120597

2119865 (1198890)

120597119889

2

+ sdot sdot sdot

(12b)

Based on the above expression this expansion can beimplemented as

119862 asymp

1205761205760119860

119889

(1 minus

Δ

119889

+

Δ

119889

2) (12c)

where Δ = 119889 minus 1198890

So for Δ ≪ 119889 the change in capacitance has linearrelationship with respect to the displacement The nonlin-earity of the function has been considered as a correctiontermof orderΔ21198892 such that nonconsideration of such errormakes the signal remain nearly linear [33]This creates a newrelationship such that the sum of the forces on the mass isequal to the acceleration of the mass (see Figure 2) such that

119896 (119883 minus 119909) + 119887

119889 (119883 minus 119909)

119889119905

= 119898

119889

2119909

119889119905

2

(12d)

where 119883 is position of the frame in Figure 2 119909 is position ofthe mass in Figure 2

Therefore the maximum detectable acceleration havingtotal gap between the electrodes 119889max is given by

119886max = 119896

119889max119898

(12e)

Additionally the above equations signify that spring con-stant ldquo119896rdquo affects directly the resonant frequency bandwidthsensitivity and furthermore the pull-in voltage Basically thespring constant is directly proportional to the beam charac-teristics such as the length (119871) the thickness (119905) the width(119882) and the elasticity of the material coefficient (YoungrsquosModulus (119864)) [44] Such variation in the spring constantin a beam occurs due the tensile and compressive stresseswhich is considered negligible during implementation andtherefore the following equation can be defined for furtherapplication

119896 =

119882119905

3

119871

3119864

(13)

where 119864 is Youngrsquos Modulus of the material utilized havingunit of gigapascals that is GPa

Since volume of proof mass is 119881 = 119871119898119879119898119882119898and is

homogeneously parallelepiped with rectangular area (119860) thevolume must be estimated from the volumic mass density 120588

as

120588 =

119898

119881

997904rArr

119881 =

119898

120588

(14)

Therefore the computation of the thickness (119879119898) of the

device is defined as

119881 = 119871119898119882119898119879119898

= 119860 sdot 119879119898

997904rArr

119879119898

=

119881

119860

(15)

Furthermore based on the above mathematical model-ing the geometry of the design accelerometer and its proofmass are defined Such modeling of the proof mass of theaccelerometer clearly depends on the various dimensions ofthe sensing elements depicted in Figure 5

The parameters utilized in Figure 5 such as widththickness and length of the proof mass and anchor dependupon the selection of the type of themodelwhich is illustratedin Table 16 (Appendix) Furthermore the sensitivity ofthe accelerometer is dependent on the size of proof massspring constant and resonance frequency graph in Figure 6illustrating the phenomena that proof mass and resonancefrequency are inversely proportional to each other withincrease in proofmass the resonance frequency decreases andvice versa

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies (Figure 7) The technological lag betweenthe application requirements and performance offered byavailable and emerging accelerometers motivates the devel-opment of dedicated sensing technology depicted in Table 2[16ndash20]

22 Accelerometers Performance Overview MEMS devicesfor seismic applications have previously been designed usingpiezoresistive [49] capacitive [10] and piezoelectric typedsensors [50] Electron tunneling is also a very promising sens-ing mechanism due to its high sensitivity to low vibrations[51]The performance of accelerometers can be characterizedbased on demonstrated operational specifications includingthe following

(i) Acceleration Range Recording unnecessary high ampli-tude signals adversely affects sensor sensitivity and con-sequently the resolution [52] It is necessary to know theacceleration range that is defined as the maximum acceler-ation input that can be measured by the accelerometer in g(acceleration due to gravity) (asymp10msminus2) As a result an idealaccelerometer should be able to capture maximum vibrationsof geophysical interest

(ii) Bandwidth It refers to the frequency range of input accel-eration that the sensor can perform with minimum distor-tion An ideal accelerometer requires minimum bandwidthto reduce undesired noise [52] and should have maximumbandwidth that is sufficient to accommodate all signals ofinterest

(iii) Noise FloorThe noise collectively generated at the sensoroutput when no acceleration is present is referred to assensor noise floor It is a composite of three noise sourcesthe thermomechanical noise (ie Brownian noise) [49 53]

6 Journal of Sensors

Table 2 Comparison of existing MEMS accelerometers [16ndash20]

Sensor Supplier Bandwidth (Hz) Full scale (mg) Noise density (ngradicHz)Trillium [20] Nanometrics 003ndash50 mdash mdashGAC [17] WesternGeco 3ndash200 108 15DSU1 [18] Sercel 0ndash800 500 40 (gt10Hz)HP sensor [19] HP 1ndash200 80 10

Wm = 120583m

Lm = 120583m

Z

X

Y

tm = 120583m

L2 = 120583m

W = 120583m

t = 120583m

Figure 5 Sensing element dimensions

Reso

nanc

e fre

quen

cy (H

z)

60 70 80 90 100 110

Proof mass (120583g)

170

180

190

200

210

220

230

240

Figure 6 Resonance frequency versus proof mass

the thermoelectrical noise (ie Johnson noise) and the 1119891

noise (Hoogersquos noise) [54] The first one is due to the randommotion induced by thermal energy of gaseous moleculessurrounding the proof mass [10] The thermoelectrical noiseis attributed to the random electron motion in the wiresinduced by ambient thermal energy Hoogersquos noise is empiri-cal noise and is function of the frequency For simplicity thetotal noise floor 119886n can be expressed in terms of mechanicalnoise (119886nm) and electrical noise (119886ne) as displayed in

119886119899= radic119886nm

2+ 119886ne2

(16)

The noise floor is desirable to be as minimal as pos-sible but an acceptable level can be determined by therequired resolution To evaluate the need for dedicated sen-sors for hydrocarbon microtremor analysis studies availableaccelerometers have been reviewed Eventually matchinganalysis between sensing requirements and performancemetrics is performed to scope down design possibilitiesand guide promising directions Based on the employedsensing principle the discussion on performance metrics is

Telemetry cable

2 horizontal MEMSLine board

IC board

Servo-loop ASIC

V board

Vertical MEMSEeprom

Figure 7 Three-axis (3-component) seismic sensor unit [16]example of accelerometer used in seismic application

categorized into piezoresistive capacitive piezoelectric andtunneling accelerometers

221 Piezoresistive Piezoresistive accelerometers exploit thepiezoresistive effects of materials typically polysilicon tomeasure the acceleration [50 51]The piezoresistive elementsare embodied in structure in such a way to be subjectedto torsion when acceleration is applied [50] The structurecan typically be a suspended beam with one end attachedto a proof mass [54] The proof mass movement imposesstress changes on the piezoresistive element thus changingits resistance Figure 8 shows a typical example of this typeof accelerometer In this example the proof mass movement

Journal of Sensors 7

A B A B

SubstrateBimorph cantilevers

Proof mass

Figure 8 Piezoresistive accelerometer showing the embodiedpiezoresistors (A B) within the cantilever [43]

implies stress changes along the embedded piezoresistiveelements (polyresistors) in the bimorph cantilever AWheat-stone bridge-like circuitry is used to measure resistancechange and deduce acceleration

For more than three decades piezoresistive accelerom-eters (eg [49 52 53 55ndash64]) have shown progressiveimprovements making them a viable option for variousapplications includingmicrogravity and low frequency appli-cations [59 63]

The demonstrated performance of these devices is shownas in Figure 8

(i) Acceleration Range Piezoresistive accelerometers havebeen designed to work in ranges as small as 1 g [55] or aslarge as 250 g [61] In average they work within 10ndash50 g [4952 53 56ndash60 62ndash64] This operation range is two orders ofmagnitude larger than desired operation range (4 ngndash80mg)(ii) Bandwidth Piezoresistive accelerometer designs [53 5558ndash63] statistically tend to have a median bandwidth of1 KHzThe uppermeasurement limit typically varies between100Hz and 2KHz whereas the lower limit is conventionallynonzero (5ndash100Hz) [46 55 59 63ndash65] except for the case ofemploying nanowires [66] that are able to respond to 0Hzacceleration (static acceleration)(iii) Noise Floor The noise floor is generally in range of 100ndash500120583gradicHz [55 56 59 63 64]

Table 3 summarizes the performance characteristics ofpiezoresistive accelerometers They are advantageously sim-ple in structure fabrication and their read-out circuitry [54]On the other hand the demonstrated performance does showcapability in neither operating in sub-g domain nor achievingbandwidth lt 50Hz or a noise floor below 5 ngradicHz Addi-tionally piezoresistive accelerometers can be seen to haveintrinsic temperature sensitivity andmeasurement drifts [62]These limitations could reduce their suitability for intendedhydrocarbonmicrotremormeasurements of current concern

222 Capacitive Capacitive accelerometers are dominantaccelerometers in market The high sensitivity good noiseperformance and low temperature sensitivity are amongtheir features [54] In principle capacitive types exploitthe change of capacitance between plates on free moving

Table 3 Piezoresistive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small sim1 g Lower limit 5ndash100 Low 100 120583

Medium 10ndash50 g BW sim1 kLarge sim250 g Upper limit 100ndash2 k High 500 120583

ElectrodeSi

Insulated layer

Si

Si

d0

d0

CA

CB

X

Proof mass

Figure 9 Capacitive sensing principle [46]

and fixed microstructures when acceleration is applied [50]Figure 9 shows a simple cantilever structure of capacitivetype accelerometer The structure consists of proof masssuspended via cantilever while the movement is sensed viaelectrodes

For quantitative analysis the performance of capacitiveaccelerometers in [19 65ndash112] is presented as follows

(i) Acceleration Range Depending on order of magnitudecapacitive accelerometers can be observed to operate in fourdifferent ranges (i) sub-g (120583g-mg) range [18 96 103] (ii) 1ndash10 g range [65ndash68 76 77 80 84ndash89 92 95ndash97 100ndash102 105](iii) 10ndash100 g range [69 72ndash74 93 99 104ndash106] and (iv) above1000 g [90 91]

(ii) Bandwidth The bandwidth of capacitive accelerometerstypically starts at DC (0Hz) [65ndash68 86 104 105] in somecases it can begin at nonzero frequencies [19 79 92]Commonly their bandwidth falls in range of 100ndash1000Hzbut it can typically vary in less than 100Hz [69] and above1000Hz [85 110]

(iii) Noise Floor The noise performance of capacitiveaccelerometers varies from 4 ngradicHz [92] up to 400mgradicHz[102] More than 60 of capacitive accelerometers have noisefloor within 120583gradicHz (ie between 01 and 100 120583gradicHz)

Capacitive accelerometers offer wide performance capa-bilities as shown in Table 4 The wide capability variationenables their successful utilization in different industrial

8 Journal of Sensors

Vz

Vx

T

T T

T

CC C C

Figure 10 Accelerometer structures using piezoelectric sensing [47]

Table 4 Capacitive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small lt1mg Small lt100 Small 4 nndash1 120583Medium 1ndash10 g Medium 100ndash1 k Medium 1 120583ndash1mLarge 10ndash100 g Large gt1 k Large gt1mVery large gt1000

domains including biomedical domain navigation spacemicrogravity military and also seismology [19 65ndash112]Remarkably the authors in [92] demonstrated noise per-formance approaching the required noise floor of HyMASapplication However the device resolution is lower than thedesired value because of the wide bandwidthTherefore a gapon achieving the required noise density and bandwidth hasstill not been met

The simple structure low drift and low temperature sen-sitivity of capacitive accelerometers along with demonstratedperformance make them suitable design option for seismicapplications [46 112]

223 Piezoelectric Piezoelectric accelerometers employmaterials with piezoelectric effects to indirectly measureacceleration via amount of deposited electric charges whenstress is induced [50] They are generally featured by lowpower consumption and temperature stability and have beenused in several applications including medical and machinevibration monitoring [47 62 113ndash117]

A typical accelerometer utilizing piezoelectric principle isillustrated in Figure 10 in which the movement of the proofmass imposes deformation on the piezoelectric elements onthe supporting bimorph beam The charge deposition alongthe sensing element induces electrical potential (119881

119909and 119881

119911)

whose magnitude indicates the acceleration appliedThe performance of accelerometers is discussed as fol-

lows

(i) Acceleration Range Piezoelectric accelerometers demon-strate a measurement range around 20ndash25 g [116] but theydo not suit sub-g operation range Additionally the inheritedhysteresis effect reduces the measurement precision that isessentially required for geophysical seismic measurement(ii) Bandwidth Piezoelectric accelerometers are normallyused in dynamic operationmode which can result in leakage

Table 5 Piezoelectric accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

and creep issues [54] The dynamic range is typically within01 kHzndash10 kHz [62 113ndash116] but can be as high as 37 kHzndash35 kHz [114] or as low as 1Hzndash60Hz [47](iii) Noise Floor It falls within the range of 10 ng to 700 ng indesigns [47 116 117] whereas the early designs suffer fromlarge noise floor reaching up to 01 g [113]

Table 5 summarizes the performance characteristics ofpiezoelectric accelerometers From presented literature theyshow substantial performance improvement in the accel-eration range bandwidth and noise level over the lastdecades This could make them viable choice of design forpassive seismic However the inherited creep and tendencyfor dynamic measurements can reduce their suitability forpassive seismic geophysical applications

224 Electron Tunneling Tunneling accelerometers exploitchanges of current tunneling through insulating mediumwith change of separating displacement [48 118ndash121] Fig-ure 11 shows an accelerometer schematic using the electrontunneling principle It is seen that the tunneling tip is justbeneath a suspended proof mass A deflection electrode andproof mass electrodes provide electrostatic force required tocontrol the tunneling current

Electron tunneling is very promising in seismic appli-cation field because of performance high sensitivity smallsize and light weight compared to piezoresistive or capacitivetypes The demonstrated measurement capabilities are statedas follows(i) Acceleration Range During the last two decades 30 grange was typically reported [119 120] Later 1mg rangewas maximally reported [48 121] which proved its sensorcapability to work in seismic operation(ii) Bandwidth Frequently accelerometers are designed towork minimally at 1 kHz bandwidth [47 113ndash122] Thisrange can reach up to 6 kHz [123ndash125] Notably tunnelingaccelerometers have a limit for the minimum detectable

Journal of Sensors 9

Table 6 Tunneling accelerometers performance range

Acceleration range (g) Bandwidth(Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

Vacuum

Proof mass

HingeProof mass electrode

Tunneling tip Deflection electrode

Figure 11 Cross sectional view of tunneling accelerometer withcantilever structure [48]

frequencyThis limit is typically in range of 5ndash200Hz [48 119121](iii) Noise Floor In early tunneling devices the noise floorvaried over a range from 1 120583gradicHz to 4mgradicHz [119 120122] As technology advances a noise floor at nanometerrange (15ndash250 ngradicHz) has been achieved [48 121] Table 6summarizes the performance characteristics of tunnelingaccelerometers in literature Tunneling accelerometers showseismic grade performance with some exception on the widebandwidth of 1 kHz Therefore further filtration process isrequired for narrow bandwidth signals

225 Resistive Accelerometers Resistive accelerometers rec-ognize the change of resistance of a metal strain gauge clungto a cantilever beam Accelerating prompts twisting of thecantilever beam and hence causes variation in the resistanceof the strain gauge In case of a metal foil the geometric effectis identified significantly dominating the piezoelectric effect[50] The model of a Wheatstone bridge circuit configuredfour strain gauges which provide a voltage signal and workfor DC estimation

226 Optical Accelerometers An optical accelerometer dis-tinguishes the change of optical characteristics in an opticalfiberTheFiber BraggGrinding (FBG) is one of themost stan-dard and popular techniques for fiber optical estimation [126127] In this technique Bragg gratings are the interferencefilter composed of optical fibers The characteristic of FBGaccelerometers defines that the appraisals reflect just a narrowspectral component of actuated light Acceleration prompts adistortion of an optical fiber connected to a suspended beamcausing a change in the reflection characteristic of the Bragggratings This change can be distinguished by contrasting thespectral component of the reflected beam with the impelledlight Hence FBG accelerometer is used to perform opticalsignal analysis with DC estimations

Table 7 Sensors performance summary

Type Bandwidth(Hz)

Acceleration(g)

Noise density(gradicHz)

Capacitive 0ndash30 22120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100 120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

227 Thermal Accelerometers Thermal accelerometer hasbeen driven based on mass displacement and does notfound a popularity among others in terms of manufacturerselling [127] Therefore the suited alternative solution of thisissue is thermal accelerometer without mass displacement[127] It consists of a heater and thermocouples situatedaround the radiator in a hermetic chamber On applyingacceleration to the accelerometer hot air in the chambermoves that leads to generating an asymmetric temperatureprofile Such asymmetric profile can be identified by thethermocouples around the radiator This process is calledtransduction principle which produces a voltage signal usingthese accelerometers and work for DC estimation [128]

23 Analysis and Design Challenges For comparative anal-ysis previously mentioned works have been summarized inTable 7 [6 7 34 43 46 62ndash64] The first column shows thesensing type of accelerometers The smallest operating band-width the upper limits of acceleration range and measurednoise floor levels are listed in columns 2ndash4 respectively Thedata summarized inTable 7 indicates the superiority of capac-itive sensors to meet passive seismic sensing requirementsAccording to Section 22 signals required in passive seismicsurvey havemaximumacceleration oflt80mg andbandwidthof 1ndash30Hz with lt1 ngradicHz noise spectral density

The key in designing high resolution capacitive acceler-ometer is to reduce the devicersquos noise floor and increase itssensitivity as demonstrated in [19 88 92 93 104 122 123]The total noise floor comes from mechanical and electricalelements of the sensor

(i) Design Overview The Brownian noise is principallyproportional to the square root of damping factor (119887) andinversely proportional to the proof mass (119898) as in (17) where119896119861and 119879 are Boltzmannrsquos constant (138 times 10minus23 JK) and the

temperature in Kelvin

119886nm =

radic4119896119861119879119887

98119898

(17)

Therefore ultralow noise accelerometers have large proofmass and low gas damping in the mass-spring accelerometersystem [19 92] The mechanical noise can be defined as afunction of the temperature damping coefficient and massWhile the temperature can be set to 20∘C or 29315∘K thedamping coefficient andmass are dependent on the geometryof the structure

10 Journal of Sensors

Sensing fingers

Springs

Driving fingers

(a)

A

A998400

Wb Wa

Lb

La

LeffLf

X0

Wf

(b)

Figure 12 Structure of a lateral capacitive accelerometer (a) isometric device view (b) spring parameters (119882119887119882119886 119871119886 119871119887) and fingers

parameters (1198830119882119891 119871119891 119871eff ) [124]

In the electrical domain the noise can be minimizedby reducing the operating bandwidth Additionally a closed-loop feedback electronic circuit is required to compensate thenonlinear response of the mechanical system and to shortenthe bandwidth of the device to 30Hz To minimize the noiseeffect from amplifier the rate of capacitance change withacceleration needs to be maximized [19] Maximizing thesensitivity requires minimizing sensing gap and lowering thenatural resonant frequency [19 92 129]

As previously discussed the minimum detectable accel-eration should be = 802

24= 47 ng This implies that

the maximum mechanical noise 119886119898

should be less than086 gradicHz according to

119886119898

=

119886minradicBW

=

47 ngradic30

= 086 gradicHz (18)

In order to size the design challenges of ultralow noisefloor a case study on accelerometer design with conventionalcomb structure is considered The structure as shown inFigure 12 comprises a fixed rectangular framewith fingers anda moving proof mass fixed on the frame by spring-like shapeat both ends and surrounded by fingers at its both sides

Accelerometers noise performance is generally deter-mined by the damping coefficient and proof mass size assuggested by (5) The dominant damping mechanism in thisstructure is due to the squeeze-film effect [125]Therefore thedamping coefficient 119887 can be written in

119887 = 72119873120583119905 (

119897eff1199090

)

3

(19)

whereby 119873 is the number of comb fingers 119905 is the proofmass thickness 120583 is the viscosity of the air under atmosphericpressure 20∘C = 154 times 10minus6 kgms and 119897eff is the engagedlength of the comb fingers

Moreover the mass 119898 can be expressed in (20) where 119898

defines the mass of the proof mass 120588 is the silicon density =2330 kgm3 119897

119891is the length of comb fingers 119882

119891is the width

of comb fingers and 119860 is the area of the proof mass

119898 = 119905120588 (119860 + 119873119897119891119882119891) (20)

As a result the mechanical noise 119886nm can be expressed bysubstituting (19) and (20) in (17) to obtain

119886nm =

radic4119896119861119879 [72119873120583119905 (119897eff1199090)

3]

98 [119905120588 (119860 + 119873119897119891119882119891)]

(21)

As depicted in Figure 12(a) the proof mass parameters119860 and 119905 typically have large values compared to fingersdimensions 119871eff 119871119891119882119891 and 119883

0[124] As a result the proof

mass is effectively increased by enlarging parameters119860 and 119905The realization of sub-ngradicHz of noise spectral density

through mass maximization has a positive impact on devicesensitivityThis can be explained by the proportional relation-ship between sensitivity and mass as displayed in

119878 =

119881119904

119886in=

4119862119904

2119862119904+ 119862119901

sdot

119881m1199090

sdot

119898

119896

(22)

whereby 119878 is the sensitivity (Vg) 119862119904is the sensing capaci-

tance 119862119901is the parasitic capacitance119881m is maximum output

voltage (V) 119886in is maximum input acceleration (g) and 119896 isthe spring constant (Nm)

The maximization of sensitivity is an important designgoal This is achievable by maximizing the proof mass andminimizing the spring constant as suggested by (22) How-ever the resonant frequency has to be considered Equations(23) and (24) describe the structural dependencies of thespring constant 119896 and the device resonant frequency 119891respectively as follows

119896 = 2

1

(119899 minus 1)

3sdot 119864 (

119882119887

2119871119887

)

3

119905 (23)

119891 =

1

2120587

sdotradic

119896

119898

(24)

where 119899 is the number of mechanical spring turns 119882119887is

the width of single turn spring 119871119887is the length of single

turn spring and 119864 is Youngrsquos Modulus of silicon = 154 times

10minus6 kgms

231 Summarized Analysis of the Type of Accelerometers Forinitial analysis (18)ndash(23) have been solved yielding to the

Journal of Sensors 11

Table 8 Initial design parameters and values

Parameter Value Parameter Value119897eff 80 120583m 119899 8119897119891

85 120583m 1199090

83 120583m119882119891

48 120583m 119905 3318 120583m119873 200 119897

1198872mm

119860 5mm times 5mm 119882119887

75 120583m119898 2120583g 119886nm 085 ngrtHz119891 46Hz 119878 026

values as listed in Table 8 The table shows the parametersand the corresponding values for the design in rows 2ndash6The resulting device performance (noise resonant frequencyand sensitivity) is shown in the last two rows The tableshows that a 5mm times 5mm proof mass area was requiredEven though the sensitivity (026Vg) is lower than state-of-the-art value this device is considered large structure forconventional CMOS technology To improve the sensitivityfurther enlargement for the proof mass is required Thisshows the major challenge of the design

Therefore achieving the noise spectral density of less than1 ngradicHz on a conventional capacitive structure is challeng-ing As a result a novel structure and design optimization isexpected to meet the stringent resolution level requirements

232 Conclusion on the Analysis The excessive demandsfor hydrocarbon have pushed the exploration technologyto the era of passive seismic monitoring The technique iseconomically promising and environmentally friendly butfacing several challenges among which is the high resolutionacquisition using state-of-the-art sensorsaccelerometers

In this paper the technological gap between themeasure-ment resolution of the state-of-the-art sensors and emergingdevices is identified for passive seismic monitoring It showsdesign possibilities using capacitive sensing techniques andmotivates further work in developing optimized sensor solu-tions

Finally a solution has been provided with specificationto design such an accelerometer To enhance the resolutionand sensitivity a dimension in the order of millimeters largerthan conventional MEMS dimensions is required Moreovertechnological issues including reducing parasitic capacitanceby increasing dielectric thickness and reducing air pressurefor less damping impact beyond 1ndash10 Torr are among theconstraints hindering prospective designs

In synopsis piezoelectric accelerometers demonstrate themost astounding estimation range shock limits and oper-ating temperature capacitive accelerometers the least powerutilization and volume and piezoresistive accelerometers thevastest frequency response

3 Sensors in Seismology

Seismic study determines that the effective exploration tech-nique for imaging the geology is active seismic imagingPreviously explosives or vibroseis trucks are utilized for

Nor

mal

ized

ampl

itude

minus1

minus05

0

05

1

0 02 04 06 08 1 12 14

Time (s)

P-wave S-wave

Figure 13 A ldquogoodrdquo occurrence of P- and S-wave arrivals in timedomain [44]

Nor

mal

ized

ampl

itude

minus1minus05

0051

0 02 04 06 08 1 12 14

Time (s)

Figure 14 A random ldquonoiserdquo event at time domain [33]

generating seismic energy sensed by the network of seismicsensors which may provide the information that determinesthe prospective oil and gas traps In view of received sensordata a 3D stratigraphy map is developed This 3D map mayhelp in determining the position of hydrocarbon depositionsMoreover the increasing demand and supply of oil and gasneed industries to explore more hydrocarbons from previous50 to 80 by identifying accurate information about hydro-carbon deposition [44 45] Conventional techniques cannotprovide the correct information about the petrophysicalproperties of reservoir because the rock pores having hydro-carbon affect the physical properties of the rockwhich in turncause poor energy sensed through seismic sensors One ofthe key solutions for accurate information is passive seismicimaging technique This technique uses naturally happeningseismic signals like earth quake microtremors and oceanwaves for subsurface imaging and structuring In comparisonof conventional technique having sensing frequency in therange of 10ndash300Hz passive seismic technique monitors thelower frequency waves (below 10Hz) whichmay travel a longdistance through the earthrsquos crust without attenuation

An example of ldquoGoodrdquo event having occurrences of P-wave and S-wave at time domain is showed in Figure 13 Onthe basis of the discrete and impulsive P-wave and S-wavearrivals the event is termed ldquoGoodrdquo event [33]

Also it is shown clearly that frequency of S-wavedecreases as the frequency of P-wave increases A randomldquonoiserdquo event occurring at time domain with indeterministicproperties of ldquoGoodrdquo events is shown in Figure 14 [33]

In the area of reservoir monitoring passive seismichave applications for recording microseismic signal at nat-ural frequency for the exploration and exploitation of thehydrocarbons (ie oil and gas) [131] The study of passiveseismic at variant frequency identifies that information aboutprediction of hydrocarbon reservoir is found at low frequencyof less than 10Hz [1ndash5 132] as depicted in Table 9

12 Journal of Sensors

Table 9 Technical description of seismic data acquisition technique at low frequency

Frequency range focused Technique used Advantage Disadvantage

Modeling frequency 50ndash60Hz[25]

Spike deconvolution for lowfrequency modeling

(i) Low-cut filter is used toattenuate low frequencies

(ii) Defining technique producesbetter P-wave and S-wave seismic

section

(i) Need for recovery of broadsignal bandwidth

(ii) Poor wavelet extraction andits structure

Modeling frequency 1 KHzAcquired seismic frequency12HzReflectivity at 40Hz [26]

(i) Ultrasonic experiment(ii) Seismic data analysis

(i) Signal is reflected from a thinwater- (S

119908) or oil-saturated (S

ℎ)

layer(ii) Frequency dependent

amplitude and phase reflectionattributes have been utilized forobserving and identifying thin

liquid saturated layers

(i) Strong attenuation in the layeraffects summation of multiples

(ii) Layers with higherattenuation create travel timedelays which increase asfrequency approaches zero

Missing frequency 5ndash10Hz [27]

(i) 3D acoustic inversion(ii) Variable depth streamerseismic data acquisition(iii) 3D elastic inversioncomparison technique

(i) Variable depth streamer fordata acquisition is better for

inversion and provides missinglow frequencies directly

(ii) Left side lobe of the wavelet isproposed to reduceless

interference in the seismic signalresults in less ambiguity in

inversion

(i) There is variation in resultinginversion due to high variation in

acquisition frequency(ii) Broadband inversion may

cause obtained results outside thetarget zone

Reflection lt15HzAmplitude 40Hz [28]

(i) AVO attribute analysis(ii) VSP analysis

(i) Imaging at low frequenciesresults in robust amplitudes for

individual frequencycomponents of propagating

wavelet(ii) Frequency based seismic

imaging permits characterizingthe subsurface fluid reservoirs

(i) Quantitative analysis of AI (asfrequency) requires NMO

stretching(ii) Conventional seismic

processing software does notwork as target-oriented

processing

Based on Table 9 it is clear that the type of geophonesused in active seismic acquisition has greater size and islinearly proportional to the velocity over the resonancefrequency (about 10Hz) [25ndash28] Therefore a new design ofthe accelerometer is defined which offers a minimal signalroll-off small size and weight solution to the larger arrayslayout Also from the table it is identified that passive seismichas high potential benefits but requires special ultra noiselow frequency and short bandwidth sensing capabilitiesSince the existing device and the sensor are unable torecord at this frequency various types of sensor are studied(discussed in Section 4) Based on sensor analysis it isfound that MEMS accelerometers (capacitive) based deviceis the best replacement of existing seismological equipmentCapacitive accelerometers performed well in low bandwidthlow frequency and minimum noise Hence passive seismicexploration is an ongoing and promising research topic withthe benefit of being environmentally friendly and of low cost

31 Comparison of Technical Structure of Active andPassive Imaging

311 Active Seismic ImagingMethod In the acquisition of theactive seismic data a feedback model has been implementedwhich is based on the principal that both sources and

Pminus(z0 z0) Rcap(z0 z0)

X0(z0 z0)

120575P+(z0 z0)

S+(z0)+

X(z0 z0)

Figure 15 A feedforward model representing the upgoing anddowngoing wavefields in conventional seismic acquisition [130]

detectors are normally placed at or near the earthrsquos surfacedepicted in Figure 15 [133] It demonstrates schematically up-and downgoingwavefields happening at the reflecting surface(1199110) while the wavefields are going ldquoalongrdquo the surface being

overlookedAccordingly consider a matrix 119883

0(1199110 1199110) having a mul-

tidimensional transfer function of the subsurface (119911 gt 1199110)

Here each variable of1198830(1199110 1199110) characterized as the impulse

response of the wavefield occurred from a unit dipole sourceat 1199110and is further sensed by a unit pressure sensor at 119911

0 Also

the subscript ldquo0rdquo in 1198830symbolizes that earthrsquos surface has a

free reflection boundary that is a single round-trip (mean

Journal of Sensors 13

two-way time) has been estimated by the seismic signal fromthe subsurface (from 119911

0to 1199110) 1198830(1199110 1199110) has been utilized

as the multidimensional wavefield operator which definesthe wavefields at the reflection free acquisition surface 119911

0

119875

minus

0(1199110 1199110) as

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (25a)

or

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 120575119875

+(1199110 1199110)

+ 1198830(1199110 1199110) 119878

+

0(1199110 1199110)

(25b)

with combining

120575119875

+(1199110 1199110) = 119877

cap(1199110 1199110) 119875

minus

0(1199110 1199110) (25c)

In (25a) source matrix 119878

+

0(1199110) signifies the downgoing

wavefield of one physical source (array) at 1199110

However1198830119878

+ stands for the upgoing primary wavefields(one round-trip) and119883

0120575119875

+ stands for the upgoingmultiple-scattering wavefields (many round-trips)

Furthermore from (25a)ndash(25c) it can be simply derivedthat

1198830(1199110 1199110)

= [119868 minus 1198830(1199110 1199110) 119877

cap(1199110 1199110)]

minus1

1198830(1199110 1199110)

(26a)

representing the complexity of119883 relating to1198830 On compar-

ing (25a)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (26b)

with (25b)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) [120575119875

+(1199110 1199110) + 119878

+(1199110 1199110)] (26c)

Based on (26b) it can be concluded that the surface-related multiple-scattering phenomenon is incorporated intoa parameter 119883 However (26c) signifies that the surface-related multiple-scattering is incorporated into the downgo-ing wavefield 120575

119875

+

and the parameter 119883 determined as 1198830

Such variation between mathematical equations (26b) and(26c) assumes an imperative part in the inversion modelingfor seismic imaging [134]

Here Figure 16 represents the mixed shot record array offive sources at or near the surfaces Since during acquisitionzero time delays and large spacing between the sourcesare considered resulting incoherent shooting will becomesimultaneous shooting [136 139 140]The resultants imagingsignifies that a passive seismic recording can be measured asa naturally mixed shot record

312 Passive Seismic Imaging Method Based on DownwardRadiating Natural Sources Initially it is considered thatpseudo sources are set at or close to the surface (119911

0)

signifying that the background noise is considered as thosewavefields generated by the natural sources However in pas-sive seismic imaging response from natural sources has been

Tim

e (s)

30

25

20

15

10

05

00 1000 2000 3000 4000 5000

Lateral distance (m)

Figure 16 A mixed pseudo shot record generated by usingincoherent source array having five source elements at the surface[135 136]

considered as the seismic signal from the subsurface Thesesources might be set anyplace at the surface (119911 = 119911

0) and

in the subsurface (119911 gt 1199110) [137] Henceforth a noise model

has been createdwhichmay consider a continuing happeningseismic background noise as an indicator to determine theinformative data from these noises This concept is knownas seismic interferometry [141] Furthermore a relationshipby utilizing the wavefield diagram (see Figure 9) has beenestablished between the downgoing source wavefield at thesource level (119911

119899) and the up- and downgoing wavefields at

perception level 1199110(119911 = 119911

0) Such relation can be expressed

as

119875

+

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 119911119899)

119878

+

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110) [119882

minus1(1199110 119911119899)

119878

+

(119911119899)]

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110)

119878

+

(1199110 119911119899)

(27a)

where

119882

minus1(1199110 119911119899) = 119883

minus1

0(1199110 1199110)1198830(1199110 1199110) (27b)

Figure 17 describes the feed-forwarded model which isbased on modeling by downward radiating natural sourcesat and below the surface (119899 ge 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

313 Passive Seismic Imaging Method Based on UpwardRadiating Natural Sources In this phase like active seismicbackground noise similar type of natural sourcersquos responseis considered but the direction has been changed to the

14 Journal of Sensors

rarr(z0 zn)

W(zn z0)

Rcap(z0 z0)

rarr(zn)+X0(z0 zn)

120575rarr

(z0 zn)

n = 0 1 2 middot middot middot

Pminus

P+

S+

Figure 17 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

rarrPminus(z0 zn)

W(z0 zn)

Rcap(z0 z0)

rarrS (zn)

+ X0(zn z0)

120575rarrP (z0 zn)

n = 1 2

+

minus

Figure 18 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

contribution of ldquoupwardrdquo radiation Figure 18 depicts theresultants response which describes the correlation betweenthe upgoing source wavefields at the source level (119911

119899) and the

up- and downgoing wavefields at observation level 1199110 Such

result can be expressed as

119875

minus

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 119882(1199110 119911119899)

119878

minus

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899) +

119878

minus

(1199110 119911119899)

(28)

Figure 18 describes the feed-forwarded model which isbased on modeling by upward radiating natural sources atand below the surface (119899 gt 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

314 Statistical Description of the Modeling In the statisticalanalysis of the above designed model the above definedexpressions have been utilized on an exceptionally straight-forward medium Such medium has one horizontal reflectorand a free surface depicted in Figure 19 The stepwiseconstruction of thismedium signifies imaging in Figure 19(a)describing the conventional active seismic record where oneprimary and the surface multiples have been identified andindicated by a mathematical expression in (25b) In continu-ation Figure 19(b) describes the measurement of a responsefrom a downward radiating noise burst by implementing(27a) and (27b) while Figure 19(c) describes the upwardtransmitting patterns by estimating (28)

From these figures and equation implementation it isclearly defined that the occurrence of response and its mul-tiples takes place directly Moreover Figure 19(d) preciselydemonstrates the effect of such multiples that is the noisebursts being the summation of Figures 19(b) and 19(c)respectively

Figure 19 defines the straightforward medium whichhas one horizontal reflector and a stress-free surface HereFigure 19(a) describes the impulsive source at the surfacewhile Figure 19(b) shows at first layer the downward radiatingnoise source Similarly Figure 19(c) shows at first layerthe upward radiating noise source Finally Figure 19(d)establishes the omnidirectional noise source in the first layerof imagingOverall it has been signified that different sourcesdetermine the different resultant responses For exampleFigure 19 clearly proved this statement by demonstrating thatall sources defined here produce the different responses at ornear the subsurface of seismic imaging

32 Example Showing the Processing of Active and PassiveSeismic Imaging and Their Significance In this examplefor a mixed seismic data response inversion method fol-lowed for known and unknown sources is illustrated Herethree reflectors are utilized to measure the response forthe subsurface modeling (see Figure 20(a)) To begin withwithout considering surface-related multiples 119883

0 the mul-

tidimensional impulse response of the subsurface has beenproduced However Figures 20(b)ndash20(d) describe the three-column impulsive response of 119883

0 It results in naturally

occurring mixed recording at the subsurface Therefore inthe next modeling step surface-related multiples have beenimplemented that is from119883

0to119883

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

[1] A E de Vasconcelos Lopes and L C Nunes ldquoPitfalls of tremor-like signals for hydrocarbon exploration in producing oil fieldsin Potiguar basin northeast Brazilrdquo The Leading Edge vol 29no 7 pp 826ndash830 2010

[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

Journal of Sensors 25

[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

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2 Journal of Sensors

Figure 1 Accelerometer example Digital Sensor Unit (DSU1) [18]

frequency microtremors in helping locating the presence ofhydrocarbon reserves [1]

A time-reverse wave-propagation method is used fordetermining the ldquoGoodrdquo event of source wave in depthdomain near the well log This is because well log dataprovides better characteristics of the rocks to distinguish thehydrocarbon reserves accurately [1 2 21]

Based on the literatures and different levels of surveysit is clear that current emerging and effective data analysistechnique is passive seismic wavefield that is microtremorsat low frequency for identifying hydrocarbon reserves accu-rately [22] Since for real data analysis there must be a needfor considering production noise in themeasured data basedon this consideration the data analysis using microtremorsrequires some careful assumptions such as the following

(a) reservoir heterogeneity may cause misinterpretationof anomalies which is caused by noise

(b) high noise (or high signal-to-noise ratio) duringexploration may overwhelm seismic signals

On the other hand one inquiry likewise emerges amidinvestigation whether microtremors can attain to the bettercorrelation for both homogenous and heterogeneous kind ofreservoir or not The answer is conceivable to achievable byinvestigating the passive seismic data and its overview all themore obviously and precisely It is a direct result of the waythat passive seismic is the location of the earth encompassingseismic waves without the utilization of controlled source[18 23] MEMS based accelerometers such as 1C (DSU1)or 3C versions (DSU3) are adept in order to sense variousenvironments (eg transition zone or seabed) depicted inFigure 1They can receive extensive attention because of theirability to give rich subsurface information at low cost and inenvironmentally friendly manner [24]

The use of passive seismic as a direct hydrocarbon indi-cator (DHI) has valuable promising advantages in reducingdrilling risks well positioning and enhancing oil recovery[22] The premise of the technique is the empirical observa-tions of unique seismic energy anomalies over hydrocarbon-bearing reservoirs Existing studies attributed this phe-nomenon to the oscillation of hydrocarbon in pores driven bythe omnipresent ambient seismic waves Some mathematicalmodels interpreting the phenomenon have been developedfor example hydrocarbon microtremor analysis (HyMAS)Navier-Stokes model (NSM) and the linear harmonic oscil-lator model (LHOM) [21] On the other hand late studies

uncovered results contradicting indisputably the correlationbetween the perceptions of tremor-like signs and the pres-ence of hydrocarbon underneath [24 29 41] Thereforethis overview proposed the thought of reservoir geology inrelating watched microtremors-like signals to hydrocarbonvicinity Accordingly the principle critical concern of passiveseismic studies is to get high resolution seismic informationThis is because of the way that available sensors were notdesigned on the basis of passive seismic signal attributesmainly in terms of amplitude and bandwidth Concerningsensors performance this paper highlights the technologicalgap and motivates developing dedicated sensors for optimalsolutions

2 Technical Infrastructure (Design andModeling of Accelerometer)

A fundamental test in simulating and designing MEMSdevice is the adjacent coupling between electrical mechan-ical optical and diverse frameworks dynamic in all MEMSdevices Furthermore a primary query concerning the cou-pling of the noise is identified that signifies processing withvariant physical or dynamic components in any of the existingMEMS devices [9] That is does the vicinity of electronicnoise say Johnson (thermal) noise influence mechanical(Brownian) noise which can influence the little masses inMEMS devices and the other way around Correspondinglythermal adsorption and desorption noise has mechanicalbehavior on a subatomic level but can incorporate electroniceffects when ions are incorporated [9]

Mechanical noise for example microphonics and vibra-tions is regularly extrinsic However Brownian motion aprincipal of intrinsic mechanical noise mechanism existswhich may appear due to the dynamic unbalanced forceshappening due to the random impacts of atoms on a small ionparticle or structure Subsequently it is likewise called ldquoran-dom walkrdquo noise Brownian movement turns out to be morecritical as the span of a structure diminishes for instance theproof mass in MEMS accelerometer Adsorption-desorptioncommotion is firmly identified with the Brownianmovementbecause of random arrival and departure of distinct atomsandmolecules on the surface ofMEMSdevice Table 1 impliesthe essentialmechanical noise source for the device due to theBrownianmotion of the gas particles encompassing the proofmass and the proof mass suspension or stays In this mannerthe aggregate noise equivalent acceleration (TNEA)ms2 [42]is

TNEA =radic

4119896119861119879119887

119898

(1)

Here (1) clearly signifies that to decrease the mechanicalnoise the quality factor and proof mass must be incre-mented Since the paper involves designing the MEMS basedaccelerometer it is very much important to understand andidentify the factor causing the mechanical noise [42] Itmainly occurred due the proof mass itself which leads to theequivalent acceleration noise Such noise is dominating and

Journal of Sensors 3

Table 1 A Comparative analysis on the characterization and noise analysis of MEMS device [9]

Paper Device or structure Focus Characterization

Gabrielson [10] Accelerometers pressure sensorscapacitive microphones

Mechanical-thermalnoise Theory

Djuric [11] Accelerometers infrared thermaldetector microbeams Several mechanisms Theory

Djuric et al [12] Microcantilevers and microresonators Several mechanisms Theory andcomputations

Greiner and Korvink[13] Micro bars Mechanical noise Theory

Vig and Kim [14] Resonators (microbeams) Several mechanisms Theory andcomputations

Leland [15] Gyroscopes Mechanical-thermalnoise Theory

limiting the performance of MEMS devices especially whenoperating under low acceleration conditions

21 Principle Design of MEMS Based Accelerometer Amechanical design of Microelectromechanical System(MEMS) based accelerometer consists of proof mass 119898effective spring (with constant 119896) and damper (with coeffi-cient 119887) affecting the dynamic motion of the mass producedby the air-structure interaction as depicted in Figure 2

The operation of the accelerometer can be modeled as asecond-order mechanical system When force is acted uponon the accelerometer themass develops a forcewhich is givenby DrsquoAlembertrsquos inertial force equation 119865 = 119898 lowast 119886 This forcedisplaces the spring by a distance 119909 Hence the total forceexternally is balanced by the sum of internal forces given by[42]

119865external = 119865inertial + 119865damping + 119865spring (2)

based on the mechanical design of MEM accelerometervibration along the 119909 direction that showed the mechanicalbehavior of the system can be given by the differentialequation [42]

119898

120597

2119909

120597119905

+ 120573

120597119909

120597119905

+ 119896119909 = 119865ext = 119898119886(3)

where 119898 is effective mass 119909 is displacement 120573 is dampingcoefficient 119896 is spring stiffness 119865 is force at the moving massand 119860 is acceleration of the moving mass

Also the transfer function in Laplace domain havingdisplacement of 119909 can be represented as [42]

119909 (119904)

119886 (119904)

=

1

119904

2+ (119887119898) 119904 + 119896119898

(4)

or

119909 (119904)

119886 (119904)

=

1

119904

2+ (120596119899119876) 119904 + 120596

2

119899

(5)

where 120596119899= radic119896119898 the resonant frequency and 119876 = 120596

119899119898119887

the quality factor

Damperb

Proof massM

x

Springk

Figure 2 Mechanical design of MEMS accelerometer [9 34 42]

However the device response time has been dictatedprincipally by the natural frequency of the proofmassThuslyto accomplish critically damped acceleration damping limi-tations must be necessary to take into consideration whichpermits getting the minimum amplitude distortion [34]Thismeans 119876 = 2

radic2 Therefore

119887

2119898120596119899

=

1

radic2

(6)

But in order to characterize the damping solving thedominatorrsquos equation by estimatingΔ of the transfer functionin (4) is needed

119904

2+

119887

119898

119904 +

119896

119898

= 0

Δ = (

119887

119898

)

2

minus 4

119896

119898

(7)

For Δ = 0 thus 119887 = 2radic119896119898 a damping coefficient

Based on (6) and (7) three different cases must beconsidered in order to determine the variation in designingthe bandwidth such as the following

(i) Underdamped system where 119887 lt 2radic119896119898

(ii) Critically damped system where 119887 = 2radic119896119898

(iii) Overdamped system where 119887 gt 2radic119896119898

4 Journal of Sensors

Disp

lace

men

t

Time

UnderdampedCritically damped

Overdamped

120587

2wr

Figure 3 Step response of the accelerometer as a second-ordermechanical system [42]

However critical damping is essential for achieving max-imum bandwidth Since the absence of damping permittedvery high levels of sensor resonant amplification it is fur-thermore recognizable that mass must be sufficiently huge toacquire the desired sensitivity with weak spring as shown inFigure 3 In thismanner themechanical resonance frequencyof suspended mass is given by

120596119899=

radic

119896

119898

(8)

Such expansion and the analysis imply that in an openloop circuiting a high sensitivity of the device yields a smallbandwidth while in closed loop circuiting the resonancepeak has been suppressed by the control circuit It is alsoclear that the mechanical resonance of the sensor does notlimit the bandwidth of the device but it is limited by thetransition frequency of the control circuit [44] Howeverdue to mechanical noise Brownian motion noise comes intoaccount which has been utilized to indicate the unwantedsignal as noise in the form of acceleration noise (see Table 1)Brownian noise has significant impact on both bulk andsurface micromachined capacitive accelerometers The mea-surement of the signal produced by the noise source andunsolicited signals is noise floor therefore it is clear that thereal signal cannot be detectable if the measured signal hasa value below this noise floor Nonetheless the variation inthe frequency causes the change in the noise floor valuesconsidering theBrowniannoise having noise floor between 10and 100 120583grtHz Such noise generates the random force withBrownian motion of air molecules which occurred becauseof the damping effect applied directly to the seismic massTherefore the Power Spectral Density (PSD) of the Browniannoise force is depicted as [45]

119865

2

119861(119891) = 4119896

119861119879119887

(9a)

where 119865119861is Brownian noise force 119896

119861is Boltzmann constant

119879 is absolute temperature and 119887 is damping coefficientHere it is clear that the damping coefficient (119887) is directly

proportional to Brownian noise such that the larger the valueof damping coefficient is the higher the noise will be or viceversa as depicted in (9a) Therefore reduction in the noisevalue requires anticipating the smaller value of the damping

W A

L

dd + Δ

L

Figure 4 Capacitance change due to variation in plate separation[33]

coefficient and hence results in a smaller damping ratio[44 45] Such ratio helps in modeling MEMS accelerometerrunning at underdamped condition having an oscillatingmess in the designed accelerometer Hence to measure theaccelerometerrsquos noise performance an acceleration-referrednoise floor has been estimated by using Newtonrsquos law as [45]

119886

2

119861(119891) =

119865

2

119861

119898

2=

radic4119896119861119879119887

98

2119898

2g2Hz (9b)

Since the thermal-mechanical Brownian noise floor iswithin 10sim100 120583grtHz it might influence the processing andthe device performance where the noise is considered asprocess noise Hence the minimum detectable acceleration isgiven by

119886min = radic

8120587119896119861119879119891119899119861

119876119898

(10a)

or

119886min =radic

4119896119861119879119887119861

119898

(10b)

However from (5) and (8) the mathematical computationidentifies that the bandwidth of an accelerometer sensingelement is directly proportional to its sensitivity (119878) duringthe design it must be considered Sensitivity of capacitiveaccelerometer is defined as the ratio of the difference ofvariation in the capacitance to the difference in variation inthe displacement which is depicted as

1198780=

119860119898120576

119896119889

2=

1198620119898

119896119889

(11)

where 120576 is the electric permittivity of air119860 is the overlap areaof electrodes and 119889 is the gap between the electrodes

The most well-known utilization of capacitive detectionfor sensors depends on signals which are coupled to changesin the electrode partition 119889 Let us consider a couple ofelectrodes with area119860 and separation 119889 depicted in Figure 4[33] A physical signal causes the partition to increment by asmall amount Δ The capacitance changes

from1205761205760

119889

to1205761205760

119889 + Δ

(12a)

Journal of Sensors 5

Here the correlation between the displacement andchange in capacitance is not linear but for a small change inthe division the capacitance can be estimated by utilizing aTaylor series expansion Generally any function 119865(119889) can beapproximated in the neighborhood of some nominal valued119889(0) as follows [33]

119865 (1198890+ Δ) = 119865 (119889

0) + Δ

120597119865 (1198890)

120597119889

+

Δ

2

2

120597

2119865 (1198890)

120597119889

2

+ sdot sdot sdot

(12b)

Based on the above expression this expansion can beimplemented as

119862 asymp

1205761205760119860

119889

(1 minus

Δ

119889

+

Δ

119889

2) (12c)

where Δ = 119889 minus 1198890

So for Δ ≪ 119889 the change in capacitance has linearrelationship with respect to the displacement The nonlin-earity of the function has been considered as a correctiontermof orderΔ21198892 such that nonconsideration of such errormakes the signal remain nearly linear [33]This creates a newrelationship such that the sum of the forces on the mass isequal to the acceleration of the mass (see Figure 2) such that

119896 (119883 minus 119909) + 119887

119889 (119883 minus 119909)

119889119905

= 119898

119889

2119909

119889119905

2

(12d)

where 119883 is position of the frame in Figure 2 119909 is position ofthe mass in Figure 2

Therefore the maximum detectable acceleration havingtotal gap between the electrodes 119889max is given by

119886max = 119896

119889max119898

(12e)

Additionally the above equations signify that spring con-stant ldquo119896rdquo affects directly the resonant frequency bandwidthsensitivity and furthermore the pull-in voltage Basically thespring constant is directly proportional to the beam charac-teristics such as the length (119871) the thickness (119905) the width(119882) and the elasticity of the material coefficient (YoungrsquosModulus (119864)) [44] Such variation in the spring constantin a beam occurs due the tensile and compressive stresseswhich is considered negligible during implementation andtherefore the following equation can be defined for furtherapplication

119896 =

119882119905

3

119871

3119864

(13)

where 119864 is Youngrsquos Modulus of the material utilized havingunit of gigapascals that is GPa

Since volume of proof mass is 119881 = 119871119898119879119898119882119898and is

homogeneously parallelepiped with rectangular area (119860) thevolume must be estimated from the volumic mass density 120588

as

120588 =

119898

119881

997904rArr

119881 =

119898

120588

(14)

Therefore the computation of the thickness (119879119898) of the

device is defined as

119881 = 119871119898119882119898119879119898

= 119860 sdot 119879119898

997904rArr

119879119898

=

119881

119860

(15)

Furthermore based on the above mathematical model-ing the geometry of the design accelerometer and its proofmass are defined Such modeling of the proof mass of theaccelerometer clearly depends on the various dimensions ofthe sensing elements depicted in Figure 5

The parameters utilized in Figure 5 such as widththickness and length of the proof mass and anchor dependupon the selection of the type of themodelwhich is illustratedin Table 16 (Appendix) Furthermore the sensitivity ofthe accelerometer is dependent on the size of proof massspring constant and resonance frequency graph in Figure 6illustrating the phenomena that proof mass and resonancefrequency are inversely proportional to each other withincrease in proofmass the resonance frequency decreases andvice versa

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies (Figure 7) The technological lag betweenthe application requirements and performance offered byavailable and emerging accelerometers motivates the devel-opment of dedicated sensing technology depicted in Table 2[16ndash20]

22 Accelerometers Performance Overview MEMS devicesfor seismic applications have previously been designed usingpiezoresistive [49] capacitive [10] and piezoelectric typedsensors [50] Electron tunneling is also a very promising sens-ing mechanism due to its high sensitivity to low vibrations[51]The performance of accelerometers can be characterizedbased on demonstrated operational specifications includingthe following

(i) Acceleration Range Recording unnecessary high ampli-tude signals adversely affects sensor sensitivity and con-sequently the resolution [52] It is necessary to know theacceleration range that is defined as the maximum acceler-ation input that can be measured by the accelerometer in g(acceleration due to gravity) (asymp10msminus2) As a result an idealaccelerometer should be able to capture maximum vibrationsof geophysical interest

(ii) Bandwidth It refers to the frequency range of input accel-eration that the sensor can perform with minimum distor-tion An ideal accelerometer requires minimum bandwidthto reduce undesired noise [52] and should have maximumbandwidth that is sufficient to accommodate all signals ofinterest

(iii) Noise FloorThe noise collectively generated at the sensoroutput when no acceleration is present is referred to assensor noise floor It is a composite of three noise sourcesthe thermomechanical noise (ie Brownian noise) [49 53]

6 Journal of Sensors

Table 2 Comparison of existing MEMS accelerometers [16ndash20]

Sensor Supplier Bandwidth (Hz) Full scale (mg) Noise density (ngradicHz)Trillium [20] Nanometrics 003ndash50 mdash mdashGAC [17] WesternGeco 3ndash200 108 15DSU1 [18] Sercel 0ndash800 500 40 (gt10Hz)HP sensor [19] HP 1ndash200 80 10

Wm = 120583m

Lm = 120583m

Z

X

Y

tm = 120583m

L2 = 120583m

W = 120583m

t = 120583m

Figure 5 Sensing element dimensions

Reso

nanc

e fre

quen

cy (H

z)

60 70 80 90 100 110

Proof mass (120583g)

170

180

190

200

210

220

230

240

Figure 6 Resonance frequency versus proof mass

the thermoelectrical noise (ie Johnson noise) and the 1119891

noise (Hoogersquos noise) [54] The first one is due to the randommotion induced by thermal energy of gaseous moleculessurrounding the proof mass [10] The thermoelectrical noiseis attributed to the random electron motion in the wiresinduced by ambient thermal energy Hoogersquos noise is empiri-cal noise and is function of the frequency For simplicity thetotal noise floor 119886n can be expressed in terms of mechanicalnoise (119886nm) and electrical noise (119886ne) as displayed in

119886119899= radic119886nm

2+ 119886ne2

(16)

The noise floor is desirable to be as minimal as pos-sible but an acceptable level can be determined by therequired resolution To evaluate the need for dedicated sen-sors for hydrocarbon microtremor analysis studies availableaccelerometers have been reviewed Eventually matchinganalysis between sensing requirements and performancemetrics is performed to scope down design possibilitiesand guide promising directions Based on the employedsensing principle the discussion on performance metrics is

Telemetry cable

2 horizontal MEMSLine board

IC board

Servo-loop ASIC

V board

Vertical MEMSEeprom

Figure 7 Three-axis (3-component) seismic sensor unit [16]example of accelerometer used in seismic application

categorized into piezoresistive capacitive piezoelectric andtunneling accelerometers

221 Piezoresistive Piezoresistive accelerometers exploit thepiezoresistive effects of materials typically polysilicon tomeasure the acceleration [50 51]The piezoresistive elementsare embodied in structure in such a way to be subjectedto torsion when acceleration is applied [50] The structurecan typically be a suspended beam with one end attachedto a proof mass [54] The proof mass movement imposesstress changes on the piezoresistive element thus changingits resistance Figure 8 shows a typical example of this typeof accelerometer In this example the proof mass movement

Journal of Sensors 7

A B A B

SubstrateBimorph cantilevers

Proof mass

Figure 8 Piezoresistive accelerometer showing the embodiedpiezoresistors (A B) within the cantilever [43]

implies stress changes along the embedded piezoresistiveelements (polyresistors) in the bimorph cantilever AWheat-stone bridge-like circuitry is used to measure resistancechange and deduce acceleration

For more than three decades piezoresistive accelerom-eters (eg [49 52 53 55ndash64]) have shown progressiveimprovements making them a viable option for variousapplications includingmicrogravity and low frequency appli-cations [59 63]

The demonstrated performance of these devices is shownas in Figure 8

(i) Acceleration Range Piezoresistive accelerometers havebeen designed to work in ranges as small as 1 g [55] or aslarge as 250 g [61] In average they work within 10ndash50 g [4952 53 56ndash60 62ndash64] This operation range is two orders ofmagnitude larger than desired operation range (4 ngndash80mg)(ii) Bandwidth Piezoresistive accelerometer designs [53 5558ndash63] statistically tend to have a median bandwidth of1 KHzThe uppermeasurement limit typically varies between100Hz and 2KHz whereas the lower limit is conventionallynonzero (5ndash100Hz) [46 55 59 63ndash65] except for the case ofemploying nanowires [66] that are able to respond to 0Hzacceleration (static acceleration)(iii) Noise Floor The noise floor is generally in range of 100ndash500120583gradicHz [55 56 59 63 64]

Table 3 summarizes the performance characteristics ofpiezoresistive accelerometers They are advantageously sim-ple in structure fabrication and their read-out circuitry [54]On the other hand the demonstrated performance does showcapability in neither operating in sub-g domain nor achievingbandwidth lt 50Hz or a noise floor below 5 ngradicHz Addi-tionally piezoresistive accelerometers can be seen to haveintrinsic temperature sensitivity andmeasurement drifts [62]These limitations could reduce their suitability for intendedhydrocarbonmicrotremormeasurements of current concern

222 Capacitive Capacitive accelerometers are dominantaccelerometers in market The high sensitivity good noiseperformance and low temperature sensitivity are amongtheir features [54] In principle capacitive types exploitthe change of capacitance between plates on free moving

Table 3 Piezoresistive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small sim1 g Lower limit 5ndash100 Low 100 120583

Medium 10ndash50 g BW sim1 kLarge sim250 g Upper limit 100ndash2 k High 500 120583

ElectrodeSi

Insulated layer

Si

Si

d0

d0

CA

CB

X

Proof mass

Figure 9 Capacitive sensing principle [46]

and fixed microstructures when acceleration is applied [50]Figure 9 shows a simple cantilever structure of capacitivetype accelerometer The structure consists of proof masssuspended via cantilever while the movement is sensed viaelectrodes

For quantitative analysis the performance of capacitiveaccelerometers in [19 65ndash112] is presented as follows

(i) Acceleration Range Depending on order of magnitudecapacitive accelerometers can be observed to operate in fourdifferent ranges (i) sub-g (120583g-mg) range [18 96 103] (ii) 1ndash10 g range [65ndash68 76 77 80 84ndash89 92 95ndash97 100ndash102 105](iii) 10ndash100 g range [69 72ndash74 93 99 104ndash106] and (iv) above1000 g [90 91]

(ii) Bandwidth The bandwidth of capacitive accelerometerstypically starts at DC (0Hz) [65ndash68 86 104 105] in somecases it can begin at nonzero frequencies [19 79 92]Commonly their bandwidth falls in range of 100ndash1000Hzbut it can typically vary in less than 100Hz [69] and above1000Hz [85 110]

(iii) Noise Floor The noise performance of capacitiveaccelerometers varies from 4 ngradicHz [92] up to 400mgradicHz[102] More than 60 of capacitive accelerometers have noisefloor within 120583gradicHz (ie between 01 and 100 120583gradicHz)

Capacitive accelerometers offer wide performance capa-bilities as shown in Table 4 The wide capability variationenables their successful utilization in different industrial

8 Journal of Sensors

Vz

Vx

T

T T

T

CC C C

Figure 10 Accelerometer structures using piezoelectric sensing [47]

Table 4 Capacitive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small lt1mg Small lt100 Small 4 nndash1 120583Medium 1ndash10 g Medium 100ndash1 k Medium 1 120583ndash1mLarge 10ndash100 g Large gt1 k Large gt1mVery large gt1000

domains including biomedical domain navigation spacemicrogravity military and also seismology [19 65ndash112]Remarkably the authors in [92] demonstrated noise per-formance approaching the required noise floor of HyMASapplication However the device resolution is lower than thedesired value because of the wide bandwidthTherefore a gapon achieving the required noise density and bandwidth hasstill not been met

The simple structure low drift and low temperature sen-sitivity of capacitive accelerometers along with demonstratedperformance make them suitable design option for seismicapplications [46 112]

223 Piezoelectric Piezoelectric accelerometers employmaterials with piezoelectric effects to indirectly measureacceleration via amount of deposited electric charges whenstress is induced [50] They are generally featured by lowpower consumption and temperature stability and have beenused in several applications including medical and machinevibration monitoring [47 62 113ndash117]

A typical accelerometer utilizing piezoelectric principle isillustrated in Figure 10 in which the movement of the proofmass imposes deformation on the piezoelectric elements onthe supporting bimorph beam The charge deposition alongthe sensing element induces electrical potential (119881

119909and 119881

119911)

whose magnitude indicates the acceleration appliedThe performance of accelerometers is discussed as fol-

lows

(i) Acceleration Range Piezoelectric accelerometers demon-strate a measurement range around 20ndash25 g [116] but theydo not suit sub-g operation range Additionally the inheritedhysteresis effect reduces the measurement precision that isessentially required for geophysical seismic measurement(ii) Bandwidth Piezoelectric accelerometers are normallyused in dynamic operationmode which can result in leakage

Table 5 Piezoelectric accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

and creep issues [54] The dynamic range is typically within01 kHzndash10 kHz [62 113ndash116] but can be as high as 37 kHzndash35 kHz [114] or as low as 1Hzndash60Hz [47](iii) Noise Floor It falls within the range of 10 ng to 700 ng indesigns [47 116 117] whereas the early designs suffer fromlarge noise floor reaching up to 01 g [113]

Table 5 summarizes the performance characteristics ofpiezoelectric accelerometers From presented literature theyshow substantial performance improvement in the accel-eration range bandwidth and noise level over the lastdecades This could make them viable choice of design forpassive seismic However the inherited creep and tendencyfor dynamic measurements can reduce their suitability forpassive seismic geophysical applications

224 Electron Tunneling Tunneling accelerometers exploitchanges of current tunneling through insulating mediumwith change of separating displacement [48 118ndash121] Fig-ure 11 shows an accelerometer schematic using the electrontunneling principle It is seen that the tunneling tip is justbeneath a suspended proof mass A deflection electrode andproof mass electrodes provide electrostatic force required tocontrol the tunneling current

Electron tunneling is very promising in seismic appli-cation field because of performance high sensitivity smallsize and light weight compared to piezoresistive or capacitivetypes The demonstrated measurement capabilities are statedas follows(i) Acceleration Range During the last two decades 30 grange was typically reported [119 120] Later 1mg rangewas maximally reported [48 121] which proved its sensorcapability to work in seismic operation(ii) Bandwidth Frequently accelerometers are designed towork minimally at 1 kHz bandwidth [47 113ndash122] Thisrange can reach up to 6 kHz [123ndash125] Notably tunnelingaccelerometers have a limit for the minimum detectable

Journal of Sensors 9

Table 6 Tunneling accelerometers performance range

Acceleration range (g) Bandwidth(Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

Vacuum

Proof mass

HingeProof mass electrode

Tunneling tip Deflection electrode

Figure 11 Cross sectional view of tunneling accelerometer withcantilever structure [48]

frequencyThis limit is typically in range of 5ndash200Hz [48 119121](iii) Noise Floor In early tunneling devices the noise floorvaried over a range from 1 120583gradicHz to 4mgradicHz [119 120122] As technology advances a noise floor at nanometerrange (15ndash250 ngradicHz) has been achieved [48 121] Table 6summarizes the performance characteristics of tunnelingaccelerometers in literature Tunneling accelerometers showseismic grade performance with some exception on the widebandwidth of 1 kHz Therefore further filtration process isrequired for narrow bandwidth signals

225 Resistive Accelerometers Resistive accelerometers rec-ognize the change of resistance of a metal strain gauge clungto a cantilever beam Accelerating prompts twisting of thecantilever beam and hence causes variation in the resistanceof the strain gauge In case of a metal foil the geometric effectis identified significantly dominating the piezoelectric effect[50] The model of a Wheatstone bridge circuit configuredfour strain gauges which provide a voltage signal and workfor DC estimation

226 Optical Accelerometers An optical accelerometer dis-tinguishes the change of optical characteristics in an opticalfiberTheFiber BraggGrinding (FBG) is one of themost stan-dard and popular techniques for fiber optical estimation [126127] In this technique Bragg gratings are the interferencefilter composed of optical fibers The characteristic of FBGaccelerometers defines that the appraisals reflect just a narrowspectral component of actuated light Acceleration prompts adistortion of an optical fiber connected to a suspended beamcausing a change in the reflection characteristic of the Bragggratings This change can be distinguished by contrasting thespectral component of the reflected beam with the impelledlight Hence FBG accelerometer is used to perform opticalsignal analysis with DC estimations

Table 7 Sensors performance summary

Type Bandwidth(Hz)

Acceleration(g)

Noise density(gradicHz)

Capacitive 0ndash30 22120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100 120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

227 Thermal Accelerometers Thermal accelerometer hasbeen driven based on mass displacement and does notfound a popularity among others in terms of manufacturerselling [127] Therefore the suited alternative solution of thisissue is thermal accelerometer without mass displacement[127] It consists of a heater and thermocouples situatedaround the radiator in a hermetic chamber On applyingacceleration to the accelerometer hot air in the chambermoves that leads to generating an asymmetric temperatureprofile Such asymmetric profile can be identified by thethermocouples around the radiator This process is calledtransduction principle which produces a voltage signal usingthese accelerometers and work for DC estimation [128]

23 Analysis and Design Challenges For comparative anal-ysis previously mentioned works have been summarized inTable 7 [6 7 34 43 46 62ndash64] The first column shows thesensing type of accelerometers The smallest operating band-width the upper limits of acceleration range and measurednoise floor levels are listed in columns 2ndash4 respectively Thedata summarized inTable 7 indicates the superiority of capac-itive sensors to meet passive seismic sensing requirementsAccording to Section 22 signals required in passive seismicsurvey havemaximumacceleration oflt80mg andbandwidthof 1ndash30Hz with lt1 ngradicHz noise spectral density

The key in designing high resolution capacitive acceler-ometer is to reduce the devicersquos noise floor and increase itssensitivity as demonstrated in [19 88 92 93 104 122 123]The total noise floor comes from mechanical and electricalelements of the sensor

(i) Design Overview The Brownian noise is principallyproportional to the square root of damping factor (119887) andinversely proportional to the proof mass (119898) as in (17) where119896119861and 119879 are Boltzmannrsquos constant (138 times 10minus23 JK) and the

temperature in Kelvin

119886nm =

radic4119896119861119879119887

98119898

(17)

Therefore ultralow noise accelerometers have large proofmass and low gas damping in the mass-spring accelerometersystem [19 92] The mechanical noise can be defined as afunction of the temperature damping coefficient and massWhile the temperature can be set to 20∘C or 29315∘K thedamping coefficient andmass are dependent on the geometryof the structure

10 Journal of Sensors

Sensing fingers

Springs

Driving fingers

(a)

A

A998400

Wb Wa

Lb

La

LeffLf

X0

Wf

(b)

Figure 12 Structure of a lateral capacitive accelerometer (a) isometric device view (b) spring parameters (119882119887119882119886 119871119886 119871119887) and fingers

parameters (1198830119882119891 119871119891 119871eff ) [124]

In the electrical domain the noise can be minimizedby reducing the operating bandwidth Additionally a closed-loop feedback electronic circuit is required to compensate thenonlinear response of the mechanical system and to shortenthe bandwidth of the device to 30Hz To minimize the noiseeffect from amplifier the rate of capacitance change withacceleration needs to be maximized [19] Maximizing thesensitivity requires minimizing sensing gap and lowering thenatural resonant frequency [19 92 129]

As previously discussed the minimum detectable accel-eration should be = 802

24= 47 ng This implies that

the maximum mechanical noise 119886119898

should be less than086 gradicHz according to

119886119898

=

119886minradicBW

=

47 ngradic30

= 086 gradicHz (18)

In order to size the design challenges of ultralow noisefloor a case study on accelerometer design with conventionalcomb structure is considered The structure as shown inFigure 12 comprises a fixed rectangular framewith fingers anda moving proof mass fixed on the frame by spring-like shapeat both ends and surrounded by fingers at its both sides

Accelerometers noise performance is generally deter-mined by the damping coefficient and proof mass size assuggested by (5) The dominant damping mechanism in thisstructure is due to the squeeze-film effect [125]Therefore thedamping coefficient 119887 can be written in

119887 = 72119873120583119905 (

119897eff1199090

)

3

(19)

whereby 119873 is the number of comb fingers 119905 is the proofmass thickness 120583 is the viscosity of the air under atmosphericpressure 20∘C = 154 times 10minus6 kgms and 119897eff is the engagedlength of the comb fingers

Moreover the mass 119898 can be expressed in (20) where 119898

defines the mass of the proof mass 120588 is the silicon density =2330 kgm3 119897

119891is the length of comb fingers 119882

119891is the width

of comb fingers and 119860 is the area of the proof mass

119898 = 119905120588 (119860 + 119873119897119891119882119891) (20)

As a result the mechanical noise 119886nm can be expressed bysubstituting (19) and (20) in (17) to obtain

119886nm =

radic4119896119861119879 [72119873120583119905 (119897eff1199090)

3]

98 [119905120588 (119860 + 119873119897119891119882119891)]

(21)

As depicted in Figure 12(a) the proof mass parameters119860 and 119905 typically have large values compared to fingersdimensions 119871eff 119871119891119882119891 and 119883

0[124] As a result the proof

mass is effectively increased by enlarging parameters119860 and 119905The realization of sub-ngradicHz of noise spectral density

through mass maximization has a positive impact on devicesensitivityThis can be explained by the proportional relation-ship between sensitivity and mass as displayed in

119878 =

119881119904

119886in=

4119862119904

2119862119904+ 119862119901

sdot

119881m1199090

sdot

119898

119896

(22)

whereby 119878 is the sensitivity (Vg) 119862119904is the sensing capaci-

tance 119862119901is the parasitic capacitance119881m is maximum output

voltage (V) 119886in is maximum input acceleration (g) and 119896 isthe spring constant (Nm)

The maximization of sensitivity is an important designgoal This is achievable by maximizing the proof mass andminimizing the spring constant as suggested by (22) How-ever the resonant frequency has to be considered Equations(23) and (24) describe the structural dependencies of thespring constant 119896 and the device resonant frequency 119891respectively as follows

119896 = 2

1

(119899 minus 1)

3sdot 119864 (

119882119887

2119871119887

)

3

119905 (23)

119891 =

1

2120587

sdotradic

119896

119898

(24)

where 119899 is the number of mechanical spring turns 119882119887is

the width of single turn spring 119871119887is the length of single

turn spring and 119864 is Youngrsquos Modulus of silicon = 154 times

10minus6 kgms

231 Summarized Analysis of the Type of Accelerometers Forinitial analysis (18)ndash(23) have been solved yielding to the

Journal of Sensors 11

Table 8 Initial design parameters and values

Parameter Value Parameter Value119897eff 80 120583m 119899 8119897119891

85 120583m 1199090

83 120583m119882119891

48 120583m 119905 3318 120583m119873 200 119897

1198872mm

119860 5mm times 5mm 119882119887

75 120583m119898 2120583g 119886nm 085 ngrtHz119891 46Hz 119878 026

values as listed in Table 8 The table shows the parametersand the corresponding values for the design in rows 2ndash6The resulting device performance (noise resonant frequencyand sensitivity) is shown in the last two rows The tableshows that a 5mm times 5mm proof mass area was requiredEven though the sensitivity (026Vg) is lower than state-of-the-art value this device is considered large structure forconventional CMOS technology To improve the sensitivityfurther enlargement for the proof mass is required Thisshows the major challenge of the design

Therefore achieving the noise spectral density of less than1 ngradicHz on a conventional capacitive structure is challeng-ing As a result a novel structure and design optimization isexpected to meet the stringent resolution level requirements

232 Conclusion on the Analysis The excessive demandsfor hydrocarbon have pushed the exploration technologyto the era of passive seismic monitoring The technique iseconomically promising and environmentally friendly butfacing several challenges among which is the high resolutionacquisition using state-of-the-art sensorsaccelerometers

In this paper the technological gap between themeasure-ment resolution of the state-of-the-art sensors and emergingdevices is identified for passive seismic monitoring It showsdesign possibilities using capacitive sensing techniques andmotivates further work in developing optimized sensor solu-tions

Finally a solution has been provided with specificationto design such an accelerometer To enhance the resolutionand sensitivity a dimension in the order of millimeters largerthan conventional MEMS dimensions is required Moreovertechnological issues including reducing parasitic capacitanceby increasing dielectric thickness and reducing air pressurefor less damping impact beyond 1ndash10 Torr are among theconstraints hindering prospective designs

In synopsis piezoelectric accelerometers demonstrate themost astounding estimation range shock limits and oper-ating temperature capacitive accelerometers the least powerutilization and volume and piezoresistive accelerometers thevastest frequency response

3 Sensors in Seismology

Seismic study determines that the effective exploration tech-nique for imaging the geology is active seismic imagingPreviously explosives or vibroseis trucks are utilized for

Nor

mal

ized

ampl

itude

minus1

minus05

0

05

1

0 02 04 06 08 1 12 14

Time (s)

P-wave S-wave

Figure 13 A ldquogoodrdquo occurrence of P- and S-wave arrivals in timedomain [44]

Nor

mal

ized

ampl

itude

minus1minus05

0051

0 02 04 06 08 1 12 14

Time (s)

Figure 14 A random ldquonoiserdquo event at time domain [33]

generating seismic energy sensed by the network of seismicsensors which may provide the information that determinesthe prospective oil and gas traps In view of received sensordata a 3D stratigraphy map is developed This 3D map mayhelp in determining the position of hydrocarbon depositionsMoreover the increasing demand and supply of oil and gasneed industries to explore more hydrocarbons from previous50 to 80 by identifying accurate information about hydro-carbon deposition [44 45] Conventional techniques cannotprovide the correct information about the petrophysicalproperties of reservoir because the rock pores having hydro-carbon affect the physical properties of the rockwhich in turncause poor energy sensed through seismic sensors One ofthe key solutions for accurate information is passive seismicimaging technique This technique uses naturally happeningseismic signals like earth quake microtremors and oceanwaves for subsurface imaging and structuring In comparisonof conventional technique having sensing frequency in therange of 10ndash300Hz passive seismic technique monitors thelower frequency waves (below 10Hz) whichmay travel a longdistance through the earthrsquos crust without attenuation

An example of ldquoGoodrdquo event having occurrences of P-wave and S-wave at time domain is showed in Figure 13 Onthe basis of the discrete and impulsive P-wave and S-wavearrivals the event is termed ldquoGoodrdquo event [33]

Also it is shown clearly that frequency of S-wavedecreases as the frequency of P-wave increases A randomldquonoiserdquo event occurring at time domain with indeterministicproperties of ldquoGoodrdquo events is shown in Figure 14 [33]

In the area of reservoir monitoring passive seismichave applications for recording microseismic signal at nat-ural frequency for the exploration and exploitation of thehydrocarbons (ie oil and gas) [131] The study of passiveseismic at variant frequency identifies that information aboutprediction of hydrocarbon reservoir is found at low frequencyof less than 10Hz [1ndash5 132] as depicted in Table 9

12 Journal of Sensors

Table 9 Technical description of seismic data acquisition technique at low frequency

Frequency range focused Technique used Advantage Disadvantage

Modeling frequency 50ndash60Hz[25]

Spike deconvolution for lowfrequency modeling

(i) Low-cut filter is used toattenuate low frequencies

(ii) Defining technique producesbetter P-wave and S-wave seismic

section

(i) Need for recovery of broadsignal bandwidth

(ii) Poor wavelet extraction andits structure

Modeling frequency 1 KHzAcquired seismic frequency12HzReflectivity at 40Hz [26]

(i) Ultrasonic experiment(ii) Seismic data analysis

(i) Signal is reflected from a thinwater- (S

119908) or oil-saturated (S

ℎ)

layer(ii) Frequency dependent

amplitude and phase reflectionattributes have been utilized forobserving and identifying thin

liquid saturated layers

(i) Strong attenuation in the layeraffects summation of multiples

(ii) Layers with higherattenuation create travel timedelays which increase asfrequency approaches zero

Missing frequency 5ndash10Hz [27]

(i) 3D acoustic inversion(ii) Variable depth streamerseismic data acquisition(iii) 3D elastic inversioncomparison technique

(i) Variable depth streamer fordata acquisition is better for

inversion and provides missinglow frequencies directly

(ii) Left side lobe of the wavelet isproposed to reduceless

interference in the seismic signalresults in less ambiguity in

inversion

(i) There is variation in resultinginversion due to high variation in

acquisition frequency(ii) Broadband inversion may

cause obtained results outside thetarget zone

Reflection lt15HzAmplitude 40Hz [28]

(i) AVO attribute analysis(ii) VSP analysis

(i) Imaging at low frequenciesresults in robust amplitudes for

individual frequencycomponents of propagating

wavelet(ii) Frequency based seismic

imaging permits characterizingthe subsurface fluid reservoirs

(i) Quantitative analysis of AI (asfrequency) requires NMO

stretching(ii) Conventional seismic

processing software does notwork as target-oriented

processing

Based on Table 9 it is clear that the type of geophonesused in active seismic acquisition has greater size and islinearly proportional to the velocity over the resonancefrequency (about 10Hz) [25ndash28] Therefore a new design ofthe accelerometer is defined which offers a minimal signalroll-off small size and weight solution to the larger arrayslayout Also from the table it is identified that passive seismichas high potential benefits but requires special ultra noiselow frequency and short bandwidth sensing capabilitiesSince the existing device and the sensor are unable torecord at this frequency various types of sensor are studied(discussed in Section 4) Based on sensor analysis it isfound that MEMS accelerometers (capacitive) based deviceis the best replacement of existing seismological equipmentCapacitive accelerometers performed well in low bandwidthlow frequency and minimum noise Hence passive seismicexploration is an ongoing and promising research topic withthe benefit of being environmentally friendly and of low cost

31 Comparison of Technical Structure of Active andPassive Imaging

311 Active Seismic ImagingMethod In the acquisition of theactive seismic data a feedback model has been implementedwhich is based on the principal that both sources and

Pminus(z0 z0) Rcap(z0 z0)

X0(z0 z0)

120575P+(z0 z0)

S+(z0)+

X(z0 z0)

Figure 15 A feedforward model representing the upgoing anddowngoing wavefields in conventional seismic acquisition [130]

detectors are normally placed at or near the earthrsquos surfacedepicted in Figure 15 [133] It demonstrates schematically up-and downgoingwavefields happening at the reflecting surface(1199110) while the wavefields are going ldquoalongrdquo the surface being

overlookedAccordingly consider a matrix 119883

0(1199110 1199110) having a mul-

tidimensional transfer function of the subsurface (119911 gt 1199110)

Here each variable of1198830(1199110 1199110) characterized as the impulse

response of the wavefield occurred from a unit dipole sourceat 1199110and is further sensed by a unit pressure sensor at 119911

0 Also

the subscript ldquo0rdquo in 1198830symbolizes that earthrsquos surface has a

free reflection boundary that is a single round-trip (mean

Journal of Sensors 13

two-way time) has been estimated by the seismic signal fromthe subsurface (from 119911

0to 1199110) 1198830(1199110 1199110) has been utilized

as the multidimensional wavefield operator which definesthe wavefields at the reflection free acquisition surface 119911

0

119875

minus

0(1199110 1199110) as

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (25a)

or

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 120575119875

+(1199110 1199110)

+ 1198830(1199110 1199110) 119878

+

0(1199110 1199110)

(25b)

with combining

120575119875

+(1199110 1199110) = 119877

cap(1199110 1199110) 119875

minus

0(1199110 1199110) (25c)

In (25a) source matrix 119878

+

0(1199110) signifies the downgoing

wavefield of one physical source (array) at 1199110

However1198830119878

+ stands for the upgoing primary wavefields(one round-trip) and119883

0120575119875

+ stands for the upgoingmultiple-scattering wavefields (many round-trips)

Furthermore from (25a)ndash(25c) it can be simply derivedthat

1198830(1199110 1199110)

= [119868 minus 1198830(1199110 1199110) 119877

cap(1199110 1199110)]

minus1

1198830(1199110 1199110)

(26a)

representing the complexity of119883 relating to1198830 On compar-

ing (25a)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (26b)

with (25b)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) [120575119875

+(1199110 1199110) + 119878

+(1199110 1199110)] (26c)

Based on (26b) it can be concluded that the surface-related multiple-scattering phenomenon is incorporated intoa parameter 119883 However (26c) signifies that the surface-related multiple-scattering is incorporated into the downgo-ing wavefield 120575

119875

+

and the parameter 119883 determined as 1198830

Such variation between mathematical equations (26b) and(26c) assumes an imperative part in the inversion modelingfor seismic imaging [134]

Here Figure 16 represents the mixed shot record array offive sources at or near the surfaces Since during acquisitionzero time delays and large spacing between the sourcesare considered resulting incoherent shooting will becomesimultaneous shooting [136 139 140]The resultants imagingsignifies that a passive seismic recording can be measured asa naturally mixed shot record

312 Passive Seismic Imaging Method Based on DownwardRadiating Natural Sources Initially it is considered thatpseudo sources are set at or close to the surface (119911

0)

signifying that the background noise is considered as thosewavefields generated by the natural sources However in pas-sive seismic imaging response from natural sources has been

Tim

e (s)

30

25

20

15

10

05

00 1000 2000 3000 4000 5000

Lateral distance (m)

Figure 16 A mixed pseudo shot record generated by usingincoherent source array having five source elements at the surface[135 136]

considered as the seismic signal from the subsurface Thesesources might be set anyplace at the surface (119911 = 119911

0) and

in the subsurface (119911 gt 1199110) [137] Henceforth a noise model

has been createdwhichmay consider a continuing happeningseismic background noise as an indicator to determine theinformative data from these noises This concept is knownas seismic interferometry [141] Furthermore a relationshipby utilizing the wavefield diagram (see Figure 9) has beenestablished between the downgoing source wavefield at thesource level (119911

119899) and the up- and downgoing wavefields at

perception level 1199110(119911 = 119911

0) Such relation can be expressed

as

119875

+

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 119911119899)

119878

+

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110) [119882

minus1(1199110 119911119899)

119878

+

(119911119899)]

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110)

119878

+

(1199110 119911119899)

(27a)

where

119882

minus1(1199110 119911119899) = 119883

minus1

0(1199110 1199110)1198830(1199110 1199110) (27b)

Figure 17 describes the feed-forwarded model which isbased on modeling by downward radiating natural sourcesat and below the surface (119899 ge 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

313 Passive Seismic Imaging Method Based on UpwardRadiating Natural Sources In this phase like active seismicbackground noise similar type of natural sourcersquos responseis considered but the direction has been changed to the

14 Journal of Sensors

rarr(z0 zn)

W(zn z0)

Rcap(z0 z0)

rarr(zn)+X0(z0 zn)

120575rarr

(z0 zn)

n = 0 1 2 middot middot middot

Pminus

P+

S+

Figure 17 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

rarrPminus(z0 zn)

W(z0 zn)

Rcap(z0 z0)

rarrS (zn)

+ X0(zn z0)

120575rarrP (z0 zn)

n = 1 2

+

minus

Figure 18 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

contribution of ldquoupwardrdquo radiation Figure 18 depicts theresultants response which describes the correlation betweenthe upgoing source wavefields at the source level (119911

119899) and the

up- and downgoing wavefields at observation level 1199110 Such

result can be expressed as

119875

minus

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 119882(1199110 119911119899)

119878

minus

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899) +

119878

minus

(1199110 119911119899)

(28)

Figure 18 describes the feed-forwarded model which isbased on modeling by upward radiating natural sources atand below the surface (119899 gt 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

314 Statistical Description of the Modeling In the statisticalanalysis of the above designed model the above definedexpressions have been utilized on an exceptionally straight-forward medium Such medium has one horizontal reflectorand a free surface depicted in Figure 19 The stepwiseconstruction of thismedium signifies imaging in Figure 19(a)describing the conventional active seismic record where oneprimary and the surface multiples have been identified andindicated by a mathematical expression in (25b) In continu-ation Figure 19(b) describes the measurement of a responsefrom a downward radiating noise burst by implementing(27a) and (27b) while Figure 19(c) describes the upwardtransmitting patterns by estimating (28)

From these figures and equation implementation it isclearly defined that the occurrence of response and its mul-tiples takes place directly Moreover Figure 19(d) preciselydemonstrates the effect of such multiples that is the noisebursts being the summation of Figures 19(b) and 19(c)respectively

Figure 19 defines the straightforward medium whichhas one horizontal reflector and a stress-free surface HereFigure 19(a) describes the impulsive source at the surfacewhile Figure 19(b) shows at first layer the downward radiatingnoise source Similarly Figure 19(c) shows at first layerthe upward radiating noise source Finally Figure 19(d)establishes the omnidirectional noise source in the first layerof imagingOverall it has been signified that different sourcesdetermine the different resultant responses For exampleFigure 19 clearly proved this statement by demonstrating thatall sources defined here produce the different responses at ornear the subsurface of seismic imaging

32 Example Showing the Processing of Active and PassiveSeismic Imaging and Their Significance In this examplefor a mixed seismic data response inversion method fol-lowed for known and unknown sources is illustrated Herethree reflectors are utilized to measure the response forthe subsurface modeling (see Figure 20(a)) To begin withwithout considering surface-related multiples 119883

0 the mul-

tidimensional impulse response of the subsurface has beenproduced However Figures 20(b)ndash20(d) describe the three-column impulsive response of 119883

0 It results in naturally

occurring mixed recording at the subsurface Therefore inthe next modeling step surface-related multiples have beenimplemented that is from119883

0to119883

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

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[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

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[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

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Journal of Sensors 3

Table 1 A Comparative analysis on the characterization and noise analysis of MEMS device [9]

Paper Device or structure Focus Characterization

Gabrielson [10] Accelerometers pressure sensorscapacitive microphones

Mechanical-thermalnoise Theory

Djuric [11] Accelerometers infrared thermaldetector microbeams Several mechanisms Theory

Djuric et al [12] Microcantilevers and microresonators Several mechanisms Theory andcomputations

Greiner and Korvink[13] Micro bars Mechanical noise Theory

Vig and Kim [14] Resonators (microbeams) Several mechanisms Theory andcomputations

Leland [15] Gyroscopes Mechanical-thermalnoise Theory

limiting the performance of MEMS devices especially whenoperating under low acceleration conditions

21 Principle Design of MEMS Based Accelerometer Amechanical design of Microelectromechanical System(MEMS) based accelerometer consists of proof mass 119898effective spring (with constant 119896) and damper (with coeffi-cient 119887) affecting the dynamic motion of the mass producedby the air-structure interaction as depicted in Figure 2

The operation of the accelerometer can be modeled as asecond-order mechanical system When force is acted uponon the accelerometer themass develops a forcewhich is givenby DrsquoAlembertrsquos inertial force equation 119865 = 119898 lowast 119886 This forcedisplaces the spring by a distance 119909 Hence the total forceexternally is balanced by the sum of internal forces given by[42]

119865external = 119865inertial + 119865damping + 119865spring (2)

based on the mechanical design of MEM accelerometervibration along the 119909 direction that showed the mechanicalbehavior of the system can be given by the differentialequation [42]

119898

120597

2119909

120597119905

+ 120573

120597119909

120597119905

+ 119896119909 = 119865ext = 119898119886(3)

where 119898 is effective mass 119909 is displacement 120573 is dampingcoefficient 119896 is spring stiffness 119865 is force at the moving massand 119860 is acceleration of the moving mass

Also the transfer function in Laplace domain havingdisplacement of 119909 can be represented as [42]

119909 (119904)

119886 (119904)

=

1

119904

2+ (119887119898) 119904 + 119896119898

(4)

or

119909 (119904)

119886 (119904)

=

1

119904

2+ (120596119899119876) 119904 + 120596

2

119899

(5)

where 120596119899= radic119896119898 the resonant frequency and 119876 = 120596

119899119898119887

the quality factor

Damperb

Proof massM

x

Springk

Figure 2 Mechanical design of MEMS accelerometer [9 34 42]

However the device response time has been dictatedprincipally by the natural frequency of the proofmassThuslyto accomplish critically damped acceleration damping limi-tations must be necessary to take into consideration whichpermits getting the minimum amplitude distortion [34]Thismeans 119876 = 2

radic2 Therefore

119887

2119898120596119899

=

1

radic2

(6)

But in order to characterize the damping solving thedominatorrsquos equation by estimatingΔ of the transfer functionin (4) is needed

119904

2+

119887

119898

119904 +

119896

119898

= 0

Δ = (

119887

119898

)

2

minus 4

119896

119898

(7)

For Δ = 0 thus 119887 = 2radic119896119898 a damping coefficient

Based on (6) and (7) three different cases must beconsidered in order to determine the variation in designingthe bandwidth such as the following

(i) Underdamped system where 119887 lt 2radic119896119898

(ii) Critically damped system where 119887 = 2radic119896119898

(iii) Overdamped system where 119887 gt 2radic119896119898

4 Journal of Sensors

Disp

lace

men

t

Time

UnderdampedCritically damped

Overdamped

120587

2wr

Figure 3 Step response of the accelerometer as a second-ordermechanical system [42]

However critical damping is essential for achieving max-imum bandwidth Since the absence of damping permittedvery high levels of sensor resonant amplification it is fur-thermore recognizable that mass must be sufficiently huge toacquire the desired sensitivity with weak spring as shown inFigure 3 In thismanner themechanical resonance frequencyof suspended mass is given by

120596119899=

radic

119896

119898

(8)

Such expansion and the analysis imply that in an openloop circuiting a high sensitivity of the device yields a smallbandwidth while in closed loop circuiting the resonancepeak has been suppressed by the control circuit It is alsoclear that the mechanical resonance of the sensor does notlimit the bandwidth of the device but it is limited by thetransition frequency of the control circuit [44] Howeverdue to mechanical noise Brownian motion noise comes intoaccount which has been utilized to indicate the unwantedsignal as noise in the form of acceleration noise (see Table 1)Brownian noise has significant impact on both bulk andsurface micromachined capacitive accelerometers The mea-surement of the signal produced by the noise source andunsolicited signals is noise floor therefore it is clear that thereal signal cannot be detectable if the measured signal hasa value below this noise floor Nonetheless the variation inthe frequency causes the change in the noise floor valuesconsidering theBrowniannoise having noise floor between 10and 100 120583grtHz Such noise generates the random force withBrownian motion of air molecules which occurred becauseof the damping effect applied directly to the seismic massTherefore the Power Spectral Density (PSD) of the Browniannoise force is depicted as [45]

119865

2

119861(119891) = 4119896

119861119879119887

(9a)

where 119865119861is Brownian noise force 119896

119861is Boltzmann constant

119879 is absolute temperature and 119887 is damping coefficientHere it is clear that the damping coefficient (119887) is directly

proportional to Brownian noise such that the larger the valueof damping coefficient is the higher the noise will be or viceversa as depicted in (9a) Therefore reduction in the noisevalue requires anticipating the smaller value of the damping

W A

L

dd + Δ

L

Figure 4 Capacitance change due to variation in plate separation[33]

coefficient and hence results in a smaller damping ratio[44 45] Such ratio helps in modeling MEMS accelerometerrunning at underdamped condition having an oscillatingmess in the designed accelerometer Hence to measure theaccelerometerrsquos noise performance an acceleration-referrednoise floor has been estimated by using Newtonrsquos law as [45]

119886

2

119861(119891) =

119865

2

119861

119898

2=

radic4119896119861119879119887

98

2119898

2g2Hz (9b)

Since the thermal-mechanical Brownian noise floor iswithin 10sim100 120583grtHz it might influence the processing andthe device performance where the noise is considered asprocess noise Hence the minimum detectable acceleration isgiven by

119886min = radic

8120587119896119861119879119891119899119861

119876119898

(10a)

or

119886min =radic

4119896119861119879119887119861

119898

(10b)

However from (5) and (8) the mathematical computationidentifies that the bandwidth of an accelerometer sensingelement is directly proportional to its sensitivity (119878) duringthe design it must be considered Sensitivity of capacitiveaccelerometer is defined as the ratio of the difference ofvariation in the capacitance to the difference in variation inthe displacement which is depicted as

1198780=

119860119898120576

119896119889

2=

1198620119898

119896119889

(11)

where 120576 is the electric permittivity of air119860 is the overlap areaof electrodes and 119889 is the gap between the electrodes

The most well-known utilization of capacitive detectionfor sensors depends on signals which are coupled to changesin the electrode partition 119889 Let us consider a couple ofelectrodes with area119860 and separation 119889 depicted in Figure 4[33] A physical signal causes the partition to increment by asmall amount Δ The capacitance changes

from1205761205760

119889

to1205761205760

119889 + Δ

(12a)

Journal of Sensors 5

Here the correlation between the displacement andchange in capacitance is not linear but for a small change inthe division the capacitance can be estimated by utilizing aTaylor series expansion Generally any function 119865(119889) can beapproximated in the neighborhood of some nominal valued119889(0) as follows [33]

119865 (1198890+ Δ) = 119865 (119889

0) + Δ

120597119865 (1198890)

120597119889

+

Δ

2

2

120597

2119865 (1198890)

120597119889

2

+ sdot sdot sdot

(12b)

Based on the above expression this expansion can beimplemented as

119862 asymp

1205761205760119860

119889

(1 minus

Δ

119889

+

Δ

119889

2) (12c)

where Δ = 119889 minus 1198890

So for Δ ≪ 119889 the change in capacitance has linearrelationship with respect to the displacement The nonlin-earity of the function has been considered as a correctiontermof orderΔ21198892 such that nonconsideration of such errormakes the signal remain nearly linear [33]This creates a newrelationship such that the sum of the forces on the mass isequal to the acceleration of the mass (see Figure 2) such that

119896 (119883 minus 119909) + 119887

119889 (119883 minus 119909)

119889119905

= 119898

119889

2119909

119889119905

2

(12d)

where 119883 is position of the frame in Figure 2 119909 is position ofthe mass in Figure 2

Therefore the maximum detectable acceleration havingtotal gap between the electrodes 119889max is given by

119886max = 119896

119889max119898

(12e)

Additionally the above equations signify that spring con-stant ldquo119896rdquo affects directly the resonant frequency bandwidthsensitivity and furthermore the pull-in voltage Basically thespring constant is directly proportional to the beam charac-teristics such as the length (119871) the thickness (119905) the width(119882) and the elasticity of the material coefficient (YoungrsquosModulus (119864)) [44] Such variation in the spring constantin a beam occurs due the tensile and compressive stresseswhich is considered negligible during implementation andtherefore the following equation can be defined for furtherapplication

119896 =

119882119905

3

119871

3119864

(13)

where 119864 is Youngrsquos Modulus of the material utilized havingunit of gigapascals that is GPa

Since volume of proof mass is 119881 = 119871119898119879119898119882119898and is

homogeneously parallelepiped with rectangular area (119860) thevolume must be estimated from the volumic mass density 120588

as

120588 =

119898

119881

997904rArr

119881 =

119898

120588

(14)

Therefore the computation of the thickness (119879119898) of the

device is defined as

119881 = 119871119898119882119898119879119898

= 119860 sdot 119879119898

997904rArr

119879119898

=

119881

119860

(15)

Furthermore based on the above mathematical model-ing the geometry of the design accelerometer and its proofmass are defined Such modeling of the proof mass of theaccelerometer clearly depends on the various dimensions ofthe sensing elements depicted in Figure 5

The parameters utilized in Figure 5 such as widththickness and length of the proof mass and anchor dependupon the selection of the type of themodelwhich is illustratedin Table 16 (Appendix) Furthermore the sensitivity ofthe accelerometer is dependent on the size of proof massspring constant and resonance frequency graph in Figure 6illustrating the phenomena that proof mass and resonancefrequency are inversely proportional to each other withincrease in proofmass the resonance frequency decreases andvice versa

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies (Figure 7) The technological lag betweenthe application requirements and performance offered byavailable and emerging accelerometers motivates the devel-opment of dedicated sensing technology depicted in Table 2[16ndash20]

22 Accelerometers Performance Overview MEMS devicesfor seismic applications have previously been designed usingpiezoresistive [49] capacitive [10] and piezoelectric typedsensors [50] Electron tunneling is also a very promising sens-ing mechanism due to its high sensitivity to low vibrations[51]The performance of accelerometers can be characterizedbased on demonstrated operational specifications includingthe following

(i) Acceleration Range Recording unnecessary high ampli-tude signals adversely affects sensor sensitivity and con-sequently the resolution [52] It is necessary to know theacceleration range that is defined as the maximum acceler-ation input that can be measured by the accelerometer in g(acceleration due to gravity) (asymp10msminus2) As a result an idealaccelerometer should be able to capture maximum vibrationsof geophysical interest

(ii) Bandwidth It refers to the frequency range of input accel-eration that the sensor can perform with minimum distor-tion An ideal accelerometer requires minimum bandwidthto reduce undesired noise [52] and should have maximumbandwidth that is sufficient to accommodate all signals ofinterest

(iii) Noise FloorThe noise collectively generated at the sensoroutput when no acceleration is present is referred to assensor noise floor It is a composite of three noise sourcesthe thermomechanical noise (ie Brownian noise) [49 53]

6 Journal of Sensors

Table 2 Comparison of existing MEMS accelerometers [16ndash20]

Sensor Supplier Bandwidth (Hz) Full scale (mg) Noise density (ngradicHz)Trillium [20] Nanometrics 003ndash50 mdash mdashGAC [17] WesternGeco 3ndash200 108 15DSU1 [18] Sercel 0ndash800 500 40 (gt10Hz)HP sensor [19] HP 1ndash200 80 10

Wm = 120583m

Lm = 120583m

Z

X

Y

tm = 120583m

L2 = 120583m

W = 120583m

t = 120583m

Figure 5 Sensing element dimensions

Reso

nanc

e fre

quen

cy (H

z)

60 70 80 90 100 110

Proof mass (120583g)

170

180

190

200

210

220

230

240

Figure 6 Resonance frequency versus proof mass

the thermoelectrical noise (ie Johnson noise) and the 1119891

noise (Hoogersquos noise) [54] The first one is due to the randommotion induced by thermal energy of gaseous moleculessurrounding the proof mass [10] The thermoelectrical noiseis attributed to the random electron motion in the wiresinduced by ambient thermal energy Hoogersquos noise is empiri-cal noise and is function of the frequency For simplicity thetotal noise floor 119886n can be expressed in terms of mechanicalnoise (119886nm) and electrical noise (119886ne) as displayed in

119886119899= radic119886nm

2+ 119886ne2

(16)

The noise floor is desirable to be as minimal as pos-sible but an acceptable level can be determined by therequired resolution To evaluate the need for dedicated sen-sors for hydrocarbon microtremor analysis studies availableaccelerometers have been reviewed Eventually matchinganalysis between sensing requirements and performancemetrics is performed to scope down design possibilitiesand guide promising directions Based on the employedsensing principle the discussion on performance metrics is

Telemetry cable

2 horizontal MEMSLine board

IC board

Servo-loop ASIC

V board

Vertical MEMSEeprom

Figure 7 Three-axis (3-component) seismic sensor unit [16]example of accelerometer used in seismic application

categorized into piezoresistive capacitive piezoelectric andtunneling accelerometers

221 Piezoresistive Piezoresistive accelerometers exploit thepiezoresistive effects of materials typically polysilicon tomeasure the acceleration [50 51]The piezoresistive elementsare embodied in structure in such a way to be subjectedto torsion when acceleration is applied [50] The structurecan typically be a suspended beam with one end attachedto a proof mass [54] The proof mass movement imposesstress changes on the piezoresistive element thus changingits resistance Figure 8 shows a typical example of this typeof accelerometer In this example the proof mass movement

Journal of Sensors 7

A B A B

SubstrateBimorph cantilevers

Proof mass

Figure 8 Piezoresistive accelerometer showing the embodiedpiezoresistors (A B) within the cantilever [43]

implies stress changes along the embedded piezoresistiveelements (polyresistors) in the bimorph cantilever AWheat-stone bridge-like circuitry is used to measure resistancechange and deduce acceleration

For more than three decades piezoresistive accelerom-eters (eg [49 52 53 55ndash64]) have shown progressiveimprovements making them a viable option for variousapplications includingmicrogravity and low frequency appli-cations [59 63]

The demonstrated performance of these devices is shownas in Figure 8

(i) Acceleration Range Piezoresistive accelerometers havebeen designed to work in ranges as small as 1 g [55] or aslarge as 250 g [61] In average they work within 10ndash50 g [4952 53 56ndash60 62ndash64] This operation range is two orders ofmagnitude larger than desired operation range (4 ngndash80mg)(ii) Bandwidth Piezoresistive accelerometer designs [53 5558ndash63] statistically tend to have a median bandwidth of1 KHzThe uppermeasurement limit typically varies between100Hz and 2KHz whereas the lower limit is conventionallynonzero (5ndash100Hz) [46 55 59 63ndash65] except for the case ofemploying nanowires [66] that are able to respond to 0Hzacceleration (static acceleration)(iii) Noise Floor The noise floor is generally in range of 100ndash500120583gradicHz [55 56 59 63 64]

Table 3 summarizes the performance characteristics ofpiezoresistive accelerometers They are advantageously sim-ple in structure fabrication and their read-out circuitry [54]On the other hand the demonstrated performance does showcapability in neither operating in sub-g domain nor achievingbandwidth lt 50Hz or a noise floor below 5 ngradicHz Addi-tionally piezoresistive accelerometers can be seen to haveintrinsic temperature sensitivity andmeasurement drifts [62]These limitations could reduce their suitability for intendedhydrocarbonmicrotremormeasurements of current concern

222 Capacitive Capacitive accelerometers are dominantaccelerometers in market The high sensitivity good noiseperformance and low temperature sensitivity are amongtheir features [54] In principle capacitive types exploitthe change of capacitance between plates on free moving

Table 3 Piezoresistive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small sim1 g Lower limit 5ndash100 Low 100 120583

Medium 10ndash50 g BW sim1 kLarge sim250 g Upper limit 100ndash2 k High 500 120583

ElectrodeSi

Insulated layer

Si

Si

d0

d0

CA

CB

X

Proof mass

Figure 9 Capacitive sensing principle [46]

and fixed microstructures when acceleration is applied [50]Figure 9 shows a simple cantilever structure of capacitivetype accelerometer The structure consists of proof masssuspended via cantilever while the movement is sensed viaelectrodes

For quantitative analysis the performance of capacitiveaccelerometers in [19 65ndash112] is presented as follows

(i) Acceleration Range Depending on order of magnitudecapacitive accelerometers can be observed to operate in fourdifferent ranges (i) sub-g (120583g-mg) range [18 96 103] (ii) 1ndash10 g range [65ndash68 76 77 80 84ndash89 92 95ndash97 100ndash102 105](iii) 10ndash100 g range [69 72ndash74 93 99 104ndash106] and (iv) above1000 g [90 91]

(ii) Bandwidth The bandwidth of capacitive accelerometerstypically starts at DC (0Hz) [65ndash68 86 104 105] in somecases it can begin at nonzero frequencies [19 79 92]Commonly their bandwidth falls in range of 100ndash1000Hzbut it can typically vary in less than 100Hz [69] and above1000Hz [85 110]

(iii) Noise Floor The noise performance of capacitiveaccelerometers varies from 4 ngradicHz [92] up to 400mgradicHz[102] More than 60 of capacitive accelerometers have noisefloor within 120583gradicHz (ie between 01 and 100 120583gradicHz)

Capacitive accelerometers offer wide performance capa-bilities as shown in Table 4 The wide capability variationenables their successful utilization in different industrial

8 Journal of Sensors

Vz

Vx

T

T T

T

CC C C

Figure 10 Accelerometer structures using piezoelectric sensing [47]

Table 4 Capacitive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small lt1mg Small lt100 Small 4 nndash1 120583Medium 1ndash10 g Medium 100ndash1 k Medium 1 120583ndash1mLarge 10ndash100 g Large gt1 k Large gt1mVery large gt1000

domains including biomedical domain navigation spacemicrogravity military and also seismology [19 65ndash112]Remarkably the authors in [92] demonstrated noise per-formance approaching the required noise floor of HyMASapplication However the device resolution is lower than thedesired value because of the wide bandwidthTherefore a gapon achieving the required noise density and bandwidth hasstill not been met

The simple structure low drift and low temperature sen-sitivity of capacitive accelerometers along with demonstratedperformance make them suitable design option for seismicapplications [46 112]

223 Piezoelectric Piezoelectric accelerometers employmaterials with piezoelectric effects to indirectly measureacceleration via amount of deposited electric charges whenstress is induced [50] They are generally featured by lowpower consumption and temperature stability and have beenused in several applications including medical and machinevibration monitoring [47 62 113ndash117]

A typical accelerometer utilizing piezoelectric principle isillustrated in Figure 10 in which the movement of the proofmass imposes deformation on the piezoelectric elements onthe supporting bimorph beam The charge deposition alongthe sensing element induces electrical potential (119881

119909and 119881

119911)

whose magnitude indicates the acceleration appliedThe performance of accelerometers is discussed as fol-

lows

(i) Acceleration Range Piezoelectric accelerometers demon-strate a measurement range around 20ndash25 g [116] but theydo not suit sub-g operation range Additionally the inheritedhysteresis effect reduces the measurement precision that isessentially required for geophysical seismic measurement(ii) Bandwidth Piezoelectric accelerometers are normallyused in dynamic operationmode which can result in leakage

Table 5 Piezoelectric accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

and creep issues [54] The dynamic range is typically within01 kHzndash10 kHz [62 113ndash116] but can be as high as 37 kHzndash35 kHz [114] or as low as 1Hzndash60Hz [47](iii) Noise Floor It falls within the range of 10 ng to 700 ng indesigns [47 116 117] whereas the early designs suffer fromlarge noise floor reaching up to 01 g [113]

Table 5 summarizes the performance characteristics ofpiezoelectric accelerometers From presented literature theyshow substantial performance improvement in the accel-eration range bandwidth and noise level over the lastdecades This could make them viable choice of design forpassive seismic However the inherited creep and tendencyfor dynamic measurements can reduce their suitability forpassive seismic geophysical applications

224 Electron Tunneling Tunneling accelerometers exploitchanges of current tunneling through insulating mediumwith change of separating displacement [48 118ndash121] Fig-ure 11 shows an accelerometer schematic using the electrontunneling principle It is seen that the tunneling tip is justbeneath a suspended proof mass A deflection electrode andproof mass electrodes provide electrostatic force required tocontrol the tunneling current

Electron tunneling is very promising in seismic appli-cation field because of performance high sensitivity smallsize and light weight compared to piezoresistive or capacitivetypes The demonstrated measurement capabilities are statedas follows(i) Acceleration Range During the last two decades 30 grange was typically reported [119 120] Later 1mg rangewas maximally reported [48 121] which proved its sensorcapability to work in seismic operation(ii) Bandwidth Frequently accelerometers are designed towork minimally at 1 kHz bandwidth [47 113ndash122] Thisrange can reach up to 6 kHz [123ndash125] Notably tunnelingaccelerometers have a limit for the minimum detectable

Journal of Sensors 9

Table 6 Tunneling accelerometers performance range

Acceleration range (g) Bandwidth(Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

Vacuum

Proof mass

HingeProof mass electrode

Tunneling tip Deflection electrode

Figure 11 Cross sectional view of tunneling accelerometer withcantilever structure [48]

frequencyThis limit is typically in range of 5ndash200Hz [48 119121](iii) Noise Floor In early tunneling devices the noise floorvaried over a range from 1 120583gradicHz to 4mgradicHz [119 120122] As technology advances a noise floor at nanometerrange (15ndash250 ngradicHz) has been achieved [48 121] Table 6summarizes the performance characteristics of tunnelingaccelerometers in literature Tunneling accelerometers showseismic grade performance with some exception on the widebandwidth of 1 kHz Therefore further filtration process isrequired for narrow bandwidth signals

225 Resistive Accelerometers Resistive accelerometers rec-ognize the change of resistance of a metal strain gauge clungto a cantilever beam Accelerating prompts twisting of thecantilever beam and hence causes variation in the resistanceof the strain gauge In case of a metal foil the geometric effectis identified significantly dominating the piezoelectric effect[50] The model of a Wheatstone bridge circuit configuredfour strain gauges which provide a voltage signal and workfor DC estimation

226 Optical Accelerometers An optical accelerometer dis-tinguishes the change of optical characteristics in an opticalfiberTheFiber BraggGrinding (FBG) is one of themost stan-dard and popular techniques for fiber optical estimation [126127] In this technique Bragg gratings are the interferencefilter composed of optical fibers The characteristic of FBGaccelerometers defines that the appraisals reflect just a narrowspectral component of actuated light Acceleration prompts adistortion of an optical fiber connected to a suspended beamcausing a change in the reflection characteristic of the Bragggratings This change can be distinguished by contrasting thespectral component of the reflected beam with the impelledlight Hence FBG accelerometer is used to perform opticalsignal analysis with DC estimations

Table 7 Sensors performance summary

Type Bandwidth(Hz)

Acceleration(g)

Noise density(gradicHz)

Capacitive 0ndash30 22120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100 120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

227 Thermal Accelerometers Thermal accelerometer hasbeen driven based on mass displacement and does notfound a popularity among others in terms of manufacturerselling [127] Therefore the suited alternative solution of thisissue is thermal accelerometer without mass displacement[127] It consists of a heater and thermocouples situatedaround the radiator in a hermetic chamber On applyingacceleration to the accelerometer hot air in the chambermoves that leads to generating an asymmetric temperatureprofile Such asymmetric profile can be identified by thethermocouples around the radiator This process is calledtransduction principle which produces a voltage signal usingthese accelerometers and work for DC estimation [128]

23 Analysis and Design Challenges For comparative anal-ysis previously mentioned works have been summarized inTable 7 [6 7 34 43 46 62ndash64] The first column shows thesensing type of accelerometers The smallest operating band-width the upper limits of acceleration range and measurednoise floor levels are listed in columns 2ndash4 respectively Thedata summarized inTable 7 indicates the superiority of capac-itive sensors to meet passive seismic sensing requirementsAccording to Section 22 signals required in passive seismicsurvey havemaximumacceleration oflt80mg andbandwidthof 1ndash30Hz with lt1 ngradicHz noise spectral density

The key in designing high resolution capacitive acceler-ometer is to reduce the devicersquos noise floor and increase itssensitivity as demonstrated in [19 88 92 93 104 122 123]The total noise floor comes from mechanical and electricalelements of the sensor

(i) Design Overview The Brownian noise is principallyproportional to the square root of damping factor (119887) andinversely proportional to the proof mass (119898) as in (17) where119896119861and 119879 are Boltzmannrsquos constant (138 times 10minus23 JK) and the

temperature in Kelvin

119886nm =

radic4119896119861119879119887

98119898

(17)

Therefore ultralow noise accelerometers have large proofmass and low gas damping in the mass-spring accelerometersystem [19 92] The mechanical noise can be defined as afunction of the temperature damping coefficient and massWhile the temperature can be set to 20∘C or 29315∘K thedamping coefficient andmass are dependent on the geometryof the structure

10 Journal of Sensors

Sensing fingers

Springs

Driving fingers

(a)

A

A998400

Wb Wa

Lb

La

LeffLf

X0

Wf

(b)

Figure 12 Structure of a lateral capacitive accelerometer (a) isometric device view (b) spring parameters (119882119887119882119886 119871119886 119871119887) and fingers

parameters (1198830119882119891 119871119891 119871eff ) [124]

In the electrical domain the noise can be minimizedby reducing the operating bandwidth Additionally a closed-loop feedback electronic circuit is required to compensate thenonlinear response of the mechanical system and to shortenthe bandwidth of the device to 30Hz To minimize the noiseeffect from amplifier the rate of capacitance change withacceleration needs to be maximized [19] Maximizing thesensitivity requires minimizing sensing gap and lowering thenatural resonant frequency [19 92 129]

As previously discussed the minimum detectable accel-eration should be = 802

24= 47 ng This implies that

the maximum mechanical noise 119886119898

should be less than086 gradicHz according to

119886119898

=

119886minradicBW

=

47 ngradic30

= 086 gradicHz (18)

In order to size the design challenges of ultralow noisefloor a case study on accelerometer design with conventionalcomb structure is considered The structure as shown inFigure 12 comprises a fixed rectangular framewith fingers anda moving proof mass fixed on the frame by spring-like shapeat both ends and surrounded by fingers at its both sides

Accelerometers noise performance is generally deter-mined by the damping coefficient and proof mass size assuggested by (5) The dominant damping mechanism in thisstructure is due to the squeeze-film effect [125]Therefore thedamping coefficient 119887 can be written in

119887 = 72119873120583119905 (

119897eff1199090

)

3

(19)

whereby 119873 is the number of comb fingers 119905 is the proofmass thickness 120583 is the viscosity of the air under atmosphericpressure 20∘C = 154 times 10minus6 kgms and 119897eff is the engagedlength of the comb fingers

Moreover the mass 119898 can be expressed in (20) where 119898

defines the mass of the proof mass 120588 is the silicon density =2330 kgm3 119897

119891is the length of comb fingers 119882

119891is the width

of comb fingers and 119860 is the area of the proof mass

119898 = 119905120588 (119860 + 119873119897119891119882119891) (20)

As a result the mechanical noise 119886nm can be expressed bysubstituting (19) and (20) in (17) to obtain

119886nm =

radic4119896119861119879 [72119873120583119905 (119897eff1199090)

3]

98 [119905120588 (119860 + 119873119897119891119882119891)]

(21)

As depicted in Figure 12(a) the proof mass parameters119860 and 119905 typically have large values compared to fingersdimensions 119871eff 119871119891119882119891 and 119883

0[124] As a result the proof

mass is effectively increased by enlarging parameters119860 and 119905The realization of sub-ngradicHz of noise spectral density

through mass maximization has a positive impact on devicesensitivityThis can be explained by the proportional relation-ship between sensitivity and mass as displayed in

119878 =

119881119904

119886in=

4119862119904

2119862119904+ 119862119901

sdot

119881m1199090

sdot

119898

119896

(22)

whereby 119878 is the sensitivity (Vg) 119862119904is the sensing capaci-

tance 119862119901is the parasitic capacitance119881m is maximum output

voltage (V) 119886in is maximum input acceleration (g) and 119896 isthe spring constant (Nm)

The maximization of sensitivity is an important designgoal This is achievable by maximizing the proof mass andminimizing the spring constant as suggested by (22) How-ever the resonant frequency has to be considered Equations(23) and (24) describe the structural dependencies of thespring constant 119896 and the device resonant frequency 119891respectively as follows

119896 = 2

1

(119899 minus 1)

3sdot 119864 (

119882119887

2119871119887

)

3

119905 (23)

119891 =

1

2120587

sdotradic

119896

119898

(24)

where 119899 is the number of mechanical spring turns 119882119887is

the width of single turn spring 119871119887is the length of single

turn spring and 119864 is Youngrsquos Modulus of silicon = 154 times

10minus6 kgms

231 Summarized Analysis of the Type of Accelerometers Forinitial analysis (18)ndash(23) have been solved yielding to the

Journal of Sensors 11

Table 8 Initial design parameters and values

Parameter Value Parameter Value119897eff 80 120583m 119899 8119897119891

85 120583m 1199090

83 120583m119882119891

48 120583m 119905 3318 120583m119873 200 119897

1198872mm

119860 5mm times 5mm 119882119887

75 120583m119898 2120583g 119886nm 085 ngrtHz119891 46Hz 119878 026

values as listed in Table 8 The table shows the parametersand the corresponding values for the design in rows 2ndash6The resulting device performance (noise resonant frequencyand sensitivity) is shown in the last two rows The tableshows that a 5mm times 5mm proof mass area was requiredEven though the sensitivity (026Vg) is lower than state-of-the-art value this device is considered large structure forconventional CMOS technology To improve the sensitivityfurther enlargement for the proof mass is required Thisshows the major challenge of the design

Therefore achieving the noise spectral density of less than1 ngradicHz on a conventional capacitive structure is challeng-ing As a result a novel structure and design optimization isexpected to meet the stringent resolution level requirements

232 Conclusion on the Analysis The excessive demandsfor hydrocarbon have pushed the exploration technologyto the era of passive seismic monitoring The technique iseconomically promising and environmentally friendly butfacing several challenges among which is the high resolutionacquisition using state-of-the-art sensorsaccelerometers

In this paper the technological gap between themeasure-ment resolution of the state-of-the-art sensors and emergingdevices is identified for passive seismic monitoring It showsdesign possibilities using capacitive sensing techniques andmotivates further work in developing optimized sensor solu-tions

Finally a solution has been provided with specificationto design such an accelerometer To enhance the resolutionand sensitivity a dimension in the order of millimeters largerthan conventional MEMS dimensions is required Moreovertechnological issues including reducing parasitic capacitanceby increasing dielectric thickness and reducing air pressurefor less damping impact beyond 1ndash10 Torr are among theconstraints hindering prospective designs

In synopsis piezoelectric accelerometers demonstrate themost astounding estimation range shock limits and oper-ating temperature capacitive accelerometers the least powerutilization and volume and piezoresistive accelerometers thevastest frequency response

3 Sensors in Seismology

Seismic study determines that the effective exploration tech-nique for imaging the geology is active seismic imagingPreviously explosives or vibroseis trucks are utilized for

Nor

mal

ized

ampl

itude

minus1

minus05

0

05

1

0 02 04 06 08 1 12 14

Time (s)

P-wave S-wave

Figure 13 A ldquogoodrdquo occurrence of P- and S-wave arrivals in timedomain [44]

Nor

mal

ized

ampl

itude

minus1minus05

0051

0 02 04 06 08 1 12 14

Time (s)

Figure 14 A random ldquonoiserdquo event at time domain [33]

generating seismic energy sensed by the network of seismicsensors which may provide the information that determinesthe prospective oil and gas traps In view of received sensordata a 3D stratigraphy map is developed This 3D map mayhelp in determining the position of hydrocarbon depositionsMoreover the increasing demand and supply of oil and gasneed industries to explore more hydrocarbons from previous50 to 80 by identifying accurate information about hydro-carbon deposition [44 45] Conventional techniques cannotprovide the correct information about the petrophysicalproperties of reservoir because the rock pores having hydro-carbon affect the physical properties of the rockwhich in turncause poor energy sensed through seismic sensors One ofthe key solutions for accurate information is passive seismicimaging technique This technique uses naturally happeningseismic signals like earth quake microtremors and oceanwaves for subsurface imaging and structuring In comparisonof conventional technique having sensing frequency in therange of 10ndash300Hz passive seismic technique monitors thelower frequency waves (below 10Hz) whichmay travel a longdistance through the earthrsquos crust without attenuation

An example of ldquoGoodrdquo event having occurrences of P-wave and S-wave at time domain is showed in Figure 13 Onthe basis of the discrete and impulsive P-wave and S-wavearrivals the event is termed ldquoGoodrdquo event [33]

Also it is shown clearly that frequency of S-wavedecreases as the frequency of P-wave increases A randomldquonoiserdquo event occurring at time domain with indeterministicproperties of ldquoGoodrdquo events is shown in Figure 14 [33]

In the area of reservoir monitoring passive seismichave applications for recording microseismic signal at nat-ural frequency for the exploration and exploitation of thehydrocarbons (ie oil and gas) [131] The study of passiveseismic at variant frequency identifies that information aboutprediction of hydrocarbon reservoir is found at low frequencyof less than 10Hz [1ndash5 132] as depicted in Table 9

12 Journal of Sensors

Table 9 Technical description of seismic data acquisition technique at low frequency

Frequency range focused Technique used Advantage Disadvantage

Modeling frequency 50ndash60Hz[25]

Spike deconvolution for lowfrequency modeling

(i) Low-cut filter is used toattenuate low frequencies

(ii) Defining technique producesbetter P-wave and S-wave seismic

section

(i) Need for recovery of broadsignal bandwidth

(ii) Poor wavelet extraction andits structure

Modeling frequency 1 KHzAcquired seismic frequency12HzReflectivity at 40Hz [26]

(i) Ultrasonic experiment(ii) Seismic data analysis

(i) Signal is reflected from a thinwater- (S

119908) or oil-saturated (S

ℎ)

layer(ii) Frequency dependent

amplitude and phase reflectionattributes have been utilized forobserving and identifying thin

liquid saturated layers

(i) Strong attenuation in the layeraffects summation of multiples

(ii) Layers with higherattenuation create travel timedelays which increase asfrequency approaches zero

Missing frequency 5ndash10Hz [27]

(i) 3D acoustic inversion(ii) Variable depth streamerseismic data acquisition(iii) 3D elastic inversioncomparison technique

(i) Variable depth streamer fordata acquisition is better for

inversion and provides missinglow frequencies directly

(ii) Left side lobe of the wavelet isproposed to reduceless

interference in the seismic signalresults in less ambiguity in

inversion

(i) There is variation in resultinginversion due to high variation in

acquisition frequency(ii) Broadband inversion may

cause obtained results outside thetarget zone

Reflection lt15HzAmplitude 40Hz [28]

(i) AVO attribute analysis(ii) VSP analysis

(i) Imaging at low frequenciesresults in robust amplitudes for

individual frequencycomponents of propagating

wavelet(ii) Frequency based seismic

imaging permits characterizingthe subsurface fluid reservoirs

(i) Quantitative analysis of AI (asfrequency) requires NMO

stretching(ii) Conventional seismic

processing software does notwork as target-oriented

processing

Based on Table 9 it is clear that the type of geophonesused in active seismic acquisition has greater size and islinearly proportional to the velocity over the resonancefrequency (about 10Hz) [25ndash28] Therefore a new design ofthe accelerometer is defined which offers a minimal signalroll-off small size and weight solution to the larger arrayslayout Also from the table it is identified that passive seismichas high potential benefits but requires special ultra noiselow frequency and short bandwidth sensing capabilitiesSince the existing device and the sensor are unable torecord at this frequency various types of sensor are studied(discussed in Section 4) Based on sensor analysis it isfound that MEMS accelerometers (capacitive) based deviceis the best replacement of existing seismological equipmentCapacitive accelerometers performed well in low bandwidthlow frequency and minimum noise Hence passive seismicexploration is an ongoing and promising research topic withthe benefit of being environmentally friendly and of low cost

31 Comparison of Technical Structure of Active andPassive Imaging

311 Active Seismic ImagingMethod In the acquisition of theactive seismic data a feedback model has been implementedwhich is based on the principal that both sources and

Pminus(z0 z0) Rcap(z0 z0)

X0(z0 z0)

120575P+(z0 z0)

S+(z0)+

X(z0 z0)

Figure 15 A feedforward model representing the upgoing anddowngoing wavefields in conventional seismic acquisition [130]

detectors are normally placed at or near the earthrsquos surfacedepicted in Figure 15 [133] It demonstrates schematically up-and downgoingwavefields happening at the reflecting surface(1199110) while the wavefields are going ldquoalongrdquo the surface being

overlookedAccordingly consider a matrix 119883

0(1199110 1199110) having a mul-

tidimensional transfer function of the subsurface (119911 gt 1199110)

Here each variable of1198830(1199110 1199110) characterized as the impulse

response of the wavefield occurred from a unit dipole sourceat 1199110and is further sensed by a unit pressure sensor at 119911

0 Also

the subscript ldquo0rdquo in 1198830symbolizes that earthrsquos surface has a

free reflection boundary that is a single round-trip (mean

Journal of Sensors 13

two-way time) has been estimated by the seismic signal fromthe subsurface (from 119911

0to 1199110) 1198830(1199110 1199110) has been utilized

as the multidimensional wavefield operator which definesthe wavefields at the reflection free acquisition surface 119911

0

119875

minus

0(1199110 1199110) as

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (25a)

or

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 120575119875

+(1199110 1199110)

+ 1198830(1199110 1199110) 119878

+

0(1199110 1199110)

(25b)

with combining

120575119875

+(1199110 1199110) = 119877

cap(1199110 1199110) 119875

minus

0(1199110 1199110) (25c)

In (25a) source matrix 119878

+

0(1199110) signifies the downgoing

wavefield of one physical source (array) at 1199110

However1198830119878

+ stands for the upgoing primary wavefields(one round-trip) and119883

0120575119875

+ stands for the upgoingmultiple-scattering wavefields (many round-trips)

Furthermore from (25a)ndash(25c) it can be simply derivedthat

1198830(1199110 1199110)

= [119868 minus 1198830(1199110 1199110) 119877

cap(1199110 1199110)]

minus1

1198830(1199110 1199110)

(26a)

representing the complexity of119883 relating to1198830 On compar-

ing (25a)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (26b)

with (25b)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) [120575119875

+(1199110 1199110) + 119878

+(1199110 1199110)] (26c)

Based on (26b) it can be concluded that the surface-related multiple-scattering phenomenon is incorporated intoa parameter 119883 However (26c) signifies that the surface-related multiple-scattering is incorporated into the downgo-ing wavefield 120575

119875

+

and the parameter 119883 determined as 1198830

Such variation between mathematical equations (26b) and(26c) assumes an imperative part in the inversion modelingfor seismic imaging [134]

Here Figure 16 represents the mixed shot record array offive sources at or near the surfaces Since during acquisitionzero time delays and large spacing between the sourcesare considered resulting incoherent shooting will becomesimultaneous shooting [136 139 140]The resultants imagingsignifies that a passive seismic recording can be measured asa naturally mixed shot record

312 Passive Seismic Imaging Method Based on DownwardRadiating Natural Sources Initially it is considered thatpseudo sources are set at or close to the surface (119911

0)

signifying that the background noise is considered as thosewavefields generated by the natural sources However in pas-sive seismic imaging response from natural sources has been

Tim

e (s)

30

25

20

15

10

05

00 1000 2000 3000 4000 5000

Lateral distance (m)

Figure 16 A mixed pseudo shot record generated by usingincoherent source array having five source elements at the surface[135 136]

considered as the seismic signal from the subsurface Thesesources might be set anyplace at the surface (119911 = 119911

0) and

in the subsurface (119911 gt 1199110) [137] Henceforth a noise model

has been createdwhichmay consider a continuing happeningseismic background noise as an indicator to determine theinformative data from these noises This concept is knownas seismic interferometry [141] Furthermore a relationshipby utilizing the wavefield diagram (see Figure 9) has beenestablished between the downgoing source wavefield at thesource level (119911

119899) and the up- and downgoing wavefields at

perception level 1199110(119911 = 119911

0) Such relation can be expressed

as

119875

+

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 119911119899)

119878

+

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110) [119882

minus1(1199110 119911119899)

119878

+

(119911119899)]

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110)

119878

+

(1199110 119911119899)

(27a)

where

119882

minus1(1199110 119911119899) = 119883

minus1

0(1199110 1199110)1198830(1199110 1199110) (27b)

Figure 17 describes the feed-forwarded model which isbased on modeling by downward radiating natural sourcesat and below the surface (119899 ge 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

313 Passive Seismic Imaging Method Based on UpwardRadiating Natural Sources In this phase like active seismicbackground noise similar type of natural sourcersquos responseis considered but the direction has been changed to the

14 Journal of Sensors

rarr(z0 zn)

W(zn z0)

Rcap(z0 z0)

rarr(zn)+X0(z0 zn)

120575rarr

(z0 zn)

n = 0 1 2 middot middot middot

Pminus

P+

S+

Figure 17 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

rarrPminus(z0 zn)

W(z0 zn)

Rcap(z0 z0)

rarrS (zn)

+ X0(zn z0)

120575rarrP (z0 zn)

n = 1 2

+

minus

Figure 18 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

contribution of ldquoupwardrdquo radiation Figure 18 depicts theresultants response which describes the correlation betweenthe upgoing source wavefields at the source level (119911

119899) and the

up- and downgoing wavefields at observation level 1199110 Such

result can be expressed as

119875

minus

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 119882(1199110 119911119899)

119878

minus

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899) +

119878

minus

(1199110 119911119899)

(28)

Figure 18 describes the feed-forwarded model which isbased on modeling by upward radiating natural sources atand below the surface (119899 gt 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

314 Statistical Description of the Modeling In the statisticalanalysis of the above designed model the above definedexpressions have been utilized on an exceptionally straight-forward medium Such medium has one horizontal reflectorand a free surface depicted in Figure 19 The stepwiseconstruction of thismedium signifies imaging in Figure 19(a)describing the conventional active seismic record where oneprimary and the surface multiples have been identified andindicated by a mathematical expression in (25b) In continu-ation Figure 19(b) describes the measurement of a responsefrom a downward radiating noise burst by implementing(27a) and (27b) while Figure 19(c) describes the upwardtransmitting patterns by estimating (28)

From these figures and equation implementation it isclearly defined that the occurrence of response and its mul-tiples takes place directly Moreover Figure 19(d) preciselydemonstrates the effect of such multiples that is the noisebursts being the summation of Figures 19(b) and 19(c)respectively

Figure 19 defines the straightforward medium whichhas one horizontal reflector and a stress-free surface HereFigure 19(a) describes the impulsive source at the surfacewhile Figure 19(b) shows at first layer the downward radiatingnoise source Similarly Figure 19(c) shows at first layerthe upward radiating noise source Finally Figure 19(d)establishes the omnidirectional noise source in the first layerof imagingOverall it has been signified that different sourcesdetermine the different resultant responses For exampleFigure 19 clearly proved this statement by demonstrating thatall sources defined here produce the different responses at ornear the subsurface of seismic imaging

32 Example Showing the Processing of Active and PassiveSeismic Imaging and Their Significance In this examplefor a mixed seismic data response inversion method fol-lowed for known and unknown sources is illustrated Herethree reflectors are utilized to measure the response forthe subsurface modeling (see Figure 20(a)) To begin withwithout considering surface-related multiples 119883

0 the mul-

tidimensional impulse response of the subsurface has beenproduced However Figures 20(b)ndash20(d) describe the three-column impulsive response of 119883

0 It results in naturally

occurring mixed recording at the subsurface Therefore inthe next modeling step surface-related multiples have beenimplemented that is from119883

0to119883

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

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[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

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[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

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[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

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[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

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[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

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[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

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[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

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Journal of Sensors 25

[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

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[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

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[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

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[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

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[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

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[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

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[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

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[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

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[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

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[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

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Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

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DistributedSensor Networks

International Journal of

4 Journal of Sensors

Disp

lace

men

t

Time

UnderdampedCritically damped

Overdamped

120587

2wr

Figure 3 Step response of the accelerometer as a second-ordermechanical system [42]

However critical damping is essential for achieving max-imum bandwidth Since the absence of damping permittedvery high levels of sensor resonant amplification it is fur-thermore recognizable that mass must be sufficiently huge toacquire the desired sensitivity with weak spring as shown inFigure 3 In thismanner themechanical resonance frequencyof suspended mass is given by

120596119899=

radic

119896

119898

(8)

Such expansion and the analysis imply that in an openloop circuiting a high sensitivity of the device yields a smallbandwidth while in closed loop circuiting the resonancepeak has been suppressed by the control circuit It is alsoclear that the mechanical resonance of the sensor does notlimit the bandwidth of the device but it is limited by thetransition frequency of the control circuit [44] Howeverdue to mechanical noise Brownian motion noise comes intoaccount which has been utilized to indicate the unwantedsignal as noise in the form of acceleration noise (see Table 1)Brownian noise has significant impact on both bulk andsurface micromachined capacitive accelerometers The mea-surement of the signal produced by the noise source andunsolicited signals is noise floor therefore it is clear that thereal signal cannot be detectable if the measured signal hasa value below this noise floor Nonetheless the variation inthe frequency causes the change in the noise floor valuesconsidering theBrowniannoise having noise floor between 10and 100 120583grtHz Such noise generates the random force withBrownian motion of air molecules which occurred becauseof the damping effect applied directly to the seismic massTherefore the Power Spectral Density (PSD) of the Browniannoise force is depicted as [45]

119865

2

119861(119891) = 4119896

119861119879119887

(9a)

where 119865119861is Brownian noise force 119896

119861is Boltzmann constant

119879 is absolute temperature and 119887 is damping coefficientHere it is clear that the damping coefficient (119887) is directly

proportional to Brownian noise such that the larger the valueof damping coefficient is the higher the noise will be or viceversa as depicted in (9a) Therefore reduction in the noisevalue requires anticipating the smaller value of the damping

W A

L

dd + Δ

L

Figure 4 Capacitance change due to variation in plate separation[33]

coefficient and hence results in a smaller damping ratio[44 45] Such ratio helps in modeling MEMS accelerometerrunning at underdamped condition having an oscillatingmess in the designed accelerometer Hence to measure theaccelerometerrsquos noise performance an acceleration-referrednoise floor has been estimated by using Newtonrsquos law as [45]

119886

2

119861(119891) =

119865

2

119861

119898

2=

radic4119896119861119879119887

98

2119898

2g2Hz (9b)

Since the thermal-mechanical Brownian noise floor iswithin 10sim100 120583grtHz it might influence the processing andthe device performance where the noise is considered asprocess noise Hence the minimum detectable acceleration isgiven by

119886min = radic

8120587119896119861119879119891119899119861

119876119898

(10a)

or

119886min =radic

4119896119861119879119887119861

119898

(10b)

However from (5) and (8) the mathematical computationidentifies that the bandwidth of an accelerometer sensingelement is directly proportional to its sensitivity (119878) duringthe design it must be considered Sensitivity of capacitiveaccelerometer is defined as the ratio of the difference ofvariation in the capacitance to the difference in variation inthe displacement which is depicted as

1198780=

119860119898120576

119896119889

2=

1198620119898

119896119889

(11)

where 120576 is the electric permittivity of air119860 is the overlap areaof electrodes and 119889 is the gap between the electrodes

The most well-known utilization of capacitive detectionfor sensors depends on signals which are coupled to changesin the electrode partition 119889 Let us consider a couple ofelectrodes with area119860 and separation 119889 depicted in Figure 4[33] A physical signal causes the partition to increment by asmall amount Δ The capacitance changes

from1205761205760

119889

to1205761205760

119889 + Δ

(12a)

Journal of Sensors 5

Here the correlation between the displacement andchange in capacitance is not linear but for a small change inthe division the capacitance can be estimated by utilizing aTaylor series expansion Generally any function 119865(119889) can beapproximated in the neighborhood of some nominal valued119889(0) as follows [33]

119865 (1198890+ Δ) = 119865 (119889

0) + Δ

120597119865 (1198890)

120597119889

+

Δ

2

2

120597

2119865 (1198890)

120597119889

2

+ sdot sdot sdot

(12b)

Based on the above expression this expansion can beimplemented as

119862 asymp

1205761205760119860

119889

(1 minus

Δ

119889

+

Δ

119889

2) (12c)

where Δ = 119889 minus 1198890

So for Δ ≪ 119889 the change in capacitance has linearrelationship with respect to the displacement The nonlin-earity of the function has been considered as a correctiontermof orderΔ21198892 such that nonconsideration of such errormakes the signal remain nearly linear [33]This creates a newrelationship such that the sum of the forces on the mass isequal to the acceleration of the mass (see Figure 2) such that

119896 (119883 minus 119909) + 119887

119889 (119883 minus 119909)

119889119905

= 119898

119889

2119909

119889119905

2

(12d)

where 119883 is position of the frame in Figure 2 119909 is position ofthe mass in Figure 2

Therefore the maximum detectable acceleration havingtotal gap between the electrodes 119889max is given by

119886max = 119896

119889max119898

(12e)

Additionally the above equations signify that spring con-stant ldquo119896rdquo affects directly the resonant frequency bandwidthsensitivity and furthermore the pull-in voltage Basically thespring constant is directly proportional to the beam charac-teristics such as the length (119871) the thickness (119905) the width(119882) and the elasticity of the material coefficient (YoungrsquosModulus (119864)) [44] Such variation in the spring constantin a beam occurs due the tensile and compressive stresseswhich is considered negligible during implementation andtherefore the following equation can be defined for furtherapplication

119896 =

119882119905

3

119871

3119864

(13)

where 119864 is Youngrsquos Modulus of the material utilized havingunit of gigapascals that is GPa

Since volume of proof mass is 119881 = 119871119898119879119898119882119898and is

homogeneously parallelepiped with rectangular area (119860) thevolume must be estimated from the volumic mass density 120588

as

120588 =

119898

119881

997904rArr

119881 =

119898

120588

(14)

Therefore the computation of the thickness (119879119898) of the

device is defined as

119881 = 119871119898119882119898119879119898

= 119860 sdot 119879119898

997904rArr

119879119898

=

119881

119860

(15)

Furthermore based on the above mathematical model-ing the geometry of the design accelerometer and its proofmass are defined Such modeling of the proof mass of theaccelerometer clearly depends on the various dimensions ofthe sensing elements depicted in Figure 5

The parameters utilized in Figure 5 such as widththickness and length of the proof mass and anchor dependupon the selection of the type of themodelwhich is illustratedin Table 16 (Appendix) Furthermore the sensitivity ofthe accelerometer is dependent on the size of proof massspring constant and resonance frequency graph in Figure 6illustrating the phenomena that proof mass and resonancefrequency are inversely proportional to each other withincrease in proofmass the resonance frequency decreases andvice versa

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies (Figure 7) The technological lag betweenthe application requirements and performance offered byavailable and emerging accelerometers motivates the devel-opment of dedicated sensing technology depicted in Table 2[16ndash20]

22 Accelerometers Performance Overview MEMS devicesfor seismic applications have previously been designed usingpiezoresistive [49] capacitive [10] and piezoelectric typedsensors [50] Electron tunneling is also a very promising sens-ing mechanism due to its high sensitivity to low vibrations[51]The performance of accelerometers can be characterizedbased on demonstrated operational specifications includingthe following

(i) Acceleration Range Recording unnecessary high ampli-tude signals adversely affects sensor sensitivity and con-sequently the resolution [52] It is necessary to know theacceleration range that is defined as the maximum acceler-ation input that can be measured by the accelerometer in g(acceleration due to gravity) (asymp10msminus2) As a result an idealaccelerometer should be able to capture maximum vibrationsof geophysical interest

(ii) Bandwidth It refers to the frequency range of input accel-eration that the sensor can perform with minimum distor-tion An ideal accelerometer requires minimum bandwidthto reduce undesired noise [52] and should have maximumbandwidth that is sufficient to accommodate all signals ofinterest

(iii) Noise FloorThe noise collectively generated at the sensoroutput when no acceleration is present is referred to assensor noise floor It is a composite of three noise sourcesthe thermomechanical noise (ie Brownian noise) [49 53]

6 Journal of Sensors

Table 2 Comparison of existing MEMS accelerometers [16ndash20]

Sensor Supplier Bandwidth (Hz) Full scale (mg) Noise density (ngradicHz)Trillium [20] Nanometrics 003ndash50 mdash mdashGAC [17] WesternGeco 3ndash200 108 15DSU1 [18] Sercel 0ndash800 500 40 (gt10Hz)HP sensor [19] HP 1ndash200 80 10

Wm = 120583m

Lm = 120583m

Z

X

Y

tm = 120583m

L2 = 120583m

W = 120583m

t = 120583m

Figure 5 Sensing element dimensions

Reso

nanc

e fre

quen

cy (H

z)

60 70 80 90 100 110

Proof mass (120583g)

170

180

190

200

210

220

230

240

Figure 6 Resonance frequency versus proof mass

the thermoelectrical noise (ie Johnson noise) and the 1119891

noise (Hoogersquos noise) [54] The first one is due to the randommotion induced by thermal energy of gaseous moleculessurrounding the proof mass [10] The thermoelectrical noiseis attributed to the random electron motion in the wiresinduced by ambient thermal energy Hoogersquos noise is empiri-cal noise and is function of the frequency For simplicity thetotal noise floor 119886n can be expressed in terms of mechanicalnoise (119886nm) and electrical noise (119886ne) as displayed in

119886119899= radic119886nm

2+ 119886ne2

(16)

The noise floor is desirable to be as minimal as pos-sible but an acceptable level can be determined by therequired resolution To evaluate the need for dedicated sen-sors for hydrocarbon microtremor analysis studies availableaccelerometers have been reviewed Eventually matchinganalysis between sensing requirements and performancemetrics is performed to scope down design possibilitiesand guide promising directions Based on the employedsensing principle the discussion on performance metrics is

Telemetry cable

2 horizontal MEMSLine board

IC board

Servo-loop ASIC

V board

Vertical MEMSEeprom

Figure 7 Three-axis (3-component) seismic sensor unit [16]example of accelerometer used in seismic application

categorized into piezoresistive capacitive piezoelectric andtunneling accelerometers

221 Piezoresistive Piezoresistive accelerometers exploit thepiezoresistive effects of materials typically polysilicon tomeasure the acceleration [50 51]The piezoresistive elementsare embodied in structure in such a way to be subjectedto torsion when acceleration is applied [50] The structurecan typically be a suspended beam with one end attachedto a proof mass [54] The proof mass movement imposesstress changes on the piezoresistive element thus changingits resistance Figure 8 shows a typical example of this typeof accelerometer In this example the proof mass movement

Journal of Sensors 7

A B A B

SubstrateBimorph cantilevers

Proof mass

Figure 8 Piezoresistive accelerometer showing the embodiedpiezoresistors (A B) within the cantilever [43]

implies stress changes along the embedded piezoresistiveelements (polyresistors) in the bimorph cantilever AWheat-stone bridge-like circuitry is used to measure resistancechange and deduce acceleration

For more than three decades piezoresistive accelerom-eters (eg [49 52 53 55ndash64]) have shown progressiveimprovements making them a viable option for variousapplications includingmicrogravity and low frequency appli-cations [59 63]

The demonstrated performance of these devices is shownas in Figure 8

(i) Acceleration Range Piezoresistive accelerometers havebeen designed to work in ranges as small as 1 g [55] or aslarge as 250 g [61] In average they work within 10ndash50 g [4952 53 56ndash60 62ndash64] This operation range is two orders ofmagnitude larger than desired operation range (4 ngndash80mg)(ii) Bandwidth Piezoresistive accelerometer designs [53 5558ndash63] statistically tend to have a median bandwidth of1 KHzThe uppermeasurement limit typically varies between100Hz and 2KHz whereas the lower limit is conventionallynonzero (5ndash100Hz) [46 55 59 63ndash65] except for the case ofemploying nanowires [66] that are able to respond to 0Hzacceleration (static acceleration)(iii) Noise Floor The noise floor is generally in range of 100ndash500120583gradicHz [55 56 59 63 64]

Table 3 summarizes the performance characteristics ofpiezoresistive accelerometers They are advantageously sim-ple in structure fabrication and their read-out circuitry [54]On the other hand the demonstrated performance does showcapability in neither operating in sub-g domain nor achievingbandwidth lt 50Hz or a noise floor below 5 ngradicHz Addi-tionally piezoresistive accelerometers can be seen to haveintrinsic temperature sensitivity andmeasurement drifts [62]These limitations could reduce their suitability for intendedhydrocarbonmicrotremormeasurements of current concern

222 Capacitive Capacitive accelerometers are dominantaccelerometers in market The high sensitivity good noiseperformance and low temperature sensitivity are amongtheir features [54] In principle capacitive types exploitthe change of capacitance between plates on free moving

Table 3 Piezoresistive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small sim1 g Lower limit 5ndash100 Low 100 120583

Medium 10ndash50 g BW sim1 kLarge sim250 g Upper limit 100ndash2 k High 500 120583

ElectrodeSi

Insulated layer

Si

Si

d0

d0

CA

CB

X

Proof mass

Figure 9 Capacitive sensing principle [46]

and fixed microstructures when acceleration is applied [50]Figure 9 shows a simple cantilever structure of capacitivetype accelerometer The structure consists of proof masssuspended via cantilever while the movement is sensed viaelectrodes

For quantitative analysis the performance of capacitiveaccelerometers in [19 65ndash112] is presented as follows

(i) Acceleration Range Depending on order of magnitudecapacitive accelerometers can be observed to operate in fourdifferent ranges (i) sub-g (120583g-mg) range [18 96 103] (ii) 1ndash10 g range [65ndash68 76 77 80 84ndash89 92 95ndash97 100ndash102 105](iii) 10ndash100 g range [69 72ndash74 93 99 104ndash106] and (iv) above1000 g [90 91]

(ii) Bandwidth The bandwidth of capacitive accelerometerstypically starts at DC (0Hz) [65ndash68 86 104 105] in somecases it can begin at nonzero frequencies [19 79 92]Commonly their bandwidth falls in range of 100ndash1000Hzbut it can typically vary in less than 100Hz [69] and above1000Hz [85 110]

(iii) Noise Floor The noise performance of capacitiveaccelerometers varies from 4 ngradicHz [92] up to 400mgradicHz[102] More than 60 of capacitive accelerometers have noisefloor within 120583gradicHz (ie between 01 and 100 120583gradicHz)

Capacitive accelerometers offer wide performance capa-bilities as shown in Table 4 The wide capability variationenables their successful utilization in different industrial

8 Journal of Sensors

Vz

Vx

T

T T

T

CC C C

Figure 10 Accelerometer structures using piezoelectric sensing [47]

Table 4 Capacitive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small lt1mg Small lt100 Small 4 nndash1 120583Medium 1ndash10 g Medium 100ndash1 k Medium 1 120583ndash1mLarge 10ndash100 g Large gt1 k Large gt1mVery large gt1000

domains including biomedical domain navigation spacemicrogravity military and also seismology [19 65ndash112]Remarkably the authors in [92] demonstrated noise per-formance approaching the required noise floor of HyMASapplication However the device resolution is lower than thedesired value because of the wide bandwidthTherefore a gapon achieving the required noise density and bandwidth hasstill not been met

The simple structure low drift and low temperature sen-sitivity of capacitive accelerometers along with demonstratedperformance make them suitable design option for seismicapplications [46 112]

223 Piezoelectric Piezoelectric accelerometers employmaterials with piezoelectric effects to indirectly measureacceleration via amount of deposited electric charges whenstress is induced [50] They are generally featured by lowpower consumption and temperature stability and have beenused in several applications including medical and machinevibration monitoring [47 62 113ndash117]

A typical accelerometer utilizing piezoelectric principle isillustrated in Figure 10 in which the movement of the proofmass imposes deformation on the piezoelectric elements onthe supporting bimorph beam The charge deposition alongthe sensing element induces electrical potential (119881

119909and 119881

119911)

whose magnitude indicates the acceleration appliedThe performance of accelerometers is discussed as fol-

lows

(i) Acceleration Range Piezoelectric accelerometers demon-strate a measurement range around 20ndash25 g [116] but theydo not suit sub-g operation range Additionally the inheritedhysteresis effect reduces the measurement precision that isessentially required for geophysical seismic measurement(ii) Bandwidth Piezoelectric accelerometers are normallyused in dynamic operationmode which can result in leakage

Table 5 Piezoelectric accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

and creep issues [54] The dynamic range is typically within01 kHzndash10 kHz [62 113ndash116] but can be as high as 37 kHzndash35 kHz [114] or as low as 1Hzndash60Hz [47](iii) Noise Floor It falls within the range of 10 ng to 700 ng indesigns [47 116 117] whereas the early designs suffer fromlarge noise floor reaching up to 01 g [113]

Table 5 summarizes the performance characteristics ofpiezoelectric accelerometers From presented literature theyshow substantial performance improvement in the accel-eration range bandwidth and noise level over the lastdecades This could make them viable choice of design forpassive seismic However the inherited creep and tendencyfor dynamic measurements can reduce their suitability forpassive seismic geophysical applications

224 Electron Tunneling Tunneling accelerometers exploitchanges of current tunneling through insulating mediumwith change of separating displacement [48 118ndash121] Fig-ure 11 shows an accelerometer schematic using the electrontunneling principle It is seen that the tunneling tip is justbeneath a suspended proof mass A deflection electrode andproof mass electrodes provide electrostatic force required tocontrol the tunneling current

Electron tunneling is very promising in seismic appli-cation field because of performance high sensitivity smallsize and light weight compared to piezoresistive or capacitivetypes The demonstrated measurement capabilities are statedas follows(i) Acceleration Range During the last two decades 30 grange was typically reported [119 120] Later 1mg rangewas maximally reported [48 121] which proved its sensorcapability to work in seismic operation(ii) Bandwidth Frequently accelerometers are designed towork minimally at 1 kHz bandwidth [47 113ndash122] Thisrange can reach up to 6 kHz [123ndash125] Notably tunnelingaccelerometers have a limit for the minimum detectable

Journal of Sensors 9

Table 6 Tunneling accelerometers performance range

Acceleration range (g) Bandwidth(Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

Vacuum

Proof mass

HingeProof mass electrode

Tunneling tip Deflection electrode

Figure 11 Cross sectional view of tunneling accelerometer withcantilever structure [48]

frequencyThis limit is typically in range of 5ndash200Hz [48 119121](iii) Noise Floor In early tunneling devices the noise floorvaried over a range from 1 120583gradicHz to 4mgradicHz [119 120122] As technology advances a noise floor at nanometerrange (15ndash250 ngradicHz) has been achieved [48 121] Table 6summarizes the performance characteristics of tunnelingaccelerometers in literature Tunneling accelerometers showseismic grade performance with some exception on the widebandwidth of 1 kHz Therefore further filtration process isrequired for narrow bandwidth signals

225 Resistive Accelerometers Resistive accelerometers rec-ognize the change of resistance of a metal strain gauge clungto a cantilever beam Accelerating prompts twisting of thecantilever beam and hence causes variation in the resistanceof the strain gauge In case of a metal foil the geometric effectis identified significantly dominating the piezoelectric effect[50] The model of a Wheatstone bridge circuit configuredfour strain gauges which provide a voltage signal and workfor DC estimation

226 Optical Accelerometers An optical accelerometer dis-tinguishes the change of optical characteristics in an opticalfiberTheFiber BraggGrinding (FBG) is one of themost stan-dard and popular techniques for fiber optical estimation [126127] In this technique Bragg gratings are the interferencefilter composed of optical fibers The characteristic of FBGaccelerometers defines that the appraisals reflect just a narrowspectral component of actuated light Acceleration prompts adistortion of an optical fiber connected to a suspended beamcausing a change in the reflection characteristic of the Bragggratings This change can be distinguished by contrasting thespectral component of the reflected beam with the impelledlight Hence FBG accelerometer is used to perform opticalsignal analysis with DC estimations

Table 7 Sensors performance summary

Type Bandwidth(Hz)

Acceleration(g)

Noise density(gradicHz)

Capacitive 0ndash30 22120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100 120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

227 Thermal Accelerometers Thermal accelerometer hasbeen driven based on mass displacement and does notfound a popularity among others in terms of manufacturerselling [127] Therefore the suited alternative solution of thisissue is thermal accelerometer without mass displacement[127] It consists of a heater and thermocouples situatedaround the radiator in a hermetic chamber On applyingacceleration to the accelerometer hot air in the chambermoves that leads to generating an asymmetric temperatureprofile Such asymmetric profile can be identified by thethermocouples around the radiator This process is calledtransduction principle which produces a voltage signal usingthese accelerometers and work for DC estimation [128]

23 Analysis and Design Challenges For comparative anal-ysis previously mentioned works have been summarized inTable 7 [6 7 34 43 46 62ndash64] The first column shows thesensing type of accelerometers The smallest operating band-width the upper limits of acceleration range and measurednoise floor levels are listed in columns 2ndash4 respectively Thedata summarized inTable 7 indicates the superiority of capac-itive sensors to meet passive seismic sensing requirementsAccording to Section 22 signals required in passive seismicsurvey havemaximumacceleration oflt80mg andbandwidthof 1ndash30Hz with lt1 ngradicHz noise spectral density

The key in designing high resolution capacitive acceler-ometer is to reduce the devicersquos noise floor and increase itssensitivity as demonstrated in [19 88 92 93 104 122 123]The total noise floor comes from mechanical and electricalelements of the sensor

(i) Design Overview The Brownian noise is principallyproportional to the square root of damping factor (119887) andinversely proportional to the proof mass (119898) as in (17) where119896119861and 119879 are Boltzmannrsquos constant (138 times 10minus23 JK) and the

temperature in Kelvin

119886nm =

radic4119896119861119879119887

98119898

(17)

Therefore ultralow noise accelerometers have large proofmass and low gas damping in the mass-spring accelerometersystem [19 92] The mechanical noise can be defined as afunction of the temperature damping coefficient and massWhile the temperature can be set to 20∘C or 29315∘K thedamping coefficient andmass are dependent on the geometryof the structure

10 Journal of Sensors

Sensing fingers

Springs

Driving fingers

(a)

A

A998400

Wb Wa

Lb

La

LeffLf

X0

Wf

(b)

Figure 12 Structure of a lateral capacitive accelerometer (a) isometric device view (b) spring parameters (119882119887119882119886 119871119886 119871119887) and fingers

parameters (1198830119882119891 119871119891 119871eff ) [124]

In the electrical domain the noise can be minimizedby reducing the operating bandwidth Additionally a closed-loop feedback electronic circuit is required to compensate thenonlinear response of the mechanical system and to shortenthe bandwidth of the device to 30Hz To minimize the noiseeffect from amplifier the rate of capacitance change withacceleration needs to be maximized [19] Maximizing thesensitivity requires minimizing sensing gap and lowering thenatural resonant frequency [19 92 129]

As previously discussed the minimum detectable accel-eration should be = 802

24= 47 ng This implies that

the maximum mechanical noise 119886119898

should be less than086 gradicHz according to

119886119898

=

119886minradicBW

=

47 ngradic30

= 086 gradicHz (18)

In order to size the design challenges of ultralow noisefloor a case study on accelerometer design with conventionalcomb structure is considered The structure as shown inFigure 12 comprises a fixed rectangular framewith fingers anda moving proof mass fixed on the frame by spring-like shapeat both ends and surrounded by fingers at its both sides

Accelerometers noise performance is generally deter-mined by the damping coefficient and proof mass size assuggested by (5) The dominant damping mechanism in thisstructure is due to the squeeze-film effect [125]Therefore thedamping coefficient 119887 can be written in

119887 = 72119873120583119905 (

119897eff1199090

)

3

(19)

whereby 119873 is the number of comb fingers 119905 is the proofmass thickness 120583 is the viscosity of the air under atmosphericpressure 20∘C = 154 times 10minus6 kgms and 119897eff is the engagedlength of the comb fingers

Moreover the mass 119898 can be expressed in (20) where 119898

defines the mass of the proof mass 120588 is the silicon density =2330 kgm3 119897

119891is the length of comb fingers 119882

119891is the width

of comb fingers and 119860 is the area of the proof mass

119898 = 119905120588 (119860 + 119873119897119891119882119891) (20)

As a result the mechanical noise 119886nm can be expressed bysubstituting (19) and (20) in (17) to obtain

119886nm =

radic4119896119861119879 [72119873120583119905 (119897eff1199090)

3]

98 [119905120588 (119860 + 119873119897119891119882119891)]

(21)

As depicted in Figure 12(a) the proof mass parameters119860 and 119905 typically have large values compared to fingersdimensions 119871eff 119871119891119882119891 and 119883

0[124] As a result the proof

mass is effectively increased by enlarging parameters119860 and 119905The realization of sub-ngradicHz of noise spectral density

through mass maximization has a positive impact on devicesensitivityThis can be explained by the proportional relation-ship between sensitivity and mass as displayed in

119878 =

119881119904

119886in=

4119862119904

2119862119904+ 119862119901

sdot

119881m1199090

sdot

119898

119896

(22)

whereby 119878 is the sensitivity (Vg) 119862119904is the sensing capaci-

tance 119862119901is the parasitic capacitance119881m is maximum output

voltage (V) 119886in is maximum input acceleration (g) and 119896 isthe spring constant (Nm)

The maximization of sensitivity is an important designgoal This is achievable by maximizing the proof mass andminimizing the spring constant as suggested by (22) How-ever the resonant frequency has to be considered Equations(23) and (24) describe the structural dependencies of thespring constant 119896 and the device resonant frequency 119891respectively as follows

119896 = 2

1

(119899 minus 1)

3sdot 119864 (

119882119887

2119871119887

)

3

119905 (23)

119891 =

1

2120587

sdotradic

119896

119898

(24)

where 119899 is the number of mechanical spring turns 119882119887is

the width of single turn spring 119871119887is the length of single

turn spring and 119864 is Youngrsquos Modulus of silicon = 154 times

10minus6 kgms

231 Summarized Analysis of the Type of Accelerometers Forinitial analysis (18)ndash(23) have been solved yielding to the

Journal of Sensors 11

Table 8 Initial design parameters and values

Parameter Value Parameter Value119897eff 80 120583m 119899 8119897119891

85 120583m 1199090

83 120583m119882119891

48 120583m 119905 3318 120583m119873 200 119897

1198872mm

119860 5mm times 5mm 119882119887

75 120583m119898 2120583g 119886nm 085 ngrtHz119891 46Hz 119878 026

values as listed in Table 8 The table shows the parametersand the corresponding values for the design in rows 2ndash6The resulting device performance (noise resonant frequencyand sensitivity) is shown in the last two rows The tableshows that a 5mm times 5mm proof mass area was requiredEven though the sensitivity (026Vg) is lower than state-of-the-art value this device is considered large structure forconventional CMOS technology To improve the sensitivityfurther enlargement for the proof mass is required Thisshows the major challenge of the design

Therefore achieving the noise spectral density of less than1 ngradicHz on a conventional capacitive structure is challeng-ing As a result a novel structure and design optimization isexpected to meet the stringent resolution level requirements

232 Conclusion on the Analysis The excessive demandsfor hydrocarbon have pushed the exploration technologyto the era of passive seismic monitoring The technique iseconomically promising and environmentally friendly butfacing several challenges among which is the high resolutionacquisition using state-of-the-art sensorsaccelerometers

In this paper the technological gap between themeasure-ment resolution of the state-of-the-art sensors and emergingdevices is identified for passive seismic monitoring It showsdesign possibilities using capacitive sensing techniques andmotivates further work in developing optimized sensor solu-tions

Finally a solution has been provided with specificationto design such an accelerometer To enhance the resolutionand sensitivity a dimension in the order of millimeters largerthan conventional MEMS dimensions is required Moreovertechnological issues including reducing parasitic capacitanceby increasing dielectric thickness and reducing air pressurefor less damping impact beyond 1ndash10 Torr are among theconstraints hindering prospective designs

In synopsis piezoelectric accelerometers demonstrate themost astounding estimation range shock limits and oper-ating temperature capacitive accelerometers the least powerutilization and volume and piezoresistive accelerometers thevastest frequency response

3 Sensors in Seismology

Seismic study determines that the effective exploration tech-nique for imaging the geology is active seismic imagingPreviously explosives or vibroseis trucks are utilized for

Nor

mal

ized

ampl

itude

minus1

minus05

0

05

1

0 02 04 06 08 1 12 14

Time (s)

P-wave S-wave

Figure 13 A ldquogoodrdquo occurrence of P- and S-wave arrivals in timedomain [44]

Nor

mal

ized

ampl

itude

minus1minus05

0051

0 02 04 06 08 1 12 14

Time (s)

Figure 14 A random ldquonoiserdquo event at time domain [33]

generating seismic energy sensed by the network of seismicsensors which may provide the information that determinesthe prospective oil and gas traps In view of received sensordata a 3D stratigraphy map is developed This 3D map mayhelp in determining the position of hydrocarbon depositionsMoreover the increasing demand and supply of oil and gasneed industries to explore more hydrocarbons from previous50 to 80 by identifying accurate information about hydro-carbon deposition [44 45] Conventional techniques cannotprovide the correct information about the petrophysicalproperties of reservoir because the rock pores having hydro-carbon affect the physical properties of the rockwhich in turncause poor energy sensed through seismic sensors One ofthe key solutions for accurate information is passive seismicimaging technique This technique uses naturally happeningseismic signals like earth quake microtremors and oceanwaves for subsurface imaging and structuring In comparisonof conventional technique having sensing frequency in therange of 10ndash300Hz passive seismic technique monitors thelower frequency waves (below 10Hz) whichmay travel a longdistance through the earthrsquos crust without attenuation

An example of ldquoGoodrdquo event having occurrences of P-wave and S-wave at time domain is showed in Figure 13 Onthe basis of the discrete and impulsive P-wave and S-wavearrivals the event is termed ldquoGoodrdquo event [33]

Also it is shown clearly that frequency of S-wavedecreases as the frequency of P-wave increases A randomldquonoiserdquo event occurring at time domain with indeterministicproperties of ldquoGoodrdquo events is shown in Figure 14 [33]

In the area of reservoir monitoring passive seismichave applications for recording microseismic signal at nat-ural frequency for the exploration and exploitation of thehydrocarbons (ie oil and gas) [131] The study of passiveseismic at variant frequency identifies that information aboutprediction of hydrocarbon reservoir is found at low frequencyof less than 10Hz [1ndash5 132] as depicted in Table 9

12 Journal of Sensors

Table 9 Technical description of seismic data acquisition technique at low frequency

Frequency range focused Technique used Advantage Disadvantage

Modeling frequency 50ndash60Hz[25]

Spike deconvolution for lowfrequency modeling

(i) Low-cut filter is used toattenuate low frequencies

(ii) Defining technique producesbetter P-wave and S-wave seismic

section

(i) Need for recovery of broadsignal bandwidth

(ii) Poor wavelet extraction andits structure

Modeling frequency 1 KHzAcquired seismic frequency12HzReflectivity at 40Hz [26]

(i) Ultrasonic experiment(ii) Seismic data analysis

(i) Signal is reflected from a thinwater- (S

119908) or oil-saturated (S

ℎ)

layer(ii) Frequency dependent

amplitude and phase reflectionattributes have been utilized forobserving and identifying thin

liquid saturated layers

(i) Strong attenuation in the layeraffects summation of multiples

(ii) Layers with higherattenuation create travel timedelays which increase asfrequency approaches zero

Missing frequency 5ndash10Hz [27]

(i) 3D acoustic inversion(ii) Variable depth streamerseismic data acquisition(iii) 3D elastic inversioncomparison technique

(i) Variable depth streamer fordata acquisition is better for

inversion and provides missinglow frequencies directly

(ii) Left side lobe of the wavelet isproposed to reduceless

interference in the seismic signalresults in less ambiguity in

inversion

(i) There is variation in resultinginversion due to high variation in

acquisition frequency(ii) Broadband inversion may

cause obtained results outside thetarget zone

Reflection lt15HzAmplitude 40Hz [28]

(i) AVO attribute analysis(ii) VSP analysis

(i) Imaging at low frequenciesresults in robust amplitudes for

individual frequencycomponents of propagating

wavelet(ii) Frequency based seismic

imaging permits characterizingthe subsurface fluid reservoirs

(i) Quantitative analysis of AI (asfrequency) requires NMO

stretching(ii) Conventional seismic

processing software does notwork as target-oriented

processing

Based on Table 9 it is clear that the type of geophonesused in active seismic acquisition has greater size and islinearly proportional to the velocity over the resonancefrequency (about 10Hz) [25ndash28] Therefore a new design ofthe accelerometer is defined which offers a minimal signalroll-off small size and weight solution to the larger arrayslayout Also from the table it is identified that passive seismichas high potential benefits but requires special ultra noiselow frequency and short bandwidth sensing capabilitiesSince the existing device and the sensor are unable torecord at this frequency various types of sensor are studied(discussed in Section 4) Based on sensor analysis it isfound that MEMS accelerometers (capacitive) based deviceis the best replacement of existing seismological equipmentCapacitive accelerometers performed well in low bandwidthlow frequency and minimum noise Hence passive seismicexploration is an ongoing and promising research topic withthe benefit of being environmentally friendly and of low cost

31 Comparison of Technical Structure of Active andPassive Imaging

311 Active Seismic ImagingMethod In the acquisition of theactive seismic data a feedback model has been implementedwhich is based on the principal that both sources and

Pminus(z0 z0) Rcap(z0 z0)

X0(z0 z0)

120575P+(z0 z0)

S+(z0)+

X(z0 z0)

Figure 15 A feedforward model representing the upgoing anddowngoing wavefields in conventional seismic acquisition [130]

detectors are normally placed at or near the earthrsquos surfacedepicted in Figure 15 [133] It demonstrates schematically up-and downgoingwavefields happening at the reflecting surface(1199110) while the wavefields are going ldquoalongrdquo the surface being

overlookedAccordingly consider a matrix 119883

0(1199110 1199110) having a mul-

tidimensional transfer function of the subsurface (119911 gt 1199110)

Here each variable of1198830(1199110 1199110) characterized as the impulse

response of the wavefield occurred from a unit dipole sourceat 1199110and is further sensed by a unit pressure sensor at 119911

0 Also

the subscript ldquo0rdquo in 1198830symbolizes that earthrsquos surface has a

free reflection boundary that is a single round-trip (mean

Journal of Sensors 13

two-way time) has been estimated by the seismic signal fromthe subsurface (from 119911

0to 1199110) 1198830(1199110 1199110) has been utilized

as the multidimensional wavefield operator which definesthe wavefields at the reflection free acquisition surface 119911

0

119875

minus

0(1199110 1199110) as

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (25a)

or

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 120575119875

+(1199110 1199110)

+ 1198830(1199110 1199110) 119878

+

0(1199110 1199110)

(25b)

with combining

120575119875

+(1199110 1199110) = 119877

cap(1199110 1199110) 119875

minus

0(1199110 1199110) (25c)

In (25a) source matrix 119878

+

0(1199110) signifies the downgoing

wavefield of one physical source (array) at 1199110

However1198830119878

+ stands for the upgoing primary wavefields(one round-trip) and119883

0120575119875

+ stands for the upgoingmultiple-scattering wavefields (many round-trips)

Furthermore from (25a)ndash(25c) it can be simply derivedthat

1198830(1199110 1199110)

= [119868 minus 1198830(1199110 1199110) 119877

cap(1199110 1199110)]

minus1

1198830(1199110 1199110)

(26a)

representing the complexity of119883 relating to1198830 On compar-

ing (25a)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (26b)

with (25b)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) [120575119875

+(1199110 1199110) + 119878

+(1199110 1199110)] (26c)

Based on (26b) it can be concluded that the surface-related multiple-scattering phenomenon is incorporated intoa parameter 119883 However (26c) signifies that the surface-related multiple-scattering is incorporated into the downgo-ing wavefield 120575

119875

+

and the parameter 119883 determined as 1198830

Such variation between mathematical equations (26b) and(26c) assumes an imperative part in the inversion modelingfor seismic imaging [134]

Here Figure 16 represents the mixed shot record array offive sources at or near the surfaces Since during acquisitionzero time delays and large spacing between the sourcesare considered resulting incoherent shooting will becomesimultaneous shooting [136 139 140]The resultants imagingsignifies that a passive seismic recording can be measured asa naturally mixed shot record

312 Passive Seismic Imaging Method Based on DownwardRadiating Natural Sources Initially it is considered thatpseudo sources are set at or close to the surface (119911

0)

signifying that the background noise is considered as thosewavefields generated by the natural sources However in pas-sive seismic imaging response from natural sources has been

Tim

e (s)

30

25

20

15

10

05

00 1000 2000 3000 4000 5000

Lateral distance (m)

Figure 16 A mixed pseudo shot record generated by usingincoherent source array having five source elements at the surface[135 136]

considered as the seismic signal from the subsurface Thesesources might be set anyplace at the surface (119911 = 119911

0) and

in the subsurface (119911 gt 1199110) [137] Henceforth a noise model

has been createdwhichmay consider a continuing happeningseismic background noise as an indicator to determine theinformative data from these noises This concept is knownas seismic interferometry [141] Furthermore a relationshipby utilizing the wavefield diagram (see Figure 9) has beenestablished between the downgoing source wavefield at thesource level (119911

119899) and the up- and downgoing wavefields at

perception level 1199110(119911 = 119911

0) Such relation can be expressed

as

119875

+

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 119911119899)

119878

+

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110) [119882

minus1(1199110 119911119899)

119878

+

(119911119899)]

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110)

119878

+

(1199110 119911119899)

(27a)

where

119882

minus1(1199110 119911119899) = 119883

minus1

0(1199110 1199110)1198830(1199110 1199110) (27b)

Figure 17 describes the feed-forwarded model which isbased on modeling by downward radiating natural sourcesat and below the surface (119899 ge 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

313 Passive Seismic Imaging Method Based on UpwardRadiating Natural Sources In this phase like active seismicbackground noise similar type of natural sourcersquos responseis considered but the direction has been changed to the

14 Journal of Sensors

rarr(z0 zn)

W(zn z0)

Rcap(z0 z0)

rarr(zn)+X0(z0 zn)

120575rarr

(z0 zn)

n = 0 1 2 middot middot middot

Pminus

P+

S+

Figure 17 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

rarrPminus(z0 zn)

W(z0 zn)

Rcap(z0 z0)

rarrS (zn)

+ X0(zn z0)

120575rarrP (z0 zn)

n = 1 2

+

minus

Figure 18 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

contribution of ldquoupwardrdquo radiation Figure 18 depicts theresultants response which describes the correlation betweenthe upgoing source wavefields at the source level (119911

119899) and the

up- and downgoing wavefields at observation level 1199110 Such

result can be expressed as

119875

minus

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 119882(1199110 119911119899)

119878

minus

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899) +

119878

minus

(1199110 119911119899)

(28)

Figure 18 describes the feed-forwarded model which isbased on modeling by upward radiating natural sources atand below the surface (119899 gt 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

314 Statistical Description of the Modeling In the statisticalanalysis of the above designed model the above definedexpressions have been utilized on an exceptionally straight-forward medium Such medium has one horizontal reflectorand a free surface depicted in Figure 19 The stepwiseconstruction of thismedium signifies imaging in Figure 19(a)describing the conventional active seismic record where oneprimary and the surface multiples have been identified andindicated by a mathematical expression in (25b) In continu-ation Figure 19(b) describes the measurement of a responsefrom a downward radiating noise burst by implementing(27a) and (27b) while Figure 19(c) describes the upwardtransmitting patterns by estimating (28)

From these figures and equation implementation it isclearly defined that the occurrence of response and its mul-tiples takes place directly Moreover Figure 19(d) preciselydemonstrates the effect of such multiples that is the noisebursts being the summation of Figures 19(b) and 19(c)respectively

Figure 19 defines the straightforward medium whichhas one horizontal reflector and a stress-free surface HereFigure 19(a) describes the impulsive source at the surfacewhile Figure 19(b) shows at first layer the downward radiatingnoise source Similarly Figure 19(c) shows at first layerthe upward radiating noise source Finally Figure 19(d)establishes the omnidirectional noise source in the first layerof imagingOverall it has been signified that different sourcesdetermine the different resultant responses For exampleFigure 19 clearly proved this statement by demonstrating thatall sources defined here produce the different responses at ornear the subsurface of seismic imaging

32 Example Showing the Processing of Active and PassiveSeismic Imaging and Their Significance In this examplefor a mixed seismic data response inversion method fol-lowed for known and unknown sources is illustrated Herethree reflectors are utilized to measure the response forthe subsurface modeling (see Figure 20(a)) To begin withwithout considering surface-related multiples 119883

0 the mul-

tidimensional impulse response of the subsurface has beenproduced However Figures 20(b)ndash20(d) describe the three-column impulsive response of 119883

0 It results in naturally

occurring mixed recording at the subsurface Therefore inthe next modeling step surface-related multiples have beenimplemented that is from119883

0to119883

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

[1] A E de Vasconcelos Lopes and L C Nunes ldquoPitfalls of tremor-like signals for hydrocarbon exploration in producing oil fieldsin Potiguar basin northeast Brazilrdquo The Leading Edge vol 29no 7 pp 826ndash830 2010

[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

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[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

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Journal of Sensors 5

Here the correlation between the displacement andchange in capacitance is not linear but for a small change inthe division the capacitance can be estimated by utilizing aTaylor series expansion Generally any function 119865(119889) can beapproximated in the neighborhood of some nominal valued119889(0) as follows [33]

119865 (1198890+ Δ) = 119865 (119889

0) + Δ

120597119865 (1198890)

120597119889

+

Δ

2

2

120597

2119865 (1198890)

120597119889

2

+ sdot sdot sdot

(12b)

Based on the above expression this expansion can beimplemented as

119862 asymp

1205761205760119860

119889

(1 minus

Δ

119889

+

Δ

119889

2) (12c)

where Δ = 119889 minus 1198890

So for Δ ≪ 119889 the change in capacitance has linearrelationship with respect to the displacement The nonlin-earity of the function has been considered as a correctiontermof orderΔ21198892 such that nonconsideration of such errormakes the signal remain nearly linear [33]This creates a newrelationship such that the sum of the forces on the mass isequal to the acceleration of the mass (see Figure 2) such that

119896 (119883 minus 119909) + 119887

119889 (119883 minus 119909)

119889119905

= 119898

119889

2119909

119889119905

2

(12d)

where 119883 is position of the frame in Figure 2 119909 is position ofthe mass in Figure 2

Therefore the maximum detectable acceleration havingtotal gap between the electrodes 119889max is given by

119886max = 119896

119889max119898

(12e)

Additionally the above equations signify that spring con-stant ldquo119896rdquo affects directly the resonant frequency bandwidthsensitivity and furthermore the pull-in voltage Basically thespring constant is directly proportional to the beam charac-teristics such as the length (119871) the thickness (119905) the width(119882) and the elasticity of the material coefficient (YoungrsquosModulus (119864)) [44] Such variation in the spring constantin a beam occurs due the tensile and compressive stresseswhich is considered negligible during implementation andtherefore the following equation can be defined for furtherapplication

119896 =

119882119905

3

119871

3119864

(13)

where 119864 is Youngrsquos Modulus of the material utilized havingunit of gigapascals that is GPa

Since volume of proof mass is 119881 = 119871119898119879119898119882119898and is

homogeneously parallelepiped with rectangular area (119860) thevolume must be estimated from the volumic mass density 120588

as

120588 =

119898

119881

997904rArr

119881 =

119898

120588

(14)

Therefore the computation of the thickness (119879119898) of the

device is defined as

119881 = 119871119898119882119898119879119898

= 119860 sdot 119879119898

997904rArr

119879119898

=

119881

119860

(15)

Furthermore based on the above mathematical model-ing the geometry of the design accelerometer and its proofmass are defined Such modeling of the proof mass of theaccelerometer clearly depends on the various dimensions ofthe sensing elements depicted in Figure 5

The parameters utilized in Figure 5 such as widththickness and length of the proof mass and anchor dependupon the selection of the type of themodelwhich is illustratedin Table 16 (Appendix) Furthermore the sensitivity ofthe accelerometer is dependent on the size of proof massspring constant and resonance frequency graph in Figure 6illustrating the phenomena that proof mass and resonancefrequency are inversely proportional to each other withincrease in proofmass the resonance frequency decreases andvice versa

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies (Figure 7) The technological lag betweenthe application requirements and performance offered byavailable and emerging accelerometers motivates the devel-opment of dedicated sensing technology depicted in Table 2[16ndash20]

22 Accelerometers Performance Overview MEMS devicesfor seismic applications have previously been designed usingpiezoresistive [49] capacitive [10] and piezoelectric typedsensors [50] Electron tunneling is also a very promising sens-ing mechanism due to its high sensitivity to low vibrations[51]The performance of accelerometers can be characterizedbased on demonstrated operational specifications includingthe following

(i) Acceleration Range Recording unnecessary high ampli-tude signals adversely affects sensor sensitivity and con-sequently the resolution [52] It is necessary to know theacceleration range that is defined as the maximum acceler-ation input that can be measured by the accelerometer in g(acceleration due to gravity) (asymp10msminus2) As a result an idealaccelerometer should be able to capture maximum vibrationsof geophysical interest

(ii) Bandwidth It refers to the frequency range of input accel-eration that the sensor can perform with minimum distor-tion An ideal accelerometer requires minimum bandwidthto reduce undesired noise [52] and should have maximumbandwidth that is sufficient to accommodate all signals ofinterest

(iii) Noise FloorThe noise collectively generated at the sensoroutput when no acceleration is present is referred to assensor noise floor It is a composite of three noise sourcesthe thermomechanical noise (ie Brownian noise) [49 53]

6 Journal of Sensors

Table 2 Comparison of existing MEMS accelerometers [16ndash20]

Sensor Supplier Bandwidth (Hz) Full scale (mg) Noise density (ngradicHz)Trillium [20] Nanometrics 003ndash50 mdash mdashGAC [17] WesternGeco 3ndash200 108 15DSU1 [18] Sercel 0ndash800 500 40 (gt10Hz)HP sensor [19] HP 1ndash200 80 10

Wm = 120583m

Lm = 120583m

Z

X

Y

tm = 120583m

L2 = 120583m

W = 120583m

t = 120583m

Figure 5 Sensing element dimensions

Reso

nanc

e fre

quen

cy (H

z)

60 70 80 90 100 110

Proof mass (120583g)

170

180

190

200

210

220

230

240

Figure 6 Resonance frequency versus proof mass

the thermoelectrical noise (ie Johnson noise) and the 1119891

noise (Hoogersquos noise) [54] The first one is due to the randommotion induced by thermal energy of gaseous moleculessurrounding the proof mass [10] The thermoelectrical noiseis attributed to the random electron motion in the wiresinduced by ambient thermal energy Hoogersquos noise is empiri-cal noise and is function of the frequency For simplicity thetotal noise floor 119886n can be expressed in terms of mechanicalnoise (119886nm) and electrical noise (119886ne) as displayed in

119886119899= radic119886nm

2+ 119886ne2

(16)

The noise floor is desirable to be as minimal as pos-sible but an acceptable level can be determined by therequired resolution To evaluate the need for dedicated sen-sors for hydrocarbon microtremor analysis studies availableaccelerometers have been reviewed Eventually matchinganalysis between sensing requirements and performancemetrics is performed to scope down design possibilitiesand guide promising directions Based on the employedsensing principle the discussion on performance metrics is

Telemetry cable

2 horizontal MEMSLine board

IC board

Servo-loop ASIC

V board

Vertical MEMSEeprom

Figure 7 Three-axis (3-component) seismic sensor unit [16]example of accelerometer used in seismic application

categorized into piezoresistive capacitive piezoelectric andtunneling accelerometers

221 Piezoresistive Piezoresistive accelerometers exploit thepiezoresistive effects of materials typically polysilicon tomeasure the acceleration [50 51]The piezoresistive elementsare embodied in structure in such a way to be subjectedto torsion when acceleration is applied [50] The structurecan typically be a suspended beam with one end attachedto a proof mass [54] The proof mass movement imposesstress changes on the piezoresistive element thus changingits resistance Figure 8 shows a typical example of this typeof accelerometer In this example the proof mass movement

Journal of Sensors 7

A B A B

SubstrateBimorph cantilevers

Proof mass

Figure 8 Piezoresistive accelerometer showing the embodiedpiezoresistors (A B) within the cantilever [43]

implies stress changes along the embedded piezoresistiveelements (polyresistors) in the bimorph cantilever AWheat-stone bridge-like circuitry is used to measure resistancechange and deduce acceleration

For more than three decades piezoresistive accelerom-eters (eg [49 52 53 55ndash64]) have shown progressiveimprovements making them a viable option for variousapplications includingmicrogravity and low frequency appli-cations [59 63]

The demonstrated performance of these devices is shownas in Figure 8

(i) Acceleration Range Piezoresistive accelerometers havebeen designed to work in ranges as small as 1 g [55] or aslarge as 250 g [61] In average they work within 10ndash50 g [4952 53 56ndash60 62ndash64] This operation range is two orders ofmagnitude larger than desired operation range (4 ngndash80mg)(ii) Bandwidth Piezoresistive accelerometer designs [53 5558ndash63] statistically tend to have a median bandwidth of1 KHzThe uppermeasurement limit typically varies between100Hz and 2KHz whereas the lower limit is conventionallynonzero (5ndash100Hz) [46 55 59 63ndash65] except for the case ofemploying nanowires [66] that are able to respond to 0Hzacceleration (static acceleration)(iii) Noise Floor The noise floor is generally in range of 100ndash500120583gradicHz [55 56 59 63 64]

Table 3 summarizes the performance characteristics ofpiezoresistive accelerometers They are advantageously sim-ple in structure fabrication and their read-out circuitry [54]On the other hand the demonstrated performance does showcapability in neither operating in sub-g domain nor achievingbandwidth lt 50Hz or a noise floor below 5 ngradicHz Addi-tionally piezoresistive accelerometers can be seen to haveintrinsic temperature sensitivity andmeasurement drifts [62]These limitations could reduce their suitability for intendedhydrocarbonmicrotremormeasurements of current concern

222 Capacitive Capacitive accelerometers are dominantaccelerometers in market The high sensitivity good noiseperformance and low temperature sensitivity are amongtheir features [54] In principle capacitive types exploitthe change of capacitance between plates on free moving

Table 3 Piezoresistive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small sim1 g Lower limit 5ndash100 Low 100 120583

Medium 10ndash50 g BW sim1 kLarge sim250 g Upper limit 100ndash2 k High 500 120583

ElectrodeSi

Insulated layer

Si

Si

d0

d0

CA

CB

X

Proof mass

Figure 9 Capacitive sensing principle [46]

and fixed microstructures when acceleration is applied [50]Figure 9 shows a simple cantilever structure of capacitivetype accelerometer The structure consists of proof masssuspended via cantilever while the movement is sensed viaelectrodes

For quantitative analysis the performance of capacitiveaccelerometers in [19 65ndash112] is presented as follows

(i) Acceleration Range Depending on order of magnitudecapacitive accelerometers can be observed to operate in fourdifferent ranges (i) sub-g (120583g-mg) range [18 96 103] (ii) 1ndash10 g range [65ndash68 76 77 80 84ndash89 92 95ndash97 100ndash102 105](iii) 10ndash100 g range [69 72ndash74 93 99 104ndash106] and (iv) above1000 g [90 91]

(ii) Bandwidth The bandwidth of capacitive accelerometerstypically starts at DC (0Hz) [65ndash68 86 104 105] in somecases it can begin at nonzero frequencies [19 79 92]Commonly their bandwidth falls in range of 100ndash1000Hzbut it can typically vary in less than 100Hz [69] and above1000Hz [85 110]

(iii) Noise Floor The noise performance of capacitiveaccelerometers varies from 4 ngradicHz [92] up to 400mgradicHz[102] More than 60 of capacitive accelerometers have noisefloor within 120583gradicHz (ie between 01 and 100 120583gradicHz)

Capacitive accelerometers offer wide performance capa-bilities as shown in Table 4 The wide capability variationenables their successful utilization in different industrial

8 Journal of Sensors

Vz

Vx

T

T T

T

CC C C

Figure 10 Accelerometer structures using piezoelectric sensing [47]

Table 4 Capacitive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small lt1mg Small lt100 Small 4 nndash1 120583Medium 1ndash10 g Medium 100ndash1 k Medium 1 120583ndash1mLarge 10ndash100 g Large gt1 k Large gt1mVery large gt1000

domains including biomedical domain navigation spacemicrogravity military and also seismology [19 65ndash112]Remarkably the authors in [92] demonstrated noise per-formance approaching the required noise floor of HyMASapplication However the device resolution is lower than thedesired value because of the wide bandwidthTherefore a gapon achieving the required noise density and bandwidth hasstill not been met

The simple structure low drift and low temperature sen-sitivity of capacitive accelerometers along with demonstratedperformance make them suitable design option for seismicapplications [46 112]

223 Piezoelectric Piezoelectric accelerometers employmaterials with piezoelectric effects to indirectly measureacceleration via amount of deposited electric charges whenstress is induced [50] They are generally featured by lowpower consumption and temperature stability and have beenused in several applications including medical and machinevibration monitoring [47 62 113ndash117]

A typical accelerometer utilizing piezoelectric principle isillustrated in Figure 10 in which the movement of the proofmass imposes deformation on the piezoelectric elements onthe supporting bimorph beam The charge deposition alongthe sensing element induces electrical potential (119881

119909and 119881

119911)

whose magnitude indicates the acceleration appliedThe performance of accelerometers is discussed as fol-

lows

(i) Acceleration Range Piezoelectric accelerometers demon-strate a measurement range around 20ndash25 g [116] but theydo not suit sub-g operation range Additionally the inheritedhysteresis effect reduces the measurement precision that isessentially required for geophysical seismic measurement(ii) Bandwidth Piezoelectric accelerometers are normallyused in dynamic operationmode which can result in leakage

Table 5 Piezoelectric accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

and creep issues [54] The dynamic range is typically within01 kHzndash10 kHz [62 113ndash116] but can be as high as 37 kHzndash35 kHz [114] or as low as 1Hzndash60Hz [47](iii) Noise Floor It falls within the range of 10 ng to 700 ng indesigns [47 116 117] whereas the early designs suffer fromlarge noise floor reaching up to 01 g [113]

Table 5 summarizes the performance characteristics ofpiezoelectric accelerometers From presented literature theyshow substantial performance improvement in the accel-eration range bandwidth and noise level over the lastdecades This could make them viable choice of design forpassive seismic However the inherited creep and tendencyfor dynamic measurements can reduce their suitability forpassive seismic geophysical applications

224 Electron Tunneling Tunneling accelerometers exploitchanges of current tunneling through insulating mediumwith change of separating displacement [48 118ndash121] Fig-ure 11 shows an accelerometer schematic using the electrontunneling principle It is seen that the tunneling tip is justbeneath a suspended proof mass A deflection electrode andproof mass electrodes provide electrostatic force required tocontrol the tunneling current

Electron tunneling is very promising in seismic appli-cation field because of performance high sensitivity smallsize and light weight compared to piezoresistive or capacitivetypes The demonstrated measurement capabilities are statedas follows(i) Acceleration Range During the last two decades 30 grange was typically reported [119 120] Later 1mg rangewas maximally reported [48 121] which proved its sensorcapability to work in seismic operation(ii) Bandwidth Frequently accelerometers are designed towork minimally at 1 kHz bandwidth [47 113ndash122] Thisrange can reach up to 6 kHz [123ndash125] Notably tunnelingaccelerometers have a limit for the minimum detectable

Journal of Sensors 9

Table 6 Tunneling accelerometers performance range

Acceleration range (g) Bandwidth(Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

Vacuum

Proof mass

HingeProof mass electrode

Tunneling tip Deflection electrode

Figure 11 Cross sectional view of tunneling accelerometer withcantilever structure [48]

frequencyThis limit is typically in range of 5ndash200Hz [48 119121](iii) Noise Floor In early tunneling devices the noise floorvaried over a range from 1 120583gradicHz to 4mgradicHz [119 120122] As technology advances a noise floor at nanometerrange (15ndash250 ngradicHz) has been achieved [48 121] Table 6summarizes the performance characteristics of tunnelingaccelerometers in literature Tunneling accelerometers showseismic grade performance with some exception on the widebandwidth of 1 kHz Therefore further filtration process isrequired for narrow bandwidth signals

225 Resistive Accelerometers Resistive accelerometers rec-ognize the change of resistance of a metal strain gauge clungto a cantilever beam Accelerating prompts twisting of thecantilever beam and hence causes variation in the resistanceof the strain gauge In case of a metal foil the geometric effectis identified significantly dominating the piezoelectric effect[50] The model of a Wheatstone bridge circuit configuredfour strain gauges which provide a voltage signal and workfor DC estimation

226 Optical Accelerometers An optical accelerometer dis-tinguishes the change of optical characteristics in an opticalfiberTheFiber BraggGrinding (FBG) is one of themost stan-dard and popular techniques for fiber optical estimation [126127] In this technique Bragg gratings are the interferencefilter composed of optical fibers The characteristic of FBGaccelerometers defines that the appraisals reflect just a narrowspectral component of actuated light Acceleration prompts adistortion of an optical fiber connected to a suspended beamcausing a change in the reflection characteristic of the Bragggratings This change can be distinguished by contrasting thespectral component of the reflected beam with the impelledlight Hence FBG accelerometer is used to perform opticalsignal analysis with DC estimations

Table 7 Sensors performance summary

Type Bandwidth(Hz)

Acceleration(g)

Noise density(gradicHz)

Capacitive 0ndash30 22120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100 120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

227 Thermal Accelerometers Thermal accelerometer hasbeen driven based on mass displacement and does notfound a popularity among others in terms of manufacturerselling [127] Therefore the suited alternative solution of thisissue is thermal accelerometer without mass displacement[127] It consists of a heater and thermocouples situatedaround the radiator in a hermetic chamber On applyingacceleration to the accelerometer hot air in the chambermoves that leads to generating an asymmetric temperatureprofile Such asymmetric profile can be identified by thethermocouples around the radiator This process is calledtransduction principle which produces a voltage signal usingthese accelerometers and work for DC estimation [128]

23 Analysis and Design Challenges For comparative anal-ysis previously mentioned works have been summarized inTable 7 [6 7 34 43 46 62ndash64] The first column shows thesensing type of accelerometers The smallest operating band-width the upper limits of acceleration range and measurednoise floor levels are listed in columns 2ndash4 respectively Thedata summarized inTable 7 indicates the superiority of capac-itive sensors to meet passive seismic sensing requirementsAccording to Section 22 signals required in passive seismicsurvey havemaximumacceleration oflt80mg andbandwidthof 1ndash30Hz with lt1 ngradicHz noise spectral density

The key in designing high resolution capacitive acceler-ometer is to reduce the devicersquos noise floor and increase itssensitivity as demonstrated in [19 88 92 93 104 122 123]The total noise floor comes from mechanical and electricalelements of the sensor

(i) Design Overview The Brownian noise is principallyproportional to the square root of damping factor (119887) andinversely proportional to the proof mass (119898) as in (17) where119896119861and 119879 are Boltzmannrsquos constant (138 times 10minus23 JK) and the

temperature in Kelvin

119886nm =

radic4119896119861119879119887

98119898

(17)

Therefore ultralow noise accelerometers have large proofmass and low gas damping in the mass-spring accelerometersystem [19 92] The mechanical noise can be defined as afunction of the temperature damping coefficient and massWhile the temperature can be set to 20∘C or 29315∘K thedamping coefficient andmass are dependent on the geometryof the structure

10 Journal of Sensors

Sensing fingers

Springs

Driving fingers

(a)

A

A998400

Wb Wa

Lb

La

LeffLf

X0

Wf

(b)

Figure 12 Structure of a lateral capacitive accelerometer (a) isometric device view (b) spring parameters (119882119887119882119886 119871119886 119871119887) and fingers

parameters (1198830119882119891 119871119891 119871eff ) [124]

In the electrical domain the noise can be minimizedby reducing the operating bandwidth Additionally a closed-loop feedback electronic circuit is required to compensate thenonlinear response of the mechanical system and to shortenthe bandwidth of the device to 30Hz To minimize the noiseeffect from amplifier the rate of capacitance change withacceleration needs to be maximized [19] Maximizing thesensitivity requires minimizing sensing gap and lowering thenatural resonant frequency [19 92 129]

As previously discussed the minimum detectable accel-eration should be = 802

24= 47 ng This implies that

the maximum mechanical noise 119886119898

should be less than086 gradicHz according to

119886119898

=

119886minradicBW

=

47 ngradic30

= 086 gradicHz (18)

In order to size the design challenges of ultralow noisefloor a case study on accelerometer design with conventionalcomb structure is considered The structure as shown inFigure 12 comprises a fixed rectangular framewith fingers anda moving proof mass fixed on the frame by spring-like shapeat both ends and surrounded by fingers at its both sides

Accelerometers noise performance is generally deter-mined by the damping coefficient and proof mass size assuggested by (5) The dominant damping mechanism in thisstructure is due to the squeeze-film effect [125]Therefore thedamping coefficient 119887 can be written in

119887 = 72119873120583119905 (

119897eff1199090

)

3

(19)

whereby 119873 is the number of comb fingers 119905 is the proofmass thickness 120583 is the viscosity of the air under atmosphericpressure 20∘C = 154 times 10minus6 kgms and 119897eff is the engagedlength of the comb fingers

Moreover the mass 119898 can be expressed in (20) where 119898

defines the mass of the proof mass 120588 is the silicon density =2330 kgm3 119897

119891is the length of comb fingers 119882

119891is the width

of comb fingers and 119860 is the area of the proof mass

119898 = 119905120588 (119860 + 119873119897119891119882119891) (20)

As a result the mechanical noise 119886nm can be expressed bysubstituting (19) and (20) in (17) to obtain

119886nm =

radic4119896119861119879 [72119873120583119905 (119897eff1199090)

3]

98 [119905120588 (119860 + 119873119897119891119882119891)]

(21)

As depicted in Figure 12(a) the proof mass parameters119860 and 119905 typically have large values compared to fingersdimensions 119871eff 119871119891119882119891 and 119883

0[124] As a result the proof

mass is effectively increased by enlarging parameters119860 and 119905The realization of sub-ngradicHz of noise spectral density

through mass maximization has a positive impact on devicesensitivityThis can be explained by the proportional relation-ship between sensitivity and mass as displayed in

119878 =

119881119904

119886in=

4119862119904

2119862119904+ 119862119901

sdot

119881m1199090

sdot

119898

119896

(22)

whereby 119878 is the sensitivity (Vg) 119862119904is the sensing capaci-

tance 119862119901is the parasitic capacitance119881m is maximum output

voltage (V) 119886in is maximum input acceleration (g) and 119896 isthe spring constant (Nm)

The maximization of sensitivity is an important designgoal This is achievable by maximizing the proof mass andminimizing the spring constant as suggested by (22) How-ever the resonant frequency has to be considered Equations(23) and (24) describe the structural dependencies of thespring constant 119896 and the device resonant frequency 119891respectively as follows

119896 = 2

1

(119899 minus 1)

3sdot 119864 (

119882119887

2119871119887

)

3

119905 (23)

119891 =

1

2120587

sdotradic

119896

119898

(24)

where 119899 is the number of mechanical spring turns 119882119887is

the width of single turn spring 119871119887is the length of single

turn spring and 119864 is Youngrsquos Modulus of silicon = 154 times

10minus6 kgms

231 Summarized Analysis of the Type of Accelerometers Forinitial analysis (18)ndash(23) have been solved yielding to the

Journal of Sensors 11

Table 8 Initial design parameters and values

Parameter Value Parameter Value119897eff 80 120583m 119899 8119897119891

85 120583m 1199090

83 120583m119882119891

48 120583m 119905 3318 120583m119873 200 119897

1198872mm

119860 5mm times 5mm 119882119887

75 120583m119898 2120583g 119886nm 085 ngrtHz119891 46Hz 119878 026

values as listed in Table 8 The table shows the parametersand the corresponding values for the design in rows 2ndash6The resulting device performance (noise resonant frequencyand sensitivity) is shown in the last two rows The tableshows that a 5mm times 5mm proof mass area was requiredEven though the sensitivity (026Vg) is lower than state-of-the-art value this device is considered large structure forconventional CMOS technology To improve the sensitivityfurther enlargement for the proof mass is required Thisshows the major challenge of the design

Therefore achieving the noise spectral density of less than1 ngradicHz on a conventional capacitive structure is challeng-ing As a result a novel structure and design optimization isexpected to meet the stringent resolution level requirements

232 Conclusion on the Analysis The excessive demandsfor hydrocarbon have pushed the exploration technologyto the era of passive seismic monitoring The technique iseconomically promising and environmentally friendly butfacing several challenges among which is the high resolutionacquisition using state-of-the-art sensorsaccelerometers

In this paper the technological gap between themeasure-ment resolution of the state-of-the-art sensors and emergingdevices is identified for passive seismic monitoring It showsdesign possibilities using capacitive sensing techniques andmotivates further work in developing optimized sensor solu-tions

Finally a solution has been provided with specificationto design such an accelerometer To enhance the resolutionand sensitivity a dimension in the order of millimeters largerthan conventional MEMS dimensions is required Moreovertechnological issues including reducing parasitic capacitanceby increasing dielectric thickness and reducing air pressurefor less damping impact beyond 1ndash10 Torr are among theconstraints hindering prospective designs

In synopsis piezoelectric accelerometers demonstrate themost astounding estimation range shock limits and oper-ating temperature capacitive accelerometers the least powerutilization and volume and piezoresistive accelerometers thevastest frequency response

3 Sensors in Seismology

Seismic study determines that the effective exploration tech-nique for imaging the geology is active seismic imagingPreviously explosives or vibroseis trucks are utilized for

Nor

mal

ized

ampl

itude

minus1

minus05

0

05

1

0 02 04 06 08 1 12 14

Time (s)

P-wave S-wave

Figure 13 A ldquogoodrdquo occurrence of P- and S-wave arrivals in timedomain [44]

Nor

mal

ized

ampl

itude

minus1minus05

0051

0 02 04 06 08 1 12 14

Time (s)

Figure 14 A random ldquonoiserdquo event at time domain [33]

generating seismic energy sensed by the network of seismicsensors which may provide the information that determinesthe prospective oil and gas traps In view of received sensordata a 3D stratigraphy map is developed This 3D map mayhelp in determining the position of hydrocarbon depositionsMoreover the increasing demand and supply of oil and gasneed industries to explore more hydrocarbons from previous50 to 80 by identifying accurate information about hydro-carbon deposition [44 45] Conventional techniques cannotprovide the correct information about the petrophysicalproperties of reservoir because the rock pores having hydro-carbon affect the physical properties of the rockwhich in turncause poor energy sensed through seismic sensors One ofthe key solutions for accurate information is passive seismicimaging technique This technique uses naturally happeningseismic signals like earth quake microtremors and oceanwaves for subsurface imaging and structuring In comparisonof conventional technique having sensing frequency in therange of 10ndash300Hz passive seismic technique monitors thelower frequency waves (below 10Hz) whichmay travel a longdistance through the earthrsquos crust without attenuation

An example of ldquoGoodrdquo event having occurrences of P-wave and S-wave at time domain is showed in Figure 13 Onthe basis of the discrete and impulsive P-wave and S-wavearrivals the event is termed ldquoGoodrdquo event [33]

Also it is shown clearly that frequency of S-wavedecreases as the frequency of P-wave increases A randomldquonoiserdquo event occurring at time domain with indeterministicproperties of ldquoGoodrdquo events is shown in Figure 14 [33]

In the area of reservoir monitoring passive seismichave applications for recording microseismic signal at nat-ural frequency for the exploration and exploitation of thehydrocarbons (ie oil and gas) [131] The study of passiveseismic at variant frequency identifies that information aboutprediction of hydrocarbon reservoir is found at low frequencyof less than 10Hz [1ndash5 132] as depicted in Table 9

12 Journal of Sensors

Table 9 Technical description of seismic data acquisition technique at low frequency

Frequency range focused Technique used Advantage Disadvantage

Modeling frequency 50ndash60Hz[25]

Spike deconvolution for lowfrequency modeling

(i) Low-cut filter is used toattenuate low frequencies

(ii) Defining technique producesbetter P-wave and S-wave seismic

section

(i) Need for recovery of broadsignal bandwidth

(ii) Poor wavelet extraction andits structure

Modeling frequency 1 KHzAcquired seismic frequency12HzReflectivity at 40Hz [26]

(i) Ultrasonic experiment(ii) Seismic data analysis

(i) Signal is reflected from a thinwater- (S

119908) or oil-saturated (S

ℎ)

layer(ii) Frequency dependent

amplitude and phase reflectionattributes have been utilized forobserving and identifying thin

liquid saturated layers

(i) Strong attenuation in the layeraffects summation of multiples

(ii) Layers with higherattenuation create travel timedelays which increase asfrequency approaches zero

Missing frequency 5ndash10Hz [27]

(i) 3D acoustic inversion(ii) Variable depth streamerseismic data acquisition(iii) 3D elastic inversioncomparison technique

(i) Variable depth streamer fordata acquisition is better for

inversion and provides missinglow frequencies directly

(ii) Left side lobe of the wavelet isproposed to reduceless

interference in the seismic signalresults in less ambiguity in

inversion

(i) There is variation in resultinginversion due to high variation in

acquisition frequency(ii) Broadband inversion may

cause obtained results outside thetarget zone

Reflection lt15HzAmplitude 40Hz [28]

(i) AVO attribute analysis(ii) VSP analysis

(i) Imaging at low frequenciesresults in robust amplitudes for

individual frequencycomponents of propagating

wavelet(ii) Frequency based seismic

imaging permits characterizingthe subsurface fluid reservoirs

(i) Quantitative analysis of AI (asfrequency) requires NMO

stretching(ii) Conventional seismic

processing software does notwork as target-oriented

processing

Based on Table 9 it is clear that the type of geophonesused in active seismic acquisition has greater size and islinearly proportional to the velocity over the resonancefrequency (about 10Hz) [25ndash28] Therefore a new design ofthe accelerometer is defined which offers a minimal signalroll-off small size and weight solution to the larger arrayslayout Also from the table it is identified that passive seismichas high potential benefits but requires special ultra noiselow frequency and short bandwidth sensing capabilitiesSince the existing device and the sensor are unable torecord at this frequency various types of sensor are studied(discussed in Section 4) Based on sensor analysis it isfound that MEMS accelerometers (capacitive) based deviceis the best replacement of existing seismological equipmentCapacitive accelerometers performed well in low bandwidthlow frequency and minimum noise Hence passive seismicexploration is an ongoing and promising research topic withthe benefit of being environmentally friendly and of low cost

31 Comparison of Technical Structure of Active andPassive Imaging

311 Active Seismic ImagingMethod In the acquisition of theactive seismic data a feedback model has been implementedwhich is based on the principal that both sources and

Pminus(z0 z0) Rcap(z0 z0)

X0(z0 z0)

120575P+(z0 z0)

S+(z0)+

X(z0 z0)

Figure 15 A feedforward model representing the upgoing anddowngoing wavefields in conventional seismic acquisition [130]

detectors are normally placed at or near the earthrsquos surfacedepicted in Figure 15 [133] It demonstrates schematically up-and downgoingwavefields happening at the reflecting surface(1199110) while the wavefields are going ldquoalongrdquo the surface being

overlookedAccordingly consider a matrix 119883

0(1199110 1199110) having a mul-

tidimensional transfer function of the subsurface (119911 gt 1199110)

Here each variable of1198830(1199110 1199110) characterized as the impulse

response of the wavefield occurred from a unit dipole sourceat 1199110and is further sensed by a unit pressure sensor at 119911

0 Also

the subscript ldquo0rdquo in 1198830symbolizes that earthrsquos surface has a

free reflection boundary that is a single round-trip (mean

Journal of Sensors 13

two-way time) has been estimated by the seismic signal fromthe subsurface (from 119911

0to 1199110) 1198830(1199110 1199110) has been utilized

as the multidimensional wavefield operator which definesthe wavefields at the reflection free acquisition surface 119911

0

119875

minus

0(1199110 1199110) as

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (25a)

or

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 120575119875

+(1199110 1199110)

+ 1198830(1199110 1199110) 119878

+

0(1199110 1199110)

(25b)

with combining

120575119875

+(1199110 1199110) = 119877

cap(1199110 1199110) 119875

minus

0(1199110 1199110) (25c)

In (25a) source matrix 119878

+

0(1199110) signifies the downgoing

wavefield of one physical source (array) at 1199110

However1198830119878

+ stands for the upgoing primary wavefields(one round-trip) and119883

0120575119875

+ stands for the upgoingmultiple-scattering wavefields (many round-trips)

Furthermore from (25a)ndash(25c) it can be simply derivedthat

1198830(1199110 1199110)

= [119868 minus 1198830(1199110 1199110) 119877

cap(1199110 1199110)]

minus1

1198830(1199110 1199110)

(26a)

representing the complexity of119883 relating to1198830 On compar-

ing (25a)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (26b)

with (25b)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) [120575119875

+(1199110 1199110) + 119878

+(1199110 1199110)] (26c)

Based on (26b) it can be concluded that the surface-related multiple-scattering phenomenon is incorporated intoa parameter 119883 However (26c) signifies that the surface-related multiple-scattering is incorporated into the downgo-ing wavefield 120575

119875

+

and the parameter 119883 determined as 1198830

Such variation between mathematical equations (26b) and(26c) assumes an imperative part in the inversion modelingfor seismic imaging [134]

Here Figure 16 represents the mixed shot record array offive sources at or near the surfaces Since during acquisitionzero time delays and large spacing between the sourcesare considered resulting incoherent shooting will becomesimultaneous shooting [136 139 140]The resultants imagingsignifies that a passive seismic recording can be measured asa naturally mixed shot record

312 Passive Seismic Imaging Method Based on DownwardRadiating Natural Sources Initially it is considered thatpseudo sources are set at or close to the surface (119911

0)

signifying that the background noise is considered as thosewavefields generated by the natural sources However in pas-sive seismic imaging response from natural sources has been

Tim

e (s)

30

25

20

15

10

05

00 1000 2000 3000 4000 5000

Lateral distance (m)

Figure 16 A mixed pseudo shot record generated by usingincoherent source array having five source elements at the surface[135 136]

considered as the seismic signal from the subsurface Thesesources might be set anyplace at the surface (119911 = 119911

0) and

in the subsurface (119911 gt 1199110) [137] Henceforth a noise model

has been createdwhichmay consider a continuing happeningseismic background noise as an indicator to determine theinformative data from these noises This concept is knownas seismic interferometry [141] Furthermore a relationshipby utilizing the wavefield diagram (see Figure 9) has beenestablished between the downgoing source wavefield at thesource level (119911

119899) and the up- and downgoing wavefields at

perception level 1199110(119911 = 119911

0) Such relation can be expressed

as

119875

+

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 119911119899)

119878

+

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110) [119882

minus1(1199110 119911119899)

119878

+

(119911119899)]

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110)

119878

+

(1199110 119911119899)

(27a)

where

119882

minus1(1199110 119911119899) = 119883

minus1

0(1199110 1199110)1198830(1199110 1199110) (27b)

Figure 17 describes the feed-forwarded model which isbased on modeling by downward radiating natural sourcesat and below the surface (119899 ge 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

313 Passive Seismic Imaging Method Based on UpwardRadiating Natural Sources In this phase like active seismicbackground noise similar type of natural sourcersquos responseis considered but the direction has been changed to the

14 Journal of Sensors

rarr(z0 zn)

W(zn z0)

Rcap(z0 z0)

rarr(zn)+X0(z0 zn)

120575rarr

(z0 zn)

n = 0 1 2 middot middot middot

Pminus

P+

S+

Figure 17 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

rarrPminus(z0 zn)

W(z0 zn)

Rcap(z0 z0)

rarrS (zn)

+ X0(zn z0)

120575rarrP (z0 zn)

n = 1 2

+

minus

Figure 18 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

contribution of ldquoupwardrdquo radiation Figure 18 depicts theresultants response which describes the correlation betweenthe upgoing source wavefields at the source level (119911

119899) and the

up- and downgoing wavefields at observation level 1199110 Such

result can be expressed as

119875

minus

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 119882(1199110 119911119899)

119878

minus

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899) +

119878

minus

(1199110 119911119899)

(28)

Figure 18 describes the feed-forwarded model which isbased on modeling by upward radiating natural sources atand below the surface (119899 gt 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

314 Statistical Description of the Modeling In the statisticalanalysis of the above designed model the above definedexpressions have been utilized on an exceptionally straight-forward medium Such medium has one horizontal reflectorand a free surface depicted in Figure 19 The stepwiseconstruction of thismedium signifies imaging in Figure 19(a)describing the conventional active seismic record where oneprimary and the surface multiples have been identified andindicated by a mathematical expression in (25b) In continu-ation Figure 19(b) describes the measurement of a responsefrom a downward radiating noise burst by implementing(27a) and (27b) while Figure 19(c) describes the upwardtransmitting patterns by estimating (28)

From these figures and equation implementation it isclearly defined that the occurrence of response and its mul-tiples takes place directly Moreover Figure 19(d) preciselydemonstrates the effect of such multiples that is the noisebursts being the summation of Figures 19(b) and 19(c)respectively

Figure 19 defines the straightforward medium whichhas one horizontal reflector and a stress-free surface HereFigure 19(a) describes the impulsive source at the surfacewhile Figure 19(b) shows at first layer the downward radiatingnoise source Similarly Figure 19(c) shows at first layerthe upward radiating noise source Finally Figure 19(d)establishes the omnidirectional noise source in the first layerof imagingOverall it has been signified that different sourcesdetermine the different resultant responses For exampleFigure 19 clearly proved this statement by demonstrating thatall sources defined here produce the different responses at ornear the subsurface of seismic imaging

32 Example Showing the Processing of Active and PassiveSeismic Imaging and Their Significance In this examplefor a mixed seismic data response inversion method fol-lowed for known and unknown sources is illustrated Herethree reflectors are utilized to measure the response forthe subsurface modeling (see Figure 20(a)) To begin withwithout considering surface-related multiples 119883

0 the mul-

tidimensional impulse response of the subsurface has beenproduced However Figures 20(b)ndash20(d) describe the three-column impulsive response of 119883

0 It results in naturally

occurring mixed recording at the subsurface Therefore inthe next modeling step surface-related multiples have beenimplemented that is from119883

0to119883

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

[1] A E de Vasconcelos Lopes and L C Nunes ldquoPitfalls of tremor-like signals for hydrocarbon exploration in producing oil fieldsin Potiguar basin northeast Brazilrdquo The Leading Edge vol 29no 7 pp 826ndash830 2010

[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

Journal of Sensors 25

[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

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International Journal of

6 Journal of Sensors

Table 2 Comparison of existing MEMS accelerometers [16ndash20]

Sensor Supplier Bandwidth (Hz) Full scale (mg) Noise density (ngradicHz)Trillium [20] Nanometrics 003ndash50 mdash mdashGAC [17] WesternGeco 3ndash200 108 15DSU1 [18] Sercel 0ndash800 500 40 (gt10Hz)HP sensor [19] HP 1ndash200 80 10

Wm = 120583m

Lm = 120583m

Z

X

Y

tm = 120583m

L2 = 120583m

W = 120583m

t = 120583m

Figure 5 Sensing element dimensions

Reso

nanc

e fre

quen

cy (H

z)

60 70 80 90 100 110

Proof mass (120583g)

170

180

190

200

210

220

230

240

Figure 6 Resonance frequency versus proof mass

the thermoelectrical noise (ie Johnson noise) and the 1119891

noise (Hoogersquos noise) [54] The first one is due to the randommotion induced by thermal energy of gaseous moleculessurrounding the proof mass [10] The thermoelectrical noiseis attributed to the random electron motion in the wiresinduced by ambient thermal energy Hoogersquos noise is empiri-cal noise and is function of the frequency For simplicity thetotal noise floor 119886n can be expressed in terms of mechanicalnoise (119886nm) and electrical noise (119886ne) as displayed in

119886119899= radic119886nm

2+ 119886ne2

(16)

The noise floor is desirable to be as minimal as pos-sible but an acceptable level can be determined by therequired resolution To evaluate the need for dedicated sen-sors for hydrocarbon microtremor analysis studies availableaccelerometers have been reviewed Eventually matchinganalysis between sensing requirements and performancemetrics is performed to scope down design possibilitiesand guide promising directions Based on the employedsensing principle the discussion on performance metrics is

Telemetry cable

2 horizontal MEMSLine board

IC board

Servo-loop ASIC

V board

Vertical MEMSEeprom

Figure 7 Three-axis (3-component) seismic sensor unit [16]example of accelerometer used in seismic application

categorized into piezoresistive capacitive piezoelectric andtunneling accelerometers

221 Piezoresistive Piezoresistive accelerometers exploit thepiezoresistive effects of materials typically polysilicon tomeasure the acceleration [50 51]The piezoresistive elementsare embodied in structure in such a way to be subjectedto torsion when acceleration is applied [50] The structurecan typically be a suspended beam with one end attachedto a proof mass [54] The proof mass movement imposesstress changes on the piezoresistive element thus changingits resistance Figure 8 shows a typical example of this typeof accelerometer In this example the proof mass movement

Journal of Sensors 7

A B A B

SubstrateBimorph cantilevers

Proof mass

Figure 8 Piezoresistive accelerometer showing the embodiedpiezoresistors (A B) within the cantilever [43]

implies stress changes along the embedded piezoresistiveelements (polyresistors) in the bimorph cantilever AWheat-stone bridge-like circuitry is used to measure resistancechange and deduce acceleration

For more than three decades piezoresistive accelerom-eters (eg [49 52 53 55ndash64]) have shown progressiveimprovements making them a viable option for variousapplications includingmicrogravity and low frequency appli-cations [59 63]

The demonstrated performance of these devices is shownas in Figure 8

(i) Acceleration Range Piezoresistive accelerometers havebeen designed to work in ranges as small as 1 g [55] or aslarge as 250 g [61] In average they work within 10ndash50 g [4952 53 56ndash60 62ndash64] This operation range is two orders ofmagnitude larger than desired operation range (4 ngndash80mg)(ii) Bandwidth Piezoresistive accelerometer designs [53 5558ndash63] statistically tend to have a median bandwidth of1 KHzThe uppermeasurement limit typically varies between100Hz and 2KHz whereas the lower limit is conventionallynonzero (5ndash100Hz) [46 55 59 63ndash65] except for the case ofemploying nanowires [66] that are able to respond to 0Hzacceleration (static acceleration)(iii) Noise Floor The noise floor is generally in range of 100ndash500120583gradicHz [55 56 59 63 64]

Table 3 summarizes the performance characteristics ofpiezoresistive accelerometers They are advantageously sim-ple in structure fabrication and their read-out circuitry [54]On the other hand the demonstrated performance does showcapability in neither operating in sub-g domain nor achievingbandwidth lt 50Hz or a noise floor below 5 ngradicHz Addi-tionally piezoresistive accelerometers can be seen to haveintrinsic temperature sensitivity andmeasurement drifts [62]These limitations could reduce their suitability for intendedhydrocarbonmicrotremormeasurements of current concern

222 Capacitive Capacitive accelerometers are dominantaccelerometers in market The high sensitivity good noiseperformance and low temperature sensitivity are amongtheir features [54] In principle capacitive types exploitthe change of capacitance between plates on free moving

Table 3 Piezoresistive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small sim1 g Lower limit 5ndash100 Low 100 120583

Medium 10ndash50 g BW sim1 kLarge sim250 g Upper limit 100ndash2 k High 500 120583

ElectrodeSi

Insulated layer

Si

Si

d0

d0

CA

CB

X

Proof mass

Figure 9 Capacitive sensing principle [46]

and fixed microstructures when acceleration is applied [50]Figure 9 shows a simple cantilever structure of capacitivetype accelerometer The structure consists of proof masssuspended via cantilever while the movement is sensed viaelectrodes

For quantitative analysis the performance of capacitiveaccelerometers in [19 65ndash112] is presented as follows

(i) Acceleration Range Depending on order of magnitudecapacitive accelerometers can be observed to operate in fourdifferent ranges (i) sub-g (120583g-mg) range [18 96 103] (ii) 1ndash10 g range [65ndash68 76 77 80 84ndash89 92 95ndash97 100ndash102 105](iii) 10ndash100 g range [69 72ndash74 93 99 104ndash106] and (iv) above1000 g [90 91]

(ii) Bandwidth The bandwidth of capacitive accelerometerstypically starts at DC (0Hz) [65ndash68 86 104 105] in somecases it can begin at nonzero frequencies [19 79 92]Commonly their bandwidth falls in range of 100ndash1000Hzbut it can typically vary in less than 100Hz [69] and above1000Hz [85 110]

(iii) Noise Floor The noise performance of capacitiveaccelerometers varies from 4 ngradicHz [92] up to 400mgradicHz[102] More than 60 of capacitive accelerometers have noisefloor within 120583gradicHz (ie between 01 and 100 120583gradicHz)

Capacitive accelerometers offer wide performance capa-bilities as shown in Table 4 The wide capability variationenables their successful utilization in different industrial

8 Journal of Sensors

Vz

Vx

T

T T

T

CC C C

Figure 10 Accelerometer structures using piezoelectric sensing [47]

Table 4 Capacitive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small lt1mg Small lt100 Small 4 nndash1 120583Medium 1ndash10 g Medium 100ndash1 k Medium 1 120583ndash1mLarge 10ndash100 g Large gt1 k Large gt1mVery large gt1000

domains including biomedical domain navigation spacemicrogravity military and also seismology [19 65ndash112]Remarkably the authors in [92] demonstrated noise per-formance approaching the required noise floor of HyMASapplication However the device resolution is lower than thedesired value because of the wide bandwidthTherefore a gapon achieving the required noise density and bandwidth hasstill not been met

The simple structure low drift and low temperature sen-sitivity of capacitive accelerometers along with demonstratedperformance make them suitable design option for seismicapplications [46 112]

223 Piezoelectric Piezoelectric accelerometers employmaterials with piezoelectric effects to indirectly measureacceleration via amount of deposited electric charges whenstress is induced [50] They are generally featured by lowpower consumption and temperature stability and have beenused in several applications including medical and machinevibration monitoring [47 62 113ndash117]

A typical accelerometer utilizing piezoelectric principle isillustrated in Figure 10 in which the movement of the proofmass imposes deformation on the piezoelectric elements onthe supporting bimorph beam The charge deposition alongthe sensing element induces electrical potential (119881

119909and 119881

119911)

whose magnitude indicates the acceleration appliedThe performance of accelerometers is discussed as fol-

lows

(i) Acceleration Range Piezoelectric accelerometers demon-strate a measurement range around 20ndash25 g [116] but theydo not suit sub-g operation range Additionally the inheritedhysteresis effect reduces the measurement precision that isessentially required for geophysical seismic measurement(ii) Bandwidth Piezoelectric accelerometers are normallyused in dynamic operationmode which can result in leakage

Table 5 Piezoelectric accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

and creep issues [54] The dynamic range is typically within01 kHzndash10 kHz [62 113ndash116] but can be as high as 37 kHzndash35 kHz [114] or as low as 1Hzndash60Hz [47](iii) Noise Floor It falls within the range of 10 ng to 700 ng indesigns [47 116 117] whereas the early designs suffer fromlarge noise floor reaching up to 01 g [113]

Table 5 summarizes the performance characteristics ofpiezoelectric accelerometers From presented literature theyshow substantial performance improvement in the accel-eration range bandwidth and noise level over the lastdecades This could make them viable choice of design forpassive seismic However the inherited creep and tendencyfor dynamic measurements can reduce their suitability forpassive seismic geophysical applications

224 Electron Tunneling Tunneling accelerometers exploitchanges of current tunneling through insulating mediumwith change of separating displacement [48 118ndash121] Fig-ure 11 shows an accelerometer schematic using the electrontunneling principle It is seen that the tunneling tip is justbeneath a suspended proof mass A deflection electrode andproof mass electrodes provide electrostatic force required tocontrol the tunneling current

Electron tunneling is very promising in seismic appli-cation field because of performance high sensitivity smallsize and light weight compared to piezoresistive or capacitivetypes The demonstrated measurement capabilities are statedas follows(i) Acceleration Range During the last two decades 30 grange was typically reported [119 120] Later 1mg rangewas maximally reported [48 121] which proved its sensorcapability to work in seismic operation(ii) Bandwidth Frequently accelerometers are designed towork minimally at 1 kHz bandwidth [47 113ndash122] Thisrange can reach up to 6 kHz [123ndash125] Notably tunnelingaccelerometers have a limit for the minimum detectable

Journal of Sensors 9

Table 6 Tunneling accelerometers performance range

Acceleration range (g) Bandwidth(Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

Vacuum

Proof mass

HingeProof mass electrode

Tunneling tip Deflection electrode

Figure 11 Cross sectional view of tunneling accelerometer withcantilever structure [48]

frequencyThis limit is typically in range of 5ndash200Hz [48 119121](iii) Noise Floor In early tunneling devices the noise floorvaried over a range from 1 120583gradicHz to 4mgradicHz [119 120122] As technology advances a noise floor at nanometerrange (15ndash250 ngradicHz) has been achieved [48 121] Table 6summarizes the performance characteristics of tunnelingaccelerometers in literature Tunneling accelerometers showseismic grade performance with some exception on the widebandwidth of 1 kHz Therefore further filtration process isrequired for narrow bandwidth signals

225 Resistive Accelerometers Resistive accelerometers rec-ognize the change of resistance of a metal strain gauge clungto a cantilever beam Accelerating prompts twisting of thecantilever beam and hence causes variation in the resistanceof the strain gauge In case of a metal foil the geometric effectis identified significantly dominating the piezoelectric effect[50] The model of a Wheatstone bridge circuit configuredfour strain gauges which provide a voltage signal and workfor DC estimation

226 Optical Accelerometers An optical accelerometer dis-tinguishes the change of optical characteristics in an opticalfiberTheFiber BraggGrinding (FBG) is one of themost stan-dard and popular techniques for fiber optical estimation [126127] In this technique Bragg gratings are the interferencefilter composed of optical fibers The characteristic of FBGaccelerometers defines that the appraisals reflect just a narrowspectral component of actuated light Acceleration prompts adistortion of an optical fiber connected to a suspended beamcausing a change in the reflection characteristic of the Bragggratings This change can be distinguished by contrasting thespectral component of the reflected beam with the impelledlight Hence FBG accelerometer is used to perform opticalsignal analysis with DC estimations

Table 7 Sensors performance summary

Type Bandwidth(Hz)

Acceleration(g)

Noise density(gradicHz)

Capacitive 0ndash30 22120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100 120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

227 Thermal Accelerometers Thermal accelerometer hasbeen driven based on mass displacement and does notfound a popularity among others in terms of manufacturerselling [127] Therefore the suited alternative solution of thisissue is thermal accelerometer without mass displacement[127] It consists of a heater and thermocouples situatedaround the radiator in a hermetic chamber On applyingacceleration to the accelerometer hot air in the chambermoves that leads to generating an asymmetric temperatureprofile Such asymmetric profile can be identified by thethermocouples around the radiator This process is calledtransduction principle which produces a voltage signal usingthese accelerometers and work for DC estimation [128]

23 Analysis and Design Challenges For comparative anal-ysis previously mentioned works have been summarized inTable 7 [6 7 34 43 46 62ndash64] The first column shows thesensing type of accelerometers The smallest operating band-width the upper limits of acceleration range and measurednoise floor levels are listed in columns 2ndash4 respectively Thedata summarized inTable 7 indicates the superiority of capac-itive sensors to meet passive seismic sensing requirementsAccording to Section 22 signals required in passive seismicsurvey havemaximumacceleration oflt80mg andbandwidthof 1ndash30Hz with lt1 ngradicHz noise spectral density

The key in designing high resolution capacitive acceler-ometer is to reduce the devicersquos noise floor and increase itssensitivity as demonstrated in [19 88 92 93 104 122 123]The total noise floor comes from mechanical and electricalelements of the sensor

(i) Design Overview The Brownian noise is principallyproportional to the square root of damping factor (119887) andinversely proportional to the proof mass (119898) as in (17) where119896119861and 119879 are Boltzmannrsquos constant (138 times 10minus23 JK) and the

temperature in Kelvin

119886nm =

radic4119896119861119879119887

98119898

(17)

Therefore ultralow noise accelerometers have large proofmass and low gas damping in the mass-spring accelerometersystem [19 92] The mechanical noise can be defined as afunction of the temperature damping coefficient and massWhile the temperature can be set to 20∘C or 29315∘K thedamping coefficient andmass are dependent on the geometryof the structure

10 Journal of Sensors

Sensing fingers

Springs

Driving fingers

(a)

A

A998400

Wb Wa

Lb

La

LeffLf

X0

Wf

(b)

Figure 12 Structure of a lateral capacitive accelerometer (a) isometric device view (b) spring parameters (119882119887119882119886 119871119886 119871119887) and fingers

parameters (1198830119882119891 119871119891 119871eff ) [124]

In the electrical domain the noise can be minimizedby reducing the operating bandwidth Additionally a closed-loop feedback electronic circuit is required to compensate thenonlinear response of the mechanical system and to shortenthe bandwidth of the device to 30Hz To minimize the noiseeffect from amplifier the rate of capacitance change withacceleration needs to be maximized [19] Maximizing thesensitivity requires minimizing sensing gap and lowering thenatural resonant frequency [19 92 129]

As previously discussed the minimum detectable accel-eration should be = 802

24= 47 ng This implies that

the maximum mechanical noise 119886119898

should be less than086 gradicHz according to

119886119898

=

119886minradicBW

=

47 ngradic30

= 086 gradicHz (18)

In order to size the design challenges of ultralow noisefloor a case study on accelerometer design with conventionalcomb structure is considered The structure as shown inFigure 12 comprises a fixed rectangular framewith fingers anda moving proof mass fixed on the frame by spring-like shapeat both ends and surrounded by fingers at its both sides

Accelerometers noise performance is generally deter-mined by the damping coefficient and proof mass size assuggested by (5) The dominant damping mechanism in thisstructure is due to the squeeze-film effect [125]Therefore thedamping coefficient 119887 can be written in

119887 = 72119873120583119905 (

119897eff1199090

)

3

(19)

whereby 119873 is the number of comb fingers 119905 is the proofmass thickness 120583 is the viscosity of the air under atmosphericpressure 20∘C = 154 times 10minus6 kgms and 119897eff is the engagedlength of the comb fingers

Moreover the mass 119898 can be expressed in (20) where 119898

defines the mass of the proof mass 120588 is the silicon density =2330 kgm3 119897

119891is the length of comb fingers 119882

119891is the width

of comb fingers and 119860 is the area of the proof mass

119898 = 119905120588 (119860 + 119873119897119891119882119891) (20)

As a result the mechanical noise 119886nm can be expressed bysubstituting (19) and (20) in (17) to obtain

119886nm =

radic4119896119861119879 [72119873120583119905 (119897eff1199090)

3]

98 [119905120588 (119860 + 119873119897119891119882119891)]

(21)

As depicted in Figure 12(a) the proof mass parameters119860 and 119905 typically have large values compared to fingersdimensions 119871eff 119871119891119882119891 and 119883

0[124] As a result the proof

mass is effectively increased by enlarging parameters119860 and 119905The realization of sub-ngradicHz of noise spectral density

through mass maximization has a positive impact on devicesensitivityThis can be explained by the proportional relation-ship between sensitivity and mass as displayed in

119878 =

119881119904

119886in=

4119862119904

2119862119904+ 119862119901

sdot

119881m1199090

sdot

119898

119896

(22)

whereby 119878 is the sensitivity (Vg) 119862119904is the sensing capaci-

tance 119862119901is the parasitic capacitance119881m is maximum output

voltage (V) 119886in is maximum input acceleration (g) and 119896 isthe spring constant (Nm)

The maximization of sensitivity is an important designgoal This is achievable by maximizing the proof mass andminimizing the spring constant as suggested by (22) How-ever the resonant frequency has to be considered Equations(23) and (24) describe the structural dependencies of thespring constant 119896 and the device resonant frequency 119891respectively as follows

119896 = 2

1

(119899 minus 1)

3sdot 119864 (

119882119887

2119871119887

)

3

119905 (23)

119891 =

1

2120587

sdotradic

119896

119898

(24)

where 119899 is the number of mechanical spring turns 119882119887is

the width of single turn spring 119871119887is the length of single

turn spring and 119864 is Youngrsquos Modulus of silicon = 154 times

10minus6 kgms

231 Summarized Analysis of the Type of Accelerometers Forinitial analysis (18)ndash(23) have been solved yielding to the

Journal of Sensors 11

Table 8 Initial design parameters and values

Parameter Value Parameter Value119897eff 80 120583m 119899 8119897119891

85 120583m 1199090

83 120583m119882119891

48 120583m 119905 3318 120583m119873 200 119897

1198872mm

119860 5mm times 5mm 119882119887

75 120583m119898 2120583g 119886nm 085 ngrtHz119891 46Hz 119878 026

values as listed in Table 8 The table shows the parametersand the corresponding values for the design in rows 2ndash6The resulting device performance (noise resonant frequencyand sensitivity) is shown in the last two rows The tableshows that a 5mm times 5mm proof mass area was requiredEven though the sensitivity (026Vg) is lower than state-of-the-art value this device is considered large structure forconventional CMOS technology To improve the sensitivityfurther enlargement for the proof mass is required Thisshows the major challenge of the design

Therefore achieving the noise spectral density of less than1 ngradicHz on a conventional capacitive structure is challeng-ing As a result a novel structure and design optimization isexpected to meet the stringent resolution level requirements

232 Conclusion on the Analysis The excessive demandsfor hydrocarbon have pushed the exploration technologyto the era of passive seismic monitoring The technique iseconomically promising and environmentally friendly butfacing several challenges among which is the high resolutionacquisition using state-of-the-art sensorsaccelerometers

In this paper the technological gap between themeasure-ment resolution of the state-of-the-art sensors and emergingdevices is identified for passive seismic monitoring It showsdesign possibilities using capacitive sensing techniques andmotivates further work in developing optimized sensor solu-tions

Finally a solution has been provided with specificationto design such an accelerometer To enhance the resolutionand sensitivity a dimension in the order of millimeters largerthan conventional MEMS dimensions is required Moreovertechnological issues including reducing parasitic capacitanceby increasing dielectric thickness and reducing air pressurefor less damping impact beyond 1ndash10 Torr are among theconstraints hindering prospective designs

In synopsis piezoelectric accelerometers demonstrate themost astounding estimation range shock limits and oper-ating temperature capacitive accelerometers the least powerutilization and volume and piezoresistive accelerometers thevastest frequency response

3 Sensors in Seismology

Seismic study determines that the effective exploration tech-nique for imaging the geology is active seismic imagingPreviously explosives or vibroseis trucks are utilized for

Nor

mal

ized

ampl

itude

minus1

minus05

0

05

1

0 02 04 06 08 1 12 14

Time (s)

P-wave S-wave

Figure 13 A ldquogoodrdquo occurrence of P- and S-wave arrivals in timedomain [44]

Nor

mal

ized

ampl

itude

minus1minus05

0051

0 02 04 06 08 1 12 14

Time (s)

Figure 14 A random ldquonoiserdquo event at time domain [33]

generating seismic energy sensed by the network of seismicsensors which may provide the information that determinesthe prospective oil and gas traps In view of received sensordata a 3D stratigraphy map is developed This 3D map mayhelp in determining the position of hydrocarbon depositionsMoreover the increasing demand and supply of oil and gasneed industries to explore more hydrocarbons from previous50 to 80 by identifying accurate information about hydro-carbon deposition [44 45] Conventional techniques cannotprovide the correct information about the petrophysicalproperties of reservoir because the rock pores having hydro-carbon affect the physical properties of the rockwhich in turncause poor energy sensed through seismic sensors One ofthe key solutions for accurate information is passive seismicimaging technique This technique uses naturally happeningseismic signals like earth quake microtremors and oceanwaves for subsurface imaging and structuring In comparisonof conventional technique having sensing frequency in therange of 10ndash300Hz passive seismic technique monitors thelower frequency waves (below 10Hz) whichmay travel a longdistance through the earthrsquos crust without attenuation

An example of ldquoGoodrdquo event having occurrences of P-wave and S-wave at time domain is showed in Figure 13 Onthe basis of the discrete and impulsive P-wave and S-wavearrivals the event is termed ldquoGoodrdquo event [33]

Also it is shown clearly that frequency of S-wavedecreases as the frequency of P-wave increases A randomldquonoiserdquo event occurring at time domain with indeterministicproperties of ldquoGoodrdquo events is shown in Figure 14 [33]

In the area of reservoir monitoring passive seismichave applications for recording microseismic signal at nat-ural frequency for the exploration and exploitation of thehydrocarbons (ie oil and gas) [131] The study of passiveseismic at variant frequency identifies that information aboutprediction of hydrocarbon reservoir is found at low frequencyof less than 10Hz [1ndash5 132] as depicted in Table 9

12 Journal of Sensors

Table 9 Technical description of seismic data acquisition technique at low frequency

Frequency range focused Technique used Advantage Disadvantage

Modeling frequency 50ndash60Hz[25]

Spike deconvolution for lowfrequency modeling

(i) Low-cut filter is used toattenuate low frequencies

(ii) Defining technique producesbetter P-wave and S-wave seismic

section

(i) Need for recovery of broadsignal bandwidth

(ii) Poor wavelet extraction andits structure

Modeling frequency 1 KHzAcquired seismic frequency12HzReflectivity at 40Hz [26]

(i) Ultrasonic experiment(ii) Seismic data analysis

(i) Signal is reflected from a thinwater- (S

119908) or oil-saturated (S

ℎ)

layer(ii) Frequency dependent

amplitude and phase reflectionattributes have been utilized forobserving and identifying thin

liquid saturated layers

(i) Strong attenuation in the layeraffects summation of multiples

(ii) Layers with higherattenuation create travel timedelays which increase asfrequency approaches zero

Missing frequency 5ndash10Hz [27]

(i) 3D acoustic inversion(ii) Variable depth streamerseismic data acquisition(iii) 3D elastic inversioncomparison technique

(i) Variable depth streamer fordata acquisition is better for

inversion and provides missinglow frequencies directly

(ii) Left side lobe of the wavelet isproposed to reduceless

interference in the seismic signalresults in less ambiguity in

inversion

(i) There is variation in resultinginversion due to high variation in

acquisition frequency(ii) Broadband inversion may

cause obtained results outside thetarget zone

Reflection lt15HzAmplitude 40Hz [28]

(i) AVO attribute analysis(ii) VSP analysis

(i) Imaging at low frequenciesresults in robust amplitudes for

individual frequencycomponents of propagating

wavelet(ii) Frequency based seismic

imaging permits characterizingthe subsurface fluid reservoirs

(i) Quantitative analysis of AI (asfrequency) requires NMO

stretching(ii) Conventional seismic

processing software does notwork as target-oriented

processing

Based on Table 9 it is clear that the type of geophonesused in active seismic acquisition has greater size and islinearly proportional to the velocity over the resonancefrequency (about 10Hz) [25ndash28] Therefore a new design ofthe accelerometer is defined which offers a minimal signalroll-off small size and weight solution to the larger arrayslayout Also from the table it is identified that passive seismichas high potential benefits but requires special ultra noiselow frequency and short bandwidth sensing capabilitiesSince the existing device and the sensor are unable torecord at this frequency various types of sensor are studied(discussed in Section 4) Based on sensor analysis it isfound that MEMS accelerometers (capacitive) based deviceis the best replacement of existing seismological equipmentCapacitive accelerometers performed well in low bandwidthlow frequency and minimum noise Hence passive seismicexploration is an ongoing and promising research topic withthe benefit of being environmentally friendly and of low cost

31 Comparison of Technical Structure of Active andPassive Imaging

311 Active Seismic ImagingMethod In the acquisition of theactive seismic data a feedback model has been implementedwhich is based on the principal that both sources and

Pminus(z0 z0) Rcap(z0 z0)

X0(z0 z0)

120575P+(z0 z0)

S+(z0)+

X(z0 z0)

Figure 15 A feedforward model representing the upgoing anddowngoing wavefields in conventional seismic acquisition [130]

detectors are normally placed at or near the earthrsquos surfacedepicted in Figure 15 [133] It demonstrates schematically up-and downgoingwavefields happening at the reflecting surface(1199110) while the wavefields are going ldquoalongrdquo the surface being

overlookedAccordingly consider a matrix 119883

0(1199110 1199110) having a mul-

tidimensional transfer function of the subsurface (119911 gt 1199110)

Here each variable of1198830(1199110 1199110) characterized as the impulse

response of the wavefield occurred from a unit dipole sourceat 1199110and is further sensed by a unit pressure sensor at 119911

0 Also

the subscript ldquo0rdquo in 1198830symbolizes that earthrsquos surface has a

free reflection boundary that is a single round-trip (mean

Journal of Sensors 13

two-way time) has been estimated by the seismic signal fromthe subsurface (from 119911

0to 1199110) 1198830(1199110 1199110) has been utilized

as the multidimensional wavefield operator which definesthe wavefields at the reflection free acquisition surface 119911

0

119875

minus

0(1199110 1199110) as

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (25a)

or

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 120575119875

+(1199110 1199110)

+ 1198830(1199110 1199110) 119878

+

0(1199110 1199110)

(25b)

with combining

120575119875

+(1199110 1199110) = 119877

cap(1199110 1199110) 119875

minus

0(1199110 1199110) (25c)

In (25a) source matrix 119878

+

0(1199110) signifies the downgoing

wavefield of one physical source (array) at 1199110

However1198830119878

+ stands for the upgoing primary wavefields(one round-trip) and119883

0120575119875

+ stands for the upgoingmultiple-scattering wavefields (many round-trips)

Furthermore from (25a)ndash(25c) it can be simply derivedthat

1198830(1199110 1199110)

= [119868 minus 1198830(1199110 1199110) 119877

cap(1199110 1199110)]

minus1

1198830(1199110 1199110)

(26a)

representing the complexity of119883 relating to1198830 On compar-

ing (25a)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (26b)

with (25b)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) [120575119875

+(1199110 1199110) + 119878

+(1199110 1199110)] (26c)

Based on (26b) it can be concluded that the surface-related multiple-scattering phenomenon is incorporated intoa parameter 119883 However (26c) signifies that the surface-related multiple-scattering is incorporated into the downgo-ing wavefield 120575

119875

+

and the parameter 119883 determined as 1198830

Such variation between mathematical equations (26b) and(26c) assumes an imperative part in the inversion modelingfor seismic imaging [134]

Here Figure 16 represents the mixed shot record array offive sources at or near the surfaces Since during acquisitionzero time delays and large spacing between the sourcesare considered resulting incoherent shooting will becomesimultaneous shooting [136 139 140]The resultants imagingsignifies that a passive seismic recording can be measured asa naturally mixed shot record

312 Passive Seismic Imaging Method Based on DownwardRadiating Natural Sources Initially it is considered thatpseudo sources are set at or close to the surface (119911

0)

signifying that the background noise is considered as thosewavefields generated by the natural sources However in pas-sive seismic imaging response from natural sources has been

Tim

e (s)

30

25

20

15

10

05

00 1000 2000 3000 4000 5000

Lateral distance (m)

Figure 16 A mixed pseudo shot record generated by usingincoherent source array having five source elements at the surface[135 136]

considered as the seismic signal from the subsurface Thesesources might be set anyplace at the surface (119911 = 119911

0) and

in the subsurface (119911 gt 1199110) [137] Henceforth a noise model

has been createdwhichmay consider a continuing happeningseismic background noise as an indicator to determine theinformative data from these noises This concept is knownas seismic interferometry [141] Furthermore a relationshipby utilizing the wavefield diagram (see Figure 9) has beenestablished between the downgoing source wavefield at thesource level (119911

119899) and the up- and downgoing wavefields at

perception level 1199110(119911 = 119911

0) Such relation can be expressed

as

119875

+

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 119911119899)

119878

+

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110) [119882

minus1(1199110 119911119899)

119878

+

(119911119899)]

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110)

119878

+

(1199110 119911119899)

(27a)

where

119882

minus1(1199110 119911119899) = 119883

minus1

0(1199110 1199110)1198830(1199110 1199110) (27b)

Figure 17 describes the feed-forwarded model which isbased on modeling by downward radiating natural sourcesat and below the surface (119899 ge 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

313 Passive Seismic Imaging Method Based on UpwardRadiating Natural Sources In this phase like active seismicbackground noise similar type of natural sourcersquos responseis considered but the direction has been changed to the

14 Journal of Sensors

rarr(z0 zn)

W(zn z0)

Rcap(z0 z0)

rarr(zn)+X0(z0 zn)

120575rarr

(z0 zn)

n = 0 1 2 middot middot middot

Pminus

P+

S+

Figure 17 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

rarrPminus(z0 zn)

W(z0 zn)

Rcap(z0 z0)

rarrS (zn)

+ X0(zn z0)

120575rarrP (z0 zn)

n = 1 2

+

minus

Figure 18 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

contribution of ldquoupwardrdquo radiation Figure 18 depicts theresultants response which describes the correlation betweenthe upgoing source wavefields at the source level (119911

119899) and the

up- and downgoing wavefields at observation level 1199110 Such

result can be expressed as

119875

minus

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 119882(1199110 119911119899)

119878

minus

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899) +

119878

minus

(1199110 119911119899)

(28)

Figure 18 describes the feed-forwarded model which isbased on modeling by upward radiating natural sources atand below the surface (119899 gt 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

314 Statistical Description of the Modeling In the statisticalanalysis of the above designed model the above definedexpressions have been utilized on an exceptionally straight-forward medium Such medium has one horizontal reflectorand a free surface depicted in Figure 19 The stepwiseconstruction of thismedium signifies imaging in Figure 19(a)describing the conventional active seismic record where oneprimary and the surface multiples have been identified andindicated by a mathematical expression in (25b) In continu-ation Figure 19(b) describes the measurement of a responsefrom a downward radiating noise burst by implementing(27a) and (27b) while Figure 19(c) describes the upwardtransmitting patterns by estimating (28)

From these figures and equation implementation it isclearly defined that the occurrence of response and its mul-tiples takes place directly Moreover Figure 19(d) preciselydemonstrates the effect of such multiples that is the noisebursts being the summation of Figures 19(b) and 19(c)respectively

Figure 19 defines the straightforward medium whichhas one horizontal reflector and a stress-free surface HereFigure 19(a) describes the impulsive source at the surfacewhile Figure 19(b) shows at first layer the downward radiatingnoise source Similarly Figure 19(c) shows at first layerthe upward radiating noise source Finally Figure 19(d)establishes the omnidirectional noise source in the first layerof imagingOverall it has been signified that different sourcesdetermine the different resultant responses For exampleFigure 19 clearly proved this statement by demonstrating thatall sources defined here produce the different responses at ornear the subsurface of seismic imaging

32 Example Showing the Processing of Active and PassiveSeismic Imaging and Their Significance In this examplefor a mixed seismic data response inversion method fol-lowed for known and unknown sources is illustrated Herethree reflectors are utilized to measure the response forthe subsurface modeling (see Figure 20(a)) To begin withwithout considering surface-related multiples 119883

0 the mul-

tidimensional impulse response of the subsurface has beenproduced However Figures 20(b)ndash20(d) describe the three-column impulsive response of 119883

0 It results in naturally

occurring mixed recording at the subsurface Therefore inthe next modeling step surface-related multiples have beenimplemented that is from119883

0to119883

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

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[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

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[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

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[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

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[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

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[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

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[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

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[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

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[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

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[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

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[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

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[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

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[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

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[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

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[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

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[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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International Journal of

Journal of Sensors 7

A B A B

SubstrateBimorph cantilevers

Proof mass

Figure 8 Piezoresistive accelerometer showing the embodiedpiezoresistors (A B) within the cantilever [43]

implies stress changes along the embedded piezoresistiveelements (polyresistors) in the bimorph cantilever AWheat-stone bridge-like circuitry is used to measure resistancechange and deduce acceleration

For more than three decades piezoresistive accelerom-eters (eg [49 52 53 55ndash64]) have shown progressiveimprovements making them a viable option for variousapplications includingmicrogravity and low frequency appli-cations [59 63]

The demonstrated performance of these devices is shownas in Figure 8

(i) Acceleration Range Piezoresistive accelerometers havebeen designed to work in ranges as small as 1 g [55] or aslarge as 250 g [61] In average they work within 10ndash50 g [4952 53 56ndash60 62ndash64] This operation range is two orders ofmagnitude larger than desired operation range (4 ngndash80mg)(ii) Bandwidth Piezoresistive accelerometer designs [53 5558ndash63] statistically tend to have a median bandwidth of1 KHzThe uppermeasurement limit typically varies between100Hz and 2KHz whereas the lower limit is conventionallynonzero (5ndash100Hz) [46 55 59 63ndash65] except for the case ofemploying nanowires [66] that are able to respond to 0Hzacceleration (static acceleration)(iii) Noise Floor The noise floor is generally in range of 100ndash500120583gradicHz [55 56 59 63 64]

Table 3 summarizes the performance characteristics ofpiezoresistive accelerometers They are advantageously sim-ple in structure fabrication and their read-out circuitry [54]On the other hand the demonstrated performance does showcapability in neither operating in sub-g domain nor achievingbandwidth lt 50Hz or a noise floor below 5 ngradicHz Addi-tionally piezoresistive accelerometers can be seen to haveintrinsic temperature sensitivity andmeasurement drifts [62]These limitations could reduce their suitability for intendedhydrocarbonmicrotremormeasurements of current concern

222 Capacitive Capacitive accelerometers are dominantaccelerometers in market The high sensitivity good noiseperformance and low temperature sensitivity are amongtheir features [54] In principle capacitive types exploitthe change of capacitance between plates on free moving

Table 3 Piezoresistive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small sim1 g Lower limit 5ndash100 Low 100 120583

Medium 10ndash50 g BW sim1 kLarge sim250 g Upper limit 100ndash2 k High 500 120583

ElectrodeSi

Insulated layer

Si

Si

d0

d0

CA

CB

X

Proof mass

Figure 9 Capacitive sensing principle [46]

and fixed microstructures when acceleration is applied [50]Figure 9 shows a simple cantilever structure of capacitivetype accelerometer The structure consists of proof masssuspended via cantilever while the movement is sensed viaelectrodes

For quantitative analysis the performance of capacitiveaccelerometers in [19 65ndash112] is presented as follows

(i) Acceleration Range Depending on order of magnitudecapacitive accelerometers can be observed to operate in fourdifferent ranges (i) sub-g (120583g-mg) range [18 96 103] (ii) 1ndash10 g range [65ndash68 76 77 80 84ndash89 92 95ndash97 100ndash102 105](iii) 10ndash100 g range [69 72ndash74 93 99 104ndash106] and (iv) above1000 g [90 91]

(ii) Bandwidth The bandwidth of capacitive accelerometerstypically starts at DC (0Hz) [65ndash68 86 104 105] in somecases it can begin at nonzero frequencies [19 79 92]Commonly their bandwidth falls in range of 100ndash1000Hzbut it can typically vary in less than 100Hz [69] and above1000Hz [85 110]

(iii) Noise Floor The noise performance of capacitiveaccelerometers varies from 4 ngradicHz [92] up to 400mgradicHz[102] More than 60 of capacitive accelerometers have noisefloor within 120583gradicHz (ie between 01 and 100 120583gradicHz)

Capacitive accelerometers offer wide performance capa-bilities as shown in Table 4 The wide capability variationenables their successful utilization in different industrial

8 Journal of Sensors

Vz

Vx

T

T T

T

CC C C

Figure 10 Accelerometer structures using piezoelectric sensing [47]

Table 4 Capacitive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small lt1mg Small lt100 Small 4 nndash1 120583Medium 1ndash10 g Medium 100ndash1 k Medium 1 120583ndash1mLarge 10ndash100 g Large gt1 k Large gt1mVery large gt1000

domains including biomedical domain navigation spacemicrogravity military and also seismology [19 65ndash112]Remarkably the authors in [92] demonstrated noise per-formance approaching the required noise floor of HyMASapplication However the device resolution is lower than thedesired value because of the wide bandwidthTherefore a gapon achieving the required noise density and bandwidth hasstill not been met

The simple structure low drift and low temperature sen-sitivity of capacitive accelerometers along with demonstratedperformance make them suitable design option for seismicapplications [46 112]

223 Piezoelectric Piezoelectric accelerometers employmaterials with piezoelectric effects to indirectly measureacceleration via amount of deposited electric charges whenstress is induced [50] They are generally featured by lowpower consumption and temperature stability and have beenused in several applications including medical and machinevibration monitoring [47 62 113ndash117]

A typical accelerometer utilizing piezoelectric principle isillustrated in Figure 10 in which the movement of the proofmass imposes deformation on the piezoelectric elements onthe supporting bimorph beam The charge deposition alongthe sensing element induces electrical potential (119881

119909and 119881

119911)

whose magnitude indicates the acceleration appliedThe performance of accelerometers is discussed as fol-

lows

(i) Acceleration Range Piezoelectric accelerometers demon-strate a measurement range around 20ndash25 g [116] but theydo not suit sub-g operation range Additionally the inheritedhysteresis effect reduces the measurement precision that isessentially required for geophysical seismic measurement(ii) Bandwidth Piezoelectric accelerometers are normallyused in dynamic operationmode which can result in leakage

Table 5 Piezoelectric accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

and creep issues [54] The dynamic range is typically within01 kHzndash10 kHz [62 113ndash116] but can be as high as 37 kHzndash35 kHz [114] or as low as 1Hzndash60Hz [47](iii) Noise Floor It falls within the range of 10 ng to 700 ng indesigns [47 116 117] whereas the early designs suffer fromlarge noise floor reaching up to 01 g [113]

Table 5 summarizes the performance characteristics ofpiezoelectric accelerometers From presented literature theyshow substantial performance improvement in the accel-eration range bandwidth and noise level over the lastdecades This could make them viable choice of design forpassive seismic However the inherited creep and tendencyfor dynamic measurements can reduce their suitability forpassive seismic geophysical applications

224 Electron Tunneling Tunneling accelerometers exploitchanges of current tunneling through insulating mediumwith change of separating displacement [48 118ndash121] Fig-ure 11 shows an accelerometer schematic using the electrontunneling principle It is seen that the tunneling tip is justbeneath a suspended proof mass A deflection electrode andproof mass electrodes provide electrostatic force required tocontrol the tunneling current

Electron tunneling is very promising in seismic appli-cation field because of performance high sensitivity smallsize and light weight compared to piezoresistive or capacitivetypes The demonstrated measurement capabilities are statedas follows(i) Acceleration Range During the last two decades 30 grange was typically reported [119 120] Later 1mg rangewas maximally reported [48 121] which proved its sensorcapability to work in seismic operation(ii) Bandwidth Frequently accelerometers are designed towork minimally at 1 kHz bandwidth [47 113ndash122] Thisrange can reach up to 6 kHz [123ndash125] Notably tunnelingaccelerometers have a limit for the minimum detectable

Journal of Sensors 9

Table 6 Tunneling accelerometers performance range

Acceleration range (g) Bandwidth(Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

Vacuum

Proof mass

HingeProof mass electrode

Tunneling tip Deflection electrode

Figure 11 Cross sectional view of tunneling accelerometer withcantilever structure [48]

frequencyThis limit is typically in range of 5ndash200Hz [48 119121](iii) Noise Floor In early tunneling devices the noise floorvaried over a range from 1 120583gradicHz to 4mgradicHz [119 120122] As technology advances a noise floor at nanometerrange (15ndash250 ngradicHz) has been achieved [48 121] Table 6summarizes the performance characteristics of tunnelingaccelerometers in literature Tunneling accelerometers showseismic grade performance with some exception on the widebandwidth of 1 kHz Therefore further filtration process isrequired for narrow bandwidth signals

225 Resistive Accelerometers Resistive accelerometers rec-ognize the change of resistance of a metal strain gauge clungto a cantilever beam Accelerating prompts twisting of thecantilever beam and hence causes variation in the resistanceof the strain gauge In case of a metal foil the geometric effectis identified significantly dominating the piezoelectric effect[50] The model of a Wheatstone bridge circuit configuredfour strain gauges which provide a voltage signal and workfor DC estimation

226 Optical Accelerometers An optical accelerometer dis-tinguishes the change of optical characteristics in an opticalfiberTheFiber BraggGrinding (FBG) is one of themost stan-dard and popular techniques for fiber optical estimation [126127] In this technique Bragg gratings are the interferencefilter composed of optical fibers The characteristic of FBGaccelerometers defines that the appraisals reflect just a narrowspectral component of actuated light Acceleration prompts adistortion of an optical fiber connected to a suspended beamcausing a change in the reflection characteristic of the Bragggratings This change can be distinguished by contrasting thespectral component of the reflected beam with the impelledlight Hence FBG accelerometer is used to perform opticalsignal analysis with DC estimations

Table 7 Sensors performance summary

Type Bandwidth(Hz)

Acceleration(g)

Noise density(gradicHz)

Capacitive 0ndash30 22120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100 120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

227 Thermal Accelerometers Thermal accelerometer hasbeen driven based on mass displacement and does notfound a popularity among others in terms of manufacturerselling [127] Therefore the suited alternative solution of thisissue is thermal accelerometer without mass displacement[127] It consists of a heater and thermocouples situatedaround the radiator in a hermetic chamber On applyingacceleration to the accelerometer hot air in the chambermoves that leads to generating an asymmetric temperatureprofile Such asymmetric profile can be identified by thethermocouples around the radiator This process is calledtransduction principle which produces a voltage signal usingthese accelerometers and work for DC estimation [128]

23 Analysis and Design Challenges For comparative anal-ysis previously mentioned works have been summarized inTable 7 [6 7 34 43 46 62ndash64] The first column shows thesensing type of accelerometers The smallest operating band-width the upper limits of acceleration range and measurednoise floor levels are listed in columns 2ndash4 respectively Thedata summarized inTable 7 indicates the superiority of capac-itive sensors to meet passive seismic sensing requirementsAccording to Section 22 signals required in passive seismicsurvey havemaximumacceleration oflt80mg andbandwidthof 1ndash30Hz with lt1 ngradicHz noise spectral density

The key in designing high resolution capacitive acceler-ometer is to reduce the devicersquos noise floor and increase itssensitivity as demonstrated in [19 88 92 93 104 122 123]The total noise floor comes from mechanical and electricalelements of the sensor

(i) Design Overview The Brownian noise is principallyproportional to the square root of damping factor (119887) andinversely proportional to the proof mass (119898) as in (17) where119896119861and 119879 are Boltzmannrsquos constant (138 times 10minus23 JK) and the

temperature in Kelvin

119886nm =

radic4119896119861119879119887

98119898

(17)

Therefore ultralow noise accelerometers have large proofmass and low gas damping in the mass-spring accelerometersystem [19 92] The mechanical noise can be defined as afunction of the temperature damping coefficient and massWhile the temperature can be set to 20∘C or 29315∘K thedamping coefficient andmass are dependent on the geometryof the structure

10 Journal of Sensors

Sensing fingers

Springs

Driving fingers

(a)

A

A998400

Wb Wa

Lb

La

LeffLf

X0

Wf

(b)

Figure 12 Structure of a lateral capacitive accelerometer (a) isometric device view (b) spring parameters (119882119887119882119886 119871119886 119871119887) and fingers

parameters (1198830119882119891 119871119891 119871eff ) [124]

In the electrical domain the noise can be minimizedby reducing the operating bandwidth Additionally a closed-loop feedback electronic circuit is required to compensate thenonlinear response of the mechanical system and to shortenthe bandwidth of the device to 30Hz To minimize the noiseeffect from amplifier the rate of capacitance change withacceleration needs to be maximized [19] Maximizing thesensitivity requires minimizing sensing gap and lowering thenatural resonant frequency [19 92 129]

As previously discussed the minimum detectable accel-eration should be = 802

24= 47 ng This implies that

the maximum mechanical noise 119886119898

should be less than086 gradicHz according to

119886119898

=

119886minradicBW

=

47 ngradic30

= 086 gradicHz (18)

In order to size the design challenges of ultralow noisefloor a case study on accelerometer design with conventionalcomb structure is considered The structure as shown inFigure 12 comprises a fixed rectangular framewith fingers anda moving proof mass fixed on the frame by spring-like shapeat both ends and surrounded by fingers at its both sides

Accelerometers noise performance is generally deter-mined by the damping coefficient and proof mass size assuggested by (5) The dominant damping mechanism in thisstructure is due to the squeeze-film effect [125]Therefore thedamping coefficient 119887 can be written in

119887 = 72119873120583119905 (

119897eff1199090

)

3

(19)

whereby 119873 is the number of comb fingers 119905 is the proofmass thickness 120583 is the viscosity of the air under atmosphericpressure 20∘C = 154 times 10minus6 kgms and 119897eff is the engagedlength of the comb fingers

Moreover the mass 119898 can be expressed in (20) where 119898

defines the mass of the proof mass 120588 is the silicon density =2330 kgm3 119897

119891is the length of comb fingers 119882

119891is the width

of comb fingers and 119860 is the area of the proof mass

119898 = 119905120588 (119860 + 119873119897119891119882119891) (20)

As a result the mechanical noise 119886nm can be expressed bysubstituting (19) and (20) in (17) to obtain

119886nm =

radic4119896119861119879 [72119873120583119905 (119897eff1199090)

3]

98 [119905120588 (119860 + 119873119897119891119882119891)]

(21)

As depicted in Figure 12(a) the proof mass parameters119860 and 119905 typically have large values compared to fingersdimensions 119871eff 119871119891119882119891 and 119883

0[124] As a result the proof

mass is effectively increased by enlarging parameters119860 and 119905The realization of sub-ngradicHz of noise spectral density

through mass maximization has a positive impact on devicesensitivityThis can be explained by the proportional relation-ship between sensitivity and mass as displayed in

119878 =

119881119904

119886in=

4119862119904

2119862119904+ 119862119901

sdot

119881m1199090

sdot

119898

119896

(22)

whereby 119878 is the sensitivity (Vg) 119862119904is the sensing capaci-

tance 119862119901is the parasitic capacitance119881m is maximum output

voltage (V) 119886in is maximum input acceleration (g) and 119896 isthe spring constant (Nm)

The maximization of sensitivity is an important designgoal This is achievable by maximizing the proof mass andminimizing the spring constant as suggested by (22) How-ever the resonant frequency has to be considered Equations(23) and (24) describe the structural dependencies of thespring constant 119896 and the device resonant frequency 119891respectively as follows

119896 = 2

1

(119899 minus 1)

3sdot 119864 (

119882119887

2119871119887

)

3

119905 (23)

119891 =

1

2120587

sdotradic

119896

119898

(24)

where 119899 is the number of mechanical spring turns 119882119887is

the width of single turn spring 119871119887is the length of single

turn spring and 119864 is Youngrsquos Modulus of silicon = 154 times

10minus6 kgms

231 Summarized Analysis of the Type of Accelerometers Forinitial analysis (18)ndash(23) have been solved yielding to the

Journal of Sensors 11

Table 8 Initial design parameters and values

Parameter Value Parameter Value119897eff 80 120583m 119899 8119897119891

85 120583m 1199090

83 120583m119882119891

48 120583m 119905 3318 120583m119873 200 119897

1198872mm

119860 5mm times 5mm 119882119887

75 120583m119898 2120583g 119886nm 085 ngrtHz119891 46Hz 119878 026

values as listed in Table 8 The table shows the parametersand the corresponding values for the design in rows 2ndash6The resulting device performance (noise resonant frequencyand sensitivity) is shown in the last two rows The tableshows that a 5mm times 5mm proof mass area was requiredEven though the sensitivity (026Vg) is lower than state-of-the-art value this device is considered large structure forconventional CMOS technology To improve the sensitivityfurther enlargement for the proof mass is required Thisshows the major challenge of the design

Therefore achieving the noise spectral density of less than1 ngradicHz on a conventional capacitive structure is challeng-ing As a result a novel structure and design optimization isexpected to meet the stringent resolution level requirements

232 Conclusion on the Analysis The excessive demandsfor hydrocarbon have pushed the exploration technologyto the era of passive seismic monitoring The technique iseconomically promising and environmentally friendly butfacing several challenges among which is the high resolutionacquisition using state-of-the-art sensorsaccelerometers

In this paper the technological gap between themeasure-ment resolution of the state-of-the-art sensors and emergingdevices is identified for passive seismic monitoring It showsdesign possibilities using capacitive sensing techniques andmotivates further work in developing optimized sensor solu-tions

Finally a solution has been provided with specificationto design such an accelerometer To enhance the resolutionand sensitivity a dimension in the order of millimeters largerthan conventional MEMS dimensions is required Moreovertechnological issues including reducing parasitic capacitanceby increasing dielectric thickness and reducing air pressurefor less damping impact beyond 1ndash10 Torr are among theconstraints hindering prospective designs

In synopsis piezoelectric accelerometers demonstrate themost astounding estimation range shock limits and oper-ating temperature capacitive accelerometers the least powerutilization and volume and piezoresistive accelerometers thevastest frequency response

3 Sensors in Seismology

Seismic study determines that the effective exploration tech-nique for imaging the geology is active seismic imagingPreviously explosives or vibroseis trucks are utilized for

Nor

mal

ized

ampl

itude

minus1

minus05

0

05

1

0 02 04 06 08 1 12 14

Time (s)

P-wave S-wave

Figure 13 A ldquogoodrdquo occurrence of P- and S-wave arrivals in timedomain [44]

Nor

mal

ized

ampl

itude

minus1minus05

0051

0 02 04 06 08 1 12 14

Time (s)

Figure 14 A random ldquonoiserdquo event at time domain [33]

generating seismic energy sensed by the network of seismicsensors which may provide the information that determinesthe prospective oil and gas traps In view of received sensordata a 3D stratigraphy map is developed This 3D map mayhelp in determining the position of hydrocarbon depositionsMoreover the increasing demand and supply of oil and gasneed industries to explore more hydrocarbons from previous50 to 80 by identifying accurate information about hydro-carbon deposition [44 45] Conventional techniques cannotprovide the correct information about the petrophysicalproperties of reservoir because the rock pores having hydro-carbon affect the physical properties of the rockwhich in turncause poor energy sensed through seismic sensors One ofthe key solutions for accurate information is passive seismicimaging technique This technique uses naturally happeningseismic signals like earth quake microtremors and oceanwaves for subsurface imaging and structuring In comparisonof conventional technique having sensing frequency in therange of 10ndash300Hz passive seismic technique monitors thelower frequency waves (below 10Hz) whichmay travel a longdistance through the earthrsquos crust without attenuation

An example of ldquoGoodrdquo event having occurrences of P-wave and S-wave at time domain is showed in Figure 13 Onthe basis of the discrete and impulsive P-wave and S-wavearrivals the event is termed ldquoGoodrdquo event [33]

Also it is shown clearly that frequency of S-wavedecreases as the frequency of P-wave increases A randomldquonoiserdquo event occurring at time domain with indeterministicproperties of ldquoGoodrdquo events is shown in Figure 14 [33]

In the area of reservoir monitoring passive seismichave applications for recording microseismic signal at nat-ural frequency for the exploration and exploitation of thehydrocarbons (ie oil and gas) [131] The study of passiveseismic at variant frequency identifies that information aboutprediction of hydrocarbon reservoir is found at low frequencyof less than 10Hz [1ndash5 132] as depicted in Table 9

12 Journal of Sensors

Table 9 Technical description of seismic data acquisition technique at low frequency

Frequency range focused Technique used Advantage Disadvantage

Modeling frequency 50ndash60Hz[25]

Spike deconvolution for lowfrequency modeling

(i) Low-cut filter is used toattenuate low frequencies

(ii) Defining technique producesbetter P-wave and S-wave seismic

section

(i) Need for recovery of broadsignal bandwidth

(ii) Poor wavelet extraction andits structure

Modeling frequency 1 KHzAcquired seismic frequency12HzReflectivity at 40Hz [26]

(i) Ultrasonic experiment(ii) Seismic data analysis

(i) Signal is reflected from a thinwater- (S

119908) or oil-saturated (S

ℎ)

layer(ii) Frequency dependent

amplitude and phase reflectionattributes have been utilized forobserving and identifying thin

liquid saturated layers

(i) Strong attenuation in the layeraffects summation of multiples

(ii) Layers with higherattenuation create travel timedelays which increase asfrequency approaches zero

Missing frequency 5ndash10Hz [27]

(i) 3D acoustic inversion(ii) Variable depth streamerseismic data acquisition(iii) 3D elastic inversioncomparison technique

(i) Variable depth streamer fordata acquisition is better for

inversion and provides missinglow frequencies directly

(ii) Left side lobe of the wavelet isproposed to reduceless

interference in the seismic signalresults in less ambiguity in

inversion

(i) There is variation in resultinginversion due to high variation in

acquisition frequency(ii) Broadband inversion may

cause obtained results outside thetarget zone

Reflection lt15HzAmplitude 40Hz [28]

(i) AVO attribute analysis(ii) VSP analysis

(i) Imaging at low frequenciesresults in robust amplitudes for

individual frequencycomponents of propagating

wavelet(ii) Frequency based seismic

imaging permits characterizingthe subsurface fluid reservoirs

(i) Quantitative analysis of AI (asfrequency) requires NMO

stretching(ii) Conventional seismic

processing software does notwork as target-oriented

processing

Based on Table 9 it is clear that the type of geophonesused in active seismic acquisition has greater size and islinearly proportional to the velocity over the resonancefrequency (about 10Hz) [25ndash28] Therefore a new design ofthe accelerometer is defined which offers a minimal signalroll-off small size and weight solution to the larger arrayslayout Also from the table it is identified that passive seismichas high potential benefits but requires special ultra noiselow frequency and short bandwidth sensing capabilitiesSince the existing device and the sensor are unable torecord at this frequency various types of sensor are studied(discussed in Section 4) Based on sensor analysis it isfound that MEMS accelerometers (capacitive) based deviceis the best replacement of existing seismological equipmentCapacitive accelerometers performed well in low bandwidthlow frequency and minimum noise Hence passive seismicexploration is an ongoing and promising research topic withthe benefit of being environmentally friendly and of low cost

31 Comparison of Technical Structure of Active andPassive Imaging

311 Active Seismic ImagingMethod In the acquisition of theactive seismic data a feedback model has been implementedwhich is based on the principal that both sources and

Pminus(z0 z0) Rcap(z0 z0)

X0(z0 z0)

120575P+(z0 z0)

S+(z0)+

X(z0 z0)

Figure 15 A feedforward model representing the upgoing anddowngoing wavefields in conventional seismic acquisition [130]

detectors are normally placed at or near the earthrsquos surfacedepicted in Figure 15 [133] It demonstrates schematically up-and downgoingwavefields happening at the reflecting surface(1199110) while the wavefields are going ldquoalongrdquo the surface being

overlookedAccordingly consider a matrix 119883

0(1199110 1199110) having a mul-

tidimensional transfer function of the subsurface (119911 gt 1199110)

Here each variable of1198830(1199110 1199110) characterized as the impulse

response of the wavefield occurred from a unit dipole sourceat 1199110and is further sensed by a unit pressure sensor at 119911

0 Also

the subscript ldquo0rdquo in 1198830symbolizes that earthrsquos surface has a

free reflection boundary that is a single round-trip (mean

Journal of Sensors 13

two-way time) has been estimated by the seismic signal fromthe subsurface (from 119911

0to 1199110) 1198830(1199110 1199110) has been utilized

as the multidimensional wavefield operator which definesthe wavefields at the reflection free acquisition surface 119911

0

119875

minus

0(1199110 1199110) as

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (25a)

or

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 120575119875

+(1199110 1199110)

+ 1198830(1199110 1199110) 119878

+

0(1199110 1199110)

(25b)

with combining

120575119875

+(1199110 1199110) = 119877

cap(1199110 1199110) 119875

minus

0(1199110 1199110) (25c)

In (25a) source matrix 119878

+

0(1199110) signifies the downgoing

wavefield of one physical source (array) at 1199110

However1198830119878

+ stands for the upgoing primary wavefields(one round-trip) and119883

0120575119875

+ stands for the upgoingmultiple-scattering wavefields (many round-trips)

Furthermore from (25a)ndash(25c) it can be simply derivedthat

1198830(1199110 1199110)

= [119868 minus 1198830(1199110 1199110) 119877

cap(1199110 1199110)]

minus1

1198830(1199110 1199110)

(26a)

representing the complexity of119883 relating to1198830 On compar-

ing (25a)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (26b)

with (25b)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) [120575119875

+(1199110 1199110) + 119878

+(1199110 1199110)] (26c)

Based on (26b) it can be concluded that the surface-related multiple-scattering phenomenon is incorporated intoa parameter 119883 However (26c) signifies that the surface-related multiple-scattering is incorporated into the downgo-ing wavefield 120575

119875

+

and the parameter 119883 determined as 1198830

Such variation between mathematical equations (26b) and(26c) assumes an imperative part in the inversion modelingfor seismic imaging [134]

Here Figure 16 represents the mixed shot record array offive sources at or near the surfaces Since during acquisitionzero time delays and large spacing between the sourcesare considered resulting incoherent shooting will becomesimultaneous shooting [136 139 140]The resultants imagingsignifies that a passive seismic recording can be measured asa naturally mixed shot record

312 Passive Seismic Imaging Method Based on DownwardRadiating Natural Sources Initially it is considered thatpseudo sources are set at or close to the surface (119911

0)

signifying that the background noise is considered as thosewavefields generated by the natural sources However in pas-sive seismic imaging response from natural sources has been

Tim

e (s)

30

25

20

15

10

05

00 1000 2000 3000 4000 5000

Lateral distance (m)

Figure 16 A mixed pseudo shot record generated by usingincoherent source array having five source elements at the surface[135 136]

considered as the seismic signal from the subsurface Thesesources might be set anyplace at the surface (119911 = 119911

0) and

in the subsurface (119911 gt 1199110) [137] Henceforth a noise model

has been createdwhichmay consider a continuing happeningseismic background noise as an indicator to determine theinformative data from these noises This concept is knownas seismic interferometry [141] Furthermore a relationshipby utilizing the wavefield diagram (see Figure 9) has beenestablished between the downgoing source wavefield at thesource level (119911

119899) and the up- and downgoing wavefields at

perception level 1199110(119911 = 119911

0) Such relation can be expressed

as

119875

+

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 119911119899)

119878

+

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110) [119882

minus1(1199110 119911119899)

119878

+

(119911119899)]

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110)

119878

+

(1199110 119911119899)

(27a)

where

119882

minus1(1199110 119911119899) = 119883

minus1

0(1199110 1199110)1198830(1199110 1199110) (27b)

Figure 17 describes the feed-forwarded model which isbased on modeling by downward radiating natural sourcesat and below the surface (119899 ge 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

313 Passive Seismic Imaging Method Based on UpwardRadiating Natural Sources In this phase like active seismicbackground noise similar type of natural sourcersquos responseis considered but the direction has been changed to the

14 Journal of Sensors

rarr(z0 zn)

W(zn z0)

Rcap(z0 z0)

rarr(zn)+X0(z0 zn)

120575rarr

(z0 zn)

n = 0 1 2 middot middot middot

Pminus

P+

S+

Figure 17 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

rarrPminus(z0 zn)

W(z0 zn)

Rcap(z0 z0)

rarrS (zn)

+ X0(zn z0)

120575rarrP (z0 zn)

n = 1 2

+

minus

Figure 18 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

contribution of ldquoupwardrdquo radiation Figure 18 depicts theresultants response which describes the correlation betweenthe upgoing source wavefields at the source level (119911

119899) and the

up- and downgoing wavefields at observation level 1199110 Such

result can be expressed as

119875

minus

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 119882(1199110 119911119899)

119878

minus

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899) +

119878

minus

(1199110 119911119899)

(28)

Figure 18 describes the feed-forwarded model which isbased on modeling by upward radiating natural sources atand below the surface (119899 gt 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

314 Statistical Description of the Modeling In the statisticalanalysis of the above designed model the above definedexpressions have been utilized on an exceptionally straight-forward medium Such medium has one horizontal reflectorand a free surface depicted in Figure 19 The stepwiseconstruction of thismedium signifies imaging in Figure 19(a)describing the conventional active seismic record where oneprimary and the surface multiples have been identified andindicated by a mathematical expression in (25b) In continu-ation Figure 19(b) describes the measurement of a responsefrom a downward radiating noise burst by implementing(27a) and (27b) while Figure 19(c) describes the upwardtransmitting patterns by estimating (28)

From these figures and equation implementation it isclearly defined that the occurrence of response and its mul-tiples takes place directly Moreover Figure 19(d) preciselydemonstrates the effect of such multiples that is the noisebursts being the summation of Figures 19(b) and 19(c)respectively

Figure 19 defines the straightforward medium whichhas one horizontal reflector and a stress-free surface HereFigure 19(a) describes the impulsive source at the surfacewhile Figure 19(b) shows at first layer the downward radiatingnoise source Similarly Figure 19(c) shows at first layerthe upward radiating noise source Finally Figure 19(d)establishes the omnidirectional noise source in the first layerof imagingOverall it has been signified that different sourcesdetermine the different resultant responses For exampleFigure 19 clearly proved this statement by demonstrating thatall sources defined here produce the different responses at ornear the subsurface of seismic imaging

32 Example Showing the Processing of Active and PassiveSeismic Imaging and Their Significance In this examplefor a mixed seismic data response inversion method fol-lowed for known and unknown sources is illustrated Herethree reflectors are utilized to measure the response forthe subsurface modeling (see Figure 20(a)) To begin withwithout considering surface-related multiples 119883

0 the mul-

tidimensional impulse response of the subsurface has beenproduced However Figures 20(b)ndash20(d) describe the three-column impulsive response of 119883

0 It results in naturally

occurring mixed recording at the subsurface Therefore inthe next modeling step surface-related multiples have beenimplemented that is from119883

0to119883

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

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[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

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[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

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[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

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DistributedSensor Networks

International Journal of

8 Journal of Sensors

Vz

Vx

T

T T

T

CC C C

Figure 10 Accelerometer structures using piezoelectric sensing [47]

Table 4 Capacitive accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)Small lt1mg Small lt100 Small 4 nndash1 120583Medium 1ndash10 g Medium 100ndash1 k Medium 1 120583ndash1mLarge 10ndash100 g Large gt1 k Large gt1mVery large gt1000

domains including biomedical domain navigation spacemicrogravity military and also seismology [19 65ndash112]Remarkably the authors in [92] demonstrated noise per-formance approaching the required noise floor of HyMASapplication However the device resolution is lower than thedesired value because of the wide bandwidthTherefore a gapon achieving the required noise density and bandwidth hasstill not been met

The simple structure low drift and low temperature sen-sitivity of capacitive accelerometers along with demonstratedperformance make them suitable design option for seismicapplications [46 112]

223 Piezoelectric Piezoelectric accelerometers employmaterials with piezoelectric effects to indirectly measureacceleration via amount of deposited electric charges whenstress is induced [50] They are generally featured by lowpower consumption and temperature stability and have beenused in several applications including medical and machinevibration monitoring [47 62 113ndash117]

A typical accelerometer utilizing piezoelectric principle isillustrated in Figure 10 in which the movement of the proofmass imposes deformation on the piezoelectric elements onthe supporting bimorph beam The charge deposition alongthe sensing element induces electrical potential (119881

119909and 119881

119911)

whose magnitude indicates the acceleration appliedThe performance of accelerometers is discussed as fol-

lows

(i) Acceleration Range Piezoelectric accelerometers demon-strate a measurement range around 20ndash25 g [116] but theydo not suit sub-g operation range Additionally the inheritedhysteresis effect reduces the measurement precision that isessentially required for geophysical seismic measurement(ii) Bandwidth Piezoelectric accelerometers are normallyused in dynamic operationmode which can result in leakage

Table 5 Piezoelectric accelerometers performance range

Acceleration range (g) Bandwidth (Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

and creep issues [54] The dynamic range is typically within01 kHzndash10 kHz [62 113ndash116] but can be as high as 37 kHzndash35 kHz [114] or as low as 1Hzndash60Hz [47](iii) Noise Floor It falls within the range of 10 ng to 700 ng indesigns [47 116 117] whereas the early designs suffer fromlarge noise floor reaching up to 01 g [113]

Table 5 summarizes the performance characteristics ofpiezoelectric accelerometers From presented literature theyshow substantial performance improvement in the accel-eration range bandwidth and noise level over the lastdecades This could make them viable choice of design forpassive seismic However the inherited creep and tendencyfor dynamic measurements can reduce their suitability forpassive seismic geophysical applications

224 Electron Tunneling Tunneling accelerometers exploitchanges of current tunneling through insulating mediumwith change of separating displacement [48 118ndash121] Fig-ure 11 shows an accelerometer schematic using the electrontunneling principle It is seen that the tunneling tip is justbeneath a suspended proof mass A deflection electrode andproof mass electrodes provide electrostatic force required tocontrol the tunneling current

Electron tunneling is very promising in seismic appli-cation field because of performance high sensitivity smallsize and light weight compared to piezoresistive or capacitivetypes The demonstrated measurement capabilities are statedas follows(i) Acceleration Range During the last two decades 30 grange was typically reported [119 120] Later 1mg rangewas maximally reported [48 121] which proved its sensorcapability to work in seismic operation(ii) Bandwidth Frequently accelerometers are designed towork minimally at 1 kHz bandwidth [47 113ndash122] Thisrange can reach up to 6 kHz [123ndash125] Notably tunnelingaccelerometers have a limit for the minimum detectable

Journal of Sensors 9

Table 6 Tunneling accelerometers performance range

Acceleration range (g) Bandwidth(Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

Vacuum

Proof mass

HingeProof mass electrode

Tunneling tip Deflection electrode

Figure 11 Cross sectional view of tunneling accelerometer withcantilever structure [48]

frequencyThis limit is typically in range of 5ndash200Hz [48 119121](iii) Noise Floor In early tunneling devices the noise floorvaried over a range from 1 120583gradicHz to 4mgradicHz [119 120122] As technology advances a noise floor at nanometerrange (15ndash250 ngradicHz) has been achieved [48 121] Table 6summarizes the performance characteristics of tunnelingaccelerometers in literature Tunneling accelerometers showseismic grade performance with some exception on the widebandwidth of 1 kHz Therefore further filtration process isrequired for narrow bandwidth signals

225 Resistive Accelerometers Resistive accelerometers rec-ognize the change of resistance of a metal strain gauge clungto a cantilever beam Accelerating prompts twisting of thecantilever beam and hence causes variation in the resistanceof the strain gauge In case of a metal foil the geometric effectis identified significantly dominating the piezoelectric effect[50] The model of a Wheatstone bridge circuit configuredfour strain gauges which provide a voltage signal and workfor DC estimation

226 Optical Accelerometers An optical accelerometer dis-tinguishes the change of optical characteristics in an opticalfiberTheFiber BraggGrinding (FBG) is one of themost stan-dard and popular techniques for fiber optical estimation [126127] In this technique Bragg gratings are the interferencefilter composed of optical fibers The characteristic of FBGaccelerometers defines that the appraisals reflect just a narrowspectral component of actuated light Acceleration prompts adistortion of an optical fiber connected to a suspended beamcausing a change in the reflection characteristic of the Bragggratings This change can be distinguished by contrasting thespectral component of the reflected beam with the impelledlight Hence FBG accelerometer is used to perform opticalsignal analysis with DC estimations

Table 7 Sensors performance summary

Type Bandwidth(Hz)

Acceleration(g)

Noise density(gradicHz)

Capacitive 0ndash30 22120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100 120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

227 Thermal Accelerometers Thermal accelerometer hasbeen driven based on mass displacement and does notfound a popularity among others in terms of manufacturerselling [127] Therefore the suited alternative solution of thisissue is thermal accelerometer without mass displacement[127] It consists of a heater and thermocouples situatedaround the radiator in a hermetic chamber On applyingacceleration to the accelerometer hot air in the chambermoves that leads to generating an asymmetric temperatureprofile Such asymmetric profile can be identified by thethermocouples around the radiator This process is calledtransduction principle which produces a voltage signal usingthese accelerometers and work for DC estimation [128]

23 Analysis and Design Challenges For comparative anal-ysis previously mentioned works have been summarized inTable 7 [6 7 34 43 46 62ndash64] The first column shows thesensing type of accelerometers The smallest operating band-width the upper limits of acceleration range and measurednoise floor levels are listed in columns 2ndash4 respectively Thedata summarized inTable 7 indicates the superiority of capac-itive sensors to meet passive seismic sensing requirementsAccording to Section 22 signals required in passive seismicsurvey havemaximumacceleration oflt80mg andbandwidthof 1ndash30Hz with lt1 ngradicHz noise spectral density

The key in designing high resolution capacitive acceler-ometer is to reduce the devicersquos noise floor and increase itssensitivity as demonstrated in [19 88 92 93 104 122 123]The total noise floor comes from mechanical and electricalelements of the sensor

(i) Design Overview The Brownian noise is principallyproportional to the square root of damping factor (119887) andinversely proportional to the proof mass (119898) as in (17) where119896119861and 119879 are Boltzmannrsquos constant (138 times 10minus23 JK) and the

temperature in Kelvin

119886nm =

radic4119896119861119879119887

98119898

(17)

Therefore ultralow noise accelerometers have large proofmass and low gas damping in the mass-spring accelerometersystem [19 92] The mechanical noise can be defined as afunction of the temperature damping coefficient and massWhile the temperature can be set to 20∘C or 29315∘K thedamping coefficient andmass are dependent on the geometryof the structure

10 Journal of Sensors

Sensing fingers

Springs

Driving fingers

(a)

A

A998400

Wb Wa

Lb

La

LeffLf

X0

Wf

(b)

Figure 12 Structure of a lateral capacitive accelerometer (a) isometric device view (b) spring parameters (119882119887119882119886 119871119886 119871119887) and fingers

parameters (1198830119882119891 119871119891 119871eff ) [124]

In the electrical domain the noise can be minimizedby reducing the operating bandwidth Additionally a closed-loop feedback electronic circuit is required to compensate thenonlinear response of the mechanical system and to shortenthe bandwidth of the device to 30Hz To minimize the noiseeffect from amplifier the rate of capacitance change withacceleration needs to be maximized [19] Maximizing thesensitivity requires minimizing sensing gap and lowering thenatural resonant frequency [19 92 129]

As previously discussed the minimum detectable accel-eration should be = 802

24= 47 ng This implies that

the maximum mechanical noise 119886119898

should be less than086 gradicHz according to

119886119898

=

119886minradicBW

=

47 ngradic30

= 086 gradicHz (18)

In order to size the design challenges of ultralow noisefloor a case study on accelerometer design with conventionalcomb structure is considered The structure as shown inFigure 12 comprises a fixed rectangular framewith fingers anda moving proof mass fixed on the frame by spring-like shapeat both ends and surrounded by fingers at its both sides

Accelerometers noise performance is generally deter-mined by the damping coefficient and proof mass size assuggested by (5) The dominant damping mechanism in thisstructure is due to the squeeze-film effect [125]Therefore thedamping coefficient 119887 can be written in

119887 = 72119873120583119905 (

119897eff1199090

)

3

(19)

whereby 119873 is the number of comb fingers 119905 is the proofmass thickness 120583 is the viscosity of the air under atmosphericpressure 20∘C = 154 times 10minus6 kgms and 119897eff is the engagedlength of the comb fingers

Moreover the mass 119898 can be expressed in (20) where 119898

defines the mass of the proof mass 120588 is the silicon density =2330 kgm3 119897

119891is the length of comb fingers 119882

119891is the width

of comb fingers and 119860 is the area of the proof mass

119898 = 119905120588 (119860 + 119873119897119891119882119891) (20)

As a result the mechanical noise 119886nm can be expressed bysubstituting (19) and (20) in (17) to obtain

119886nm =

radic4119896119861119879 [72119873120583119905 (119897eff1199090)

3]

98 [119905120588 (119860 + 119873119897119891119882119891)]

(21)

As depicted in Figure 12(a) the proof mass parameters119860 and 119905 typically have large values compared to fingersdimensions 119871eff 119871119891119882119891 and 119883

0[124] As a result the proof

mass is effectively increased by enlarging parameters119860 and 119905The realization of sub-ngradicHz of noise spectral density

through mass maximization has a positive impact on devicesensitivityThis can be explained by the proportional relation-ship between sensitivity and mass as displayed in

119878 =

119881119904

119886in=

4119862119904

2119862119904+ 119862119901

sdot

119881m1199090

sdot

119898

119896

(22)

whereby 119878 is the sensitivity (Vg) 119862119904is the sensing capaci-

tance 119862119901is the parasitic capacitance119881m is maximum output

voltage (V) 119886in is maximum input acceleration (g) and 119896 isthe spring constant (Nm)

The maximization of sensitivity is an important designgoal This is achievable by maximizing the proof mass andminimizing the spring constant as suggested by (22) How-ever the resonant frequency has to be considered Equations(23) and (24) describe the structural dependencies of thespring constant 119896 and the device resonant frequency 119891respectively as follows

119896 = 2

1

(119899 minus 1)

3sdot 119864 (

119882119887

2119871119887

)

3

119905 (23)

119891 =

1

2120587

sdotradic

119896

119898

(24)

where 119899 is the number of mechanical spring turns 119882119887is

the width of single turn spring 119871119887is the length of single

turn spring and 119864 is Youngrsquos Modulus of silicon = 154 times

10minus6 kgms

231 Summarized Analysis of the Type of Accelerometers Forinitial analysis (18)ndash(23) have been solved yielding to the

Journal of Sensors 11

Table 8 Initial design parameters and values

Parameter Value Parameter Value119897eff 80 120583m 119899 8119897119891

85 120583m 1199090

83 120583m119882119891

48 120583m 119905 3318 120583m119873 200 119897

1198872mm

119860 5mm times 5mm 119882119887

75 120583m119898 2120583g 119886nm 085 ngrtHz119891 46Hz 119878 026

values as listed in Table 8 The table shows the parametersand the corresponding values for the design in rows 2ndash6The resulting device performance (noise resonant frequencyand sensitivity) is shown in the last two rows The tableshows that a 5mm times 5mm proof mass area was requiredEven though the sensitivity (026Vg) is lower than state-of-the-art value this device is considered large structure forconventional CMOS technology To improve the sensitivityfurther enlargement for the proof mass is required Thisshows the major challenge of the design

Therefore achieving the noise spectral density of less than1 ngradicHz on a conventional capacitive structure is challeng-ing As a result a novel structure and design optimization isexpected to meet the stringent resolution level requirements

232 Conclusion on the Analysis The excessive demandsfor hydrocarbon have pushed the exploration technologyto the era of passive seismic monitoring The technique iseconomically promising and environmentally friendly butfacing several challenges among which is the high resolutionacquisition using state-of-the-art sensorsaccelerometers

In this paper the technological gap between themeasure-ment resolution of the state-of-the-art sensors and emergingdevices is identified for passive seismic monitoring It showsdesign possibilities using capacitive sensing techniques andmotivates further work in developing optimized sensor solu-tions

Finally a solution has been provided with specificationto design such an accelerometer To enhance the resolutionand sensitivity a dimension in the order of millimeters largerthan conventional MEMS dimensions is required Moreovertechnological issues including reducing parasitic capacitanceby increasing dielectric thickness and reducing air pressurefor less damping impact beyond 1ndash10 Torr are among theconstraints hindering prospective designs

In synopsis piezoelectric accelerometers demonstrate themost astounding estimation range shock limits and oper-ating temperature capacitive accelerometers the least powerutilization and volume and piezoresistive accelerometers thevastest frequency response

3 Sensors in Seismology

Seismic study determines that the effective exploration tech-nique for imaging the geology is active seismic imagingPreviously explosives or vibroseis trucks are utilized for

Nor

mal

ized

ampl

itude

minus1

minus05

0

05

1

0 02 04 06 08 1 12 14

Time (s)

P-wave S-wave

Figure 13 A ldquogoodrdquo occurrence of P- and S-wave arrivals in timedomain [44]

Nor

mal

ized

ampl

itude

minus1minus05

0051

0 02 04 06 08 1 12 14

Time (s)

Figure 14 A random ldquonoiserdquo event at time domain [33]

generating seismic energy sensed by the network of seismicsensors which may provide the information that determinesthe prospective oil and gas traps In view of received sensordata a 3D stratigraphy map is developed This 3D map mayhelp in determining the position of hydrocarbon depositionsMoreover the increasing demand and supply of oil and gasneed industries to explore more hydrocarbons from previous50 to 80 by identifying accurate information about hydro-carbon deposition [44 45] Conventional techniques cannotprovide the correct information about the petrophysicalproperties of reservoir because the rock pores having hydro-carbon affect the physical properties of the rockwhich in turncause poor energy sensed through seismic sensors One ofthe key solutions for accurate information is passive seismicimaging technique This technique uses naturally happeningseismic signals like earth quake microtremors and oceanwaves for subsurface imaging and structuring In comparisonof conventional technique having sensing frequency in therange of 10ndash300Hz passive seismic technique monitors thelower frequency waves (below 10Hz) whichmay travel a longdistance through the earthrsquos crust without attenuation

An example of ldquoGoodrdquo event having occurrences of P-wave and S-wave at time domain is showed in Figure 13 Onthe basis of the discrete and impulsive P-wave and S-wavearrivals the event is termed ldquoGoodrdquo event [33]

Also it is shown clearly that frequency of S-wavedecreases as the frequency of P-wave increases A randomldquonoiserdquo event occurring at time domain with indeterministicproperties of ldquoGoodrdquo events is shown in Figure 14 [33]

In the area of reservoir monitoring passive seismichave applications for recording microseismic signal at nat-ural frequency for the exploration and exploitation of thehydrocarbons (ie oil and gas) [131] The study of passiveseismic at variant frequency identifies that information aboutprediction of hydrocarbon reservoir is found at low frequencyof less than 10Hz [1ndash5 132] as depicted in Table 9

12 Journal of Sensors

Table 9 Technical description of seismic data acquisition technique at low frequency

Frequency range focused Technique used Advantage Disadvantage

Modeling frequency 50ndash60Hz[25]

Spike deconvolution for lowfrequency modeling

(i) Low-cut filter is used toattenuate low frequencies

(ii) Defining technique producesbetter P-wave and S-wave seismic

section

(i) Need for recovery of broadsignal bandwidth

(ii) Poor wavelet extraction andits structure

Modeling frequency 1 KHzAcquired seismic frequency12HzReflectivity at 40Hz [26]

(i) Ultrasonic experiment(ii) Seismic data analysis

(i) Signal is reflected from a thinwater- (S

119908) or oil-saturated (S

ℎ)

layer(ii) Frequency dependent

amplitude and phase reflectionattributes have been utilized forobserving and identifying thin

liquid saturated layers

(i) Strong attenuation in the layeraffects summation of multiples

(ii) Layers with higherattenuation create travel timedelays which increase asfrequency approaches zero

Missing frequency 5ndash10Hz [27]

(i) 3D acoustic inversion(ii) Variable depth streamerseismic data acquisition(iii) 3D elastic inversioncomparison technique

(i) Variable depth streamer fordata acquisition is better for

inversion and provides missinglow frequencies directly

(ii) Left side lobe of the wavelet isproposed to reduceless

interference in the seismic signalresults in less ambiguity in

inversion

(i) There is variation in resultinginversion due to high variation in

acquisition frequency(ii) Broadband inversion may

cause obtained results outside thetarget zone

Reflection lt15HzAmplitude 40Hz [28]

(i) AVO attribute analysis(ii) VSP analysis

(i) Imaging at low frequenciesresults in robust amplitudes for

individual frequencycomponents of propagating

wavelet(ii) Frequency based seismic

imaging permits characterizingthe subsurface fluid reservoirs

(i) Quantitative analysis of AI (asfrequency) requires NMO

stretching(ii) Conventional seismic

processing software does notwork as target-oriented

processing

Based on Table 9 it is clear that the type of geophonesused in active seismic acquisition has greater size and islinearly proportional to the velocity over the resonancefrequency (about 10Hz) [25ndash28] Therefore a new design ofthe accelerometer is defined which offers a minimal signalroll-off small size and weight solution to the larger arrayslayout Also from the table it is identified that passive seismichas high potential benefits but requires special ultra noiselow frequency and short bandwidth sensing capabilitiesSince the existing device and the sensor are unable torecord at this frequency various types of sensor are studied(discussed in Section 4) Based on sensor analysis it isfound that MEMS accelerometers (capacitive) based deviceis the best replacement of existing seismological equipmentCapacitive accelerometers performed well in low bandwidthlow frequency and minimum noise Hence passive seismicexploration is an ongoing and promising research topic withthe benefit of being environmentally friendly and of low cost

31 Comparison of Technical Structure of Active andPassive Imaging

311 Active Seismic ImagingMethod In the acquisition of theactive seismic data a feedback model has been implementedwhich is based on the principal that both sources and

Pminus(z0 z0) Rcap(z0 z0)

X0(z0 z0)

120575P+(z0 z0)

S+(z0)+

X(z0 z0)

Figure 15 A feedforward model representing the upgoing anddowngoing wavefields in conventional seismic acquisition [130]

detectors are normally placed at or near the earthrsquos surfacedepicted in Figure 15 [133] It demonstrates schematically up-and downgoingwavefields happening at the reflecting surface(1199110) while the wavefields are going ldquoalongrdquo the surface being

overlookedAccordingly consider a matrix 119883

0(1199110 1199110) having a mul-

tidimensional transfer function of the subsurface (119911 gt 1199110)

Here each variable of1198830(1199110 1199110) characterized as the impulse

response of the wavefield occurred from a unit dipole sourceat 1199110and is further sensed by a unit pressure sensor at 119911

0 Also

the subscript ldquo0rdquo in 1198830symbolizes that earthrsquos surface has a

free reflection boundary that is a single round-trip (mean

Journal of Sensors 13

two-way time) has been estimated by the seismic signal fromthe subsurface (from 119911

0to 1199110) 1198830(1199110 1199110) has been utilized

as the multidimensional wavefield operator which definesthe wavefields at the reflection free acquisition surface 119911

0

119875

minus

0(1199110 1199110) as

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (25a)

or

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 120575119875

+(1199110 1199110)

+ 1198830(1199110 1199110) 119878

+

0(1199110 1199110)

(25b)

with combining

120575119875

+(1199110 1199110) = 119877

cap(1199110 1199110) 119875

minus

0(1199110 1199110) (25c)

In (25a) source matrix 119878

+

0(1199110) signifies the downgoing

wavefield of one physical source (array) at 1199110

However1198830119878

+ stands for the upgoing primary wavefields(one round-trip) and119883

0120575119875

+ stands for the upgoingmultiple-scattering wavefields (many round-trips)

Furthermore from (25a)ndash(25c) it can be simply derivedthat

1198830(1199110 1199110)

= [119868 minus 1198830(1199110 1199110) 119877

cap(1199110 1199110)]

minus1

1198830(1199110 1199110)

(26a)

representing the complexity of119883 relating to1198830 On compar-

ing (25a)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (26b)

with (25b)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) [120575119875

+(1199110 1199110) + 119878

+(1199110 1199110)] (26c)

Based on (26b) it can be concluded that the surface-related multiple-scattering phenomenon is incorporated intoa parameter 119883 However (26c) signifies that the surface-related multiple-scattering is incorporated into the downgo-ing wavefield 120575

119875

+

and the parameter 119883 determined as 1198830

Such variation between mathematical equations (26b) and(26c) assumes an imperative part in the inversion modelingfor seismic imaging [134]

Here Figure 16 represents the mixed shot record array offive sources at or near the surfaces Since during acquisitionzero time delays and large spacing between the sourcesare considered resulting incoherent shooting will becomesimultaneous shooting [136 139 140]The resultants imagingsignifies that a passive seismic recording can be measured asa naturally mixed shot record

312 Passive Seismic Imaging Method Based on DownwardRadiating Natural Sources Initially it is considered thatpseudo sources are set at or close to the surface (119911

0)

signifying that the background noise is considered as thosewavefields generated by the natural sources However in pas-sive seismic imaging response from natural sources has been

Tim

e (s)

30

25

20

15

10

05

00 1000 2000 3000 4000 5000

Lateral distance (m)

Figure 16 A mixed pseudo shot record generated by usingincoherent source array having five source elements at the surface[135 136]

considered as the seismic signal from the subsurface Thesesources might be set anyplace at the surface (119911 = 119911

0) and

in the subsurface (119911 gt 1199110) [137] Henceforth a noise model

has been createdwhichmay consider a continuing happeningseismic background noise as an indicator to determine theinformative data from these noises This concept is knownas seismic interferometry [141] Furthermore a relationshipby utilizing the wavefield diagram (see Figure 9) has beenestablished between the downgoing source wavefield at thesource level (119911

119899) and the up- and downgoing wavefields at

perception level 1199110(119911 = 119911

0) Such relation can be expressed

as

119875

+

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 119911119899)

119878

+

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110) [119882

minus1(1199110 119911119899)

119878

+

(119911119899)]

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110)

119878

+

(1199110 119911119899)

(27a)

where

119882

minus1(1199110 119911119899) = 119883

minus1

0(1199110 1199110)1198830(1199110 1199110) (27b)

Figure 17 describes the feed-forwarded model which isbased on modeling by downward radiating natural sourcesat and below the surface (119899 ge 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

313 Passive Seismic Imaging Method Based on UpwardRadiating Natural Sources In this phase like active seismicbackground noise similar type of natural sourcersquos responseis considered but the direction has been changed to the

14 Journal of Sensors

rarr(z0 zn)

W(zn z0)

Rcap(z0 z0)

rarr(zn)+X0(z0 zn)

120575rarr

(z0 zn)

n = 0 1 2 middot middot middot

Pminus

P+

S+

Figure 17 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

rarrPminus(z0 zn)

W(z0 zn)

Rcap(z0 z0)

rarrS (zn)

+ X0(zn z0)

120575rarrP (z0 zn)

n = 1 2

+

minus

Figure 18 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

contribution of ldquoupwardrdquo radiation Figure 18 depicts theresultants response which describes the correlation betweenthe upgoing source wavefields at the source level (119911

119899) and the

up- and downgoing wavefields at observation level 1199110 Such

result can be expressed as

119875

minus

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 119882(1199110 119911119899)

119878

minus

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899) +

119878

minus

(1199110 119911119899)

(28)

Figure 18 describes the feed-forwarded model which isbased on modeling by upward radiating natural sources atand below the surface (119899 gt 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

314 Statistical Description of the Modeling In the statisticalanalysis of the above designed model the above definedexpressions have been utilized on an exceptionally straight-forward medium Such medium has one horizontal reflectorand a free surface depicted in Figure 19 The stepwiseconstruction of thismedium signifies imaging in Figure 19(a)describing the conventional active seismic record where oneprimary and the surface multiples have been identified andindicated by a mathematical expression in (25b) In continu-ation Figure 19(b) describes the measurement of a responsefrom a downward radiating noise burst by implementing(27a) and (27b) while Figure 19(c) describes the upwardtransmitting patterns by estimating (28)

From these figures and equation implementation it isclearly defined that the occurrence of response and its mul-tiples takes place directly Moreover Figure 19(d) preciselydemonstrates the effect of such multiples that is the noisebursts being the summation of Figures 19(b) and 19(c)respectively

Figure 19 defines the straightforward medium whichhas one horizontal reflector and a stress-free surface HereFigure 19(a) describes the impulsive source at the surfacewhile Figure 19(b) shows at first layer the downward radiatingnoise source Similarly Figure 19(c) shows at first layerthe upward radiating noise source Finally Figure 19(d)establishes the omnidirectional noise source in the first layerof imagingOverall it has been signified that different sourcesdetermine the different resultant responses For exampleFigure 19 clearly proved this statement by demonstrating thatall sources defined here produce the different responses at ornear the subsurface of seismic imaging

32 Example Showing the Processing of Active and PassiveSeismic Imaging and Their Significance In this examplefor a mixed seismic data response inversion method fol-lowed for known and unknown sources is illustrated Herethree reflectors are utilized to measure the response forthe subsurface modeling (see Figure 20(a)) To begin withwithout considering surface-related multiples 119883

0 the mul-

tidimensional impulse response of the subsurface has beenproduced However Figures 20(b)ndash20(d) describe the three-column impulsive response of 119883

0 It results in naturally

occurring mixed recording at the subsurface Therefore inthe next modeling step surface-related multiples have beenimplemented that is from119883

0to119883

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

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[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

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[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Submit your manuscripts athttpwwwhindawicom

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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DistributedSensor Networks

International Journal of

Journal of Sensors 9

Table 6 Tunneling accelerometers performance range

Acceleration range (g) Bandwidth(Hz) Noise density (gradicHz)

Low 20 Small 1ndash60 Low 10 nndash700 nMedium 100ndash10 k

High 25 Large 37 kndash35 k High 01

Vacuum

Proof mass

HingeProof mass electrode

Tunneling tip Deflection electrode

Figure 11 Cross sectional view of tunneling accelerometer withcantilever structure [48]

frequencyThis limit is typically in range of 5ndash200Hz [48 119121](iii) Noise Floor In early tunneling devices the noise floorvaried over a range from 1 120583gradicHz to 4mgradicHz [119 120122] As technology advances a noise floor at nanometerrange (15ndash250 ngradicHz) has been achieved [48 121] Table 6summarizes the performance characteristics of tunnelingaccelerometers in literature Tunneling accelerometers showseismic grade performance with some exception on the widebandwidth of 1 kHz Therefore further filtration process isrequired for narrow bandwidth signals

225 Resistive Accelerometers Resistive accelerometers rec-ognize the change of resistance of a metal strain gauge clungto a cantilever beam Accelerating prompts twisting of thecantilever beam and hence causes variation in the resistanceof the strain gauge In case of a metal foil the geometric effectis identified significantly dominating the piezoelectric effect[50] The model of a Wheatstone bridge circuit configuredfour strain gauges which provide a voltage signal and workfor DC estimation

226 Optical Accelerometers An optical accelerometer dis-tinguishes the change of optical characteristics in an opticalfiberTheFiber BraggGrinding (FBG) is one of themost stan-dard and popular techniques for fiber optical estimation [126127] In this technique Bragg gratings are the interferencefilter composed of optical fibers The characteristic of FBGaccelerometers defines that the appraisals reflect just a narrowspectral component of actuated light Acceleration prompts adistortion of an optical fiber connected to a suspended beamcausing a change in the reflection characteristic of the Bragggratings This change can be distinguished by contrasting thespectral component of the reflected beam with the impelledlight Hence FBG accelerometer is used to perform opticalsignal analysis with DC estimations

Table 7 Sensors performance summary

Type Bandwidth(Hz)

Acceleration(g)

Noise density(gradicHz)

Capacitive 0ndash30 22120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100 120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

227 Thermal Accelerometers Thermal accelerometer hasbeen driven based on mass displacement and does notfound a popularity among others in terms of manufacturerselling [127] Therefore the suited alternative solution of thisissue is thermal accelerometer without mass displacement[127] It consists of a heater and thermocouples situatedaround the radiator in a hermetic chamber On applyingacceleration to the accelerometer hot air in the chambermoves that leads to generating an asymmetric temperatureprofile Such asymmetric profile can be identified by thethermocouples around the radiator This process is calledtransduction principle which produces a voltage signal usingthese accelerometers and work for DC estimation [128]

23 Analysis and Design Challenges For comparative anal-ysis previously mentioned works have been summarized inTable 7 [6 7 34 43 46 62ndash64] The first column shows thesensing type of accelerometers The smallest operating band-width the upper limits of acceleration range and measurednoise floor levels are listed in columns 2ndash4 respectively Thedata summarized inTable 7 indicates the superiority of capac-itive sensors to meet passive seismic sensing requirementsAccording to Section 22 signals required in passive seismicsurvey havemaximumacceleration oflt80mg andbandwidthof 1ndash30Hz with lt1 ngradicHz noise spectral density

The key in designing high resolution capacitive acceler-ometer is to reduce the devicersquos noise floor and increase itssensitivity as demonstrated in [19 88 92 93 104 122 123]The total noise floor comes from mechanical and electricalelements of the sensor

(i) Design Overview The Brownian noise is principallyproportional to the square root of damping factor (119887) andinversely proportional to the proof mass (119898) as in (17) where119896119861and 119879 are Boltzmannrsquos constant (138 times 10minus23 JK) and the

temperature in Kelvin

119886nm =

radic4119896119861119879119887

98119898

(17)

Therefore ultralow noise accelerometers have large proofmass and low gas damping in the mass-spring accelerometersystem [19 92] The mechanical noise can be defined as afunction of the temperature damping coefficient and massWhile the temperature can be set to 20∘C or 29315∘K thedamping coefficient andmass are dependent on the geometryof the structure

10 Journal of Sensors

Sensing fingers

Springs

Driving fingers

(a)

A

A998400

Wb Wa

Lb

La

LeffLf

X0

Wf

(b)

Figure 12 Structure of a lateral capacitive accelerometer (a) isometric device view (b) spring parameters (119882119887119882119886 119871119886 119871119887) and fingers

parameters (1198830119882119891 119871119891 119871eff ) [124]

In the electrical domain the noise can be minimizedby reducing the operating bandwidth Additionally a closed-loop feedback electronic circuit is required to compensate thenonlinear response of the mechanical system and to shortenthe bandwidth of the device to 30Hz To minimize the noiseeffect from amplifier the rate of capacitance change withacceleration needs to be maximized [19] Maximizing thesensitivity requires minimizing sensing gap and lowering thenatural resonant frequency [19 92 129]

As previously discussed the minimum detectable accel-eration should be = 802

24= 47 ng This implies that

the maximum mechanical noise 119886119898

should be less than086 gradicHz according to

119886119898

=

119886minradicBW

=

47 ngradic30

= 086 gradicHz (18)

In order to size the design challenges of ultralow noisefloor a case study on accelerometer design with conventionalcomb structure is considered The structure as shown inFigure 12 comprises a fixed rectangular framewith fingers anda moving proof mass fixed on the frame by spring-like shapeat both ends and surrounded by fingers at its both sides

Accelerometers noise performance is generally deter-mined by the damping coefficient and proof mass size assuggested by (5) The dominant damping mechanism in thisstructure is due to the squeeze-film effect [125]Therefore thedamping coefficient 119887 can be written in

119887 = 72119873120583119905 (

119897eff1199090

)

3

(19)

whereby 119873 is the number of comb fingers 119905 is the proofmass thickness 120583 is the viscosity of the air under atmosphericpressure 20∘C = 154 times 10minus6 kgms and 119897eff is the engagedlength of the comb fingers

Moreover the mass 119898 can be expressed in (20) where 119898

defines the mass of the proof mass 120588 is the silicon density =2330 kgm3 119897

119891is the length of comb fingers 119882

119891is the width

of comb fingers and 119860 is the area of the proof mass

119898 = 119905120588 (119860 + 119873119897119891119882119891) (20)

As a result the mechanical noise 119886nm can be expressed bysubstituting (19) and (20) in (17) to obtain

119886nm =

radic4119896119861119879 [72119873120583119905 (119897eff1199090)

3]

98 [119905120588 (119860 + 119873119897119891119882119891)]

(21)

As depicted in Figure 12(a) the proof mass parameters119860 and 119905 typically have large values compared to fingersdimensions 119871eff 119871119891119882119891 and 119883

0[124] As a result the proof

mass is effectively increased by enlarging parameters119860 and 119905The realization of sub-ngradicHz of noise spectral density

through mass maximization has a positive impact on devicesensitivityThis can be explained by the proportional relation-ship between sensitivity and mass as displayed in

119878 =

119881119904

119886in=

4119862119904

2119862119904+ 119862119901

sdot

119881m1199090

sdot

119898

119896

(22)

whereby 119878 is the sensitivity (Vg) 119862119904is the sensing capaci-

tance 119862119901is the parasitic capacitance119881m is maximum output

voltage (V) 119886in is maximum input acceleration (g) and 119896 isthe spring constant (Nm)

The maximization of sensitivity is an important designgoal This is achievable by maximizing the proof mass andminimizing the spring constant as suggested by (22) How-ever the resonant frequency has to be considered Equations(23) and (24) describe the structural dependencies of thespring constant 119896 and the device resonant frequency 119891respectively as follows

119896 = 2

1

(119899 minus 1)

3sdot 119864 (

119882119887

2119871119887

)

3

119905 (23)

119891 =

1

2120587

sdotradic

119896

119898

(24)

where 119899 is the number of mechanical spring turns 119882119887is

the width of single turn spring 119871119887is the length of single

turn spring and 119864 is Youngrsquos Modulus of silicon = 154 times

10minus6 kgms

231 Summarized Analysis of the Type of Accelerometers Forinitial analysis (18)ndash(23) have been solved yielding to the

Journal of Sensors 11

Table 8 Initial design parameters and values

Parameter Value Parameter Value119897eff 80 120583m 119899 8119897119891

85 120583m 1199090

83 120583m119882119891

48 120583m 119905 3318 120583m119873 200 119897

1198872mm

119860 5mm times 5mm 119882119887

75 120583m119898 2120583g 119886nm 085 ngrtHz119891 46Hz 119878 026

values as listed in Table 8 The table shows the parametersand the corresponding values for the design in rows 2ndash6The resulting device performance (noise resonant frequencyand sensitivity) is shown in the last two rows The tableshows that a 5mm times 5mm proof mass area was requiredEven though the sensitivity (026Vg) is lower than state-of-the-art value this device is considered large structure forconventional CMOS technology To improve the sensitivityfurther enlargement for the proof mass is required Thisshows the major challenge of the design

Therefore achieving the noise spectral density of less than1 ngradicHz on a conventional capacitive structure is challeng-ing As a result a novel structure and design optimization isexpected to meet the stringent resolution level requirements

232 Conclusion on the Analysis The excessive demandsfor hydrocarbon have pushed the exploration technologyto the era of passive seismic monitoring The technique iseconomically promising and environmentally friendly butfacing several challenges among which is the high resolutionacquisition using state-of-the-art sensorsaccelerometers

In this paper the technological gap between themeasure-ment resolution of the state-of-the-art sensors and emergingdevices is identified for passive seismic monitoring It showsdesign possibilities using capacitive sensing techniques andmotivates further work in developing optimized sensor solu-tions

Finally a solution has been provided with specificationto design such an accelerometer To enhance the resolutionand sensitivity a dimension in the order of millimeters largerthan conventional MEMS dimensions is required Moreovertechnological issues including reducing parasitic capacitanceby increasing dielectric thickness and reducing air pressurefor less damping impact beyond 1ndash10 Torr are among theconstraints hindering prospective designs

In synopsis piezoelectric accelerometers demonstrate themost astounding estimation range shock limits and oper-ating temperature capacitive accelerometers the least powerutilization and volume and piezoresistive accelerometers thevastest frequency response

3 Sensors in Seismology

Seismic study determines that the effective exploration tech-nique for imaging the geology is active seismic imagingPreviously explosives or vibroseis trucks are utilized for

Nor

mal

ized

ampl

itude

minus1

minus05

0

05

1

0 02 04 06 08 1 12 14

Time (s)

P-wave S-wave

Figure 13 A ldquogoodrdquo occurrence of P- and S-wave arrivals in timedomain [44]

Nor

mal

ized

ampl

itude

minus1minus05

0051

0 02 04 06 08 1 12 14

Time (s)

Figure 14 A random ldquonoiserdquo event at time domain [33]

generating seismic energy sensed by the network of seismicsensors which may provide the information that determinesthe prospective oil and gas traps In view of received sensordata a 3D stratigraphy map is developed This 3D map mayhelp in determining the position of hydrocarbon depositionsMoreover the increasing demand and supply of oil and gasneed industries to explore more hydrocarbons from previous50 to 80 by identifying accurate information about hydro-carbon deposition [44 45] Conventional techniques cannotprovide the correct information about the petrophysicalproperties of reservoir because the rock pores having hydro-carbon affect the physical properties of the rockwhich in turncause poor energy sensed through seismic sensors One ofthe key solutions for accurate information is passive seismicimaging technique This technique uses naturally happeningseismic signals like earth quake microtremors and oceanwaves for subsurface imaging and structuring In comparisonof conventional technique having sensing frequency in therange of 10ndash300Hz passive seismic technique monitors thelower frequency waves (below 10Hz) whichmay travel a longdistance through the earthrsquos crust without attenuation

An example of ldquoGoodrdquo event having occurrences of P-wave and S-wave at time domain is showed in Figure 13 Onthe basis of the discrete and impulsive P-wave and S-wavearrivals the event is termed ldquoGoodrdquo event [33]

Also it is shown clearly that frequency of S-wavedecreases as the frequency of P-wave increases A randomldquonoiserdquo event occurring at time domain with indeterministicproperties of ldquoGoodrdquo events is shown in Figure 14 [33]

In the area of reservoir monitoring passive seismichave applications for recording microseismic signal at nat-ural frequency for the exploration and exploitation of thehydrocarbons (ie oil and gas) [131] The study of passiveseismic at variant frequency identifies that information aboutprediction of hydrocarbon reservoir is found at low frequencyof less than 10Hz [1ndash5 132] as depicted in Table 9

12 Journal of Sensors

Table 9 Technical description of seismic data acquisition technique at low frequency

Frequency range focused Technique used Advantage Disadvantage

Modeling frequency 50ndash60Hz[25]

Spike deconvolution for lowfrequency modeling

(i) Low-cut filter is used toattenuate low frequencies

(ii) Defining technique producesbetter P-wave and S-wave seismic

section

(i) Need for recovery of broadsignal bandwidth

(ii) Poor wavelet extraction andits structure

Modeling frequency 1 KHzAcquired seismic frequency12HzReflectivity at 40Hz [26]

(i) Ultrasonic experiment(ii) Seismic data analysis

(i) Signal is reflected from a thinwater- (S

119908) or oil-saturated (S

ℎ)

layer(ii) Frequency dependent

amplitude and phase reflectionattributes have been utilized forobserving and identifying thin

liquid saturated layers

(i) Strong attenuation in the layeraffects summation of multiples

(ii) Layers with higherattenuation create travel timedelays which increase asfrequency approaches zero

Missing frequency 5ndash10Hz [27]

(i) 3D acoustic inversion(ii) Variable depth streamerseismic data acquisition(iii) 3D elastic inversioncomparison technique

(i) Variable depth streamer fordata acquisition is better for

inversion and provides missinglow frequencies directly

(ii) Left side lobe of the wavelet isproposed to reduceless

interference in the seismic signalresults in less ambiguity in

inversion

(i) There is variation in resultinginversion due to high variation in

acquisition frequency(ii) Broadband inversion may

cause obtained results outside thetarget zone

Reflection lt15HzAmplitude 40Hz [28]

(i) AVO attribute analysis(ii) VSP analysis

(i) Imaging at low frequenciesresults in robust amplitudes for

individual frequencycomponents of propagating

wavelet(ii) Frequency based seismic

imaging permits characterizingthe subsurface fluid reservoirs

(i) Quantitative analysis of AI (asfrequency) requires NMO

stretching(ii) Conventional seismic

processing software does notwork as target-oriented

processing

Based on Table 9 it is clear that the type of geophonesused in active seismic acquisition has greater size and islinearly proportional to the velocity over the resonancefrequency (about 10Hz) [25ndash28] Therefore a new design ofthe accelerometer is defined which offers a minimal signalroll-off small size and weight solution to the larger arrayslayout Also from the table it is identified that passive seismichas high potential benefits but requires special ultra noiselow frequency and short bandwidth sensing capabilitiesSince the existing device and the sensor are unable torecord at this frequency various types of sensor are studied(discussed in Section 4) Based on sensor analysis it isfound that MEMS accelerometers (capacitive) based deviceis the best replacement of existing seismological equipmentCapacitive accelerometers performed well in low bandwidthlow frequency and minimum noise Hence passive seismicexploration is an ongoing and promising research topic withthe benefit of being environmentally friendly and of low cost

31 Comparison of Technical Structure of Active andPassive Imaging

311 Active Seismic ImagingMethod In the acquisition of theactive seismic data a feedback model has been implementedwhich is based on the principal that both sources and

Pminus(z0 z0) Rcap(z0 z0)

X0(z0 z0)

120575P+(z0 z0)

S+(z0)+

X(z0 z0)

Figure 15 A feedforward model representing the upgoing anddowngoing wavefields in conventional seismic acquisition [130]

detectors are normally placed at or near the earthrsquos surfacedepicted in Figure 15 [133] It demonstrates schematically up-and downgoingwavefields happening at the reflecting surface(1199110) while the wavefields are going ldquoalongrdquo the surface being

overlookedAccordingly consider a matrix 119883

0(1199110 1199110) having a mul-

tidimensional transfer function of the subsurface (119911 gt 1199110)

Here each variable of1198830(1199110 1199110) characterized as the impulse

response of the wavefield occurred from a unit dipole sourceat 1199110and is further sensed by a unit pressure sensor at 119911

0 Also

the subscript ldquo0rdquo in 1198830symbolizes that earthrsquos surface has a

free reflection boundary that is a single round-trip (mean

Journal of Sensors 13

two-way time) has been estimated by the seismic signal fromthe subsurface (from 119911

0to 1199110) 1198830(1199110 1199110) has been utilized

as the multidimensional wavefield operator which definesthe wavefields at the reflection free acquisition surface 119911

0

119875

minus

0(1199110 1199110) as

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (25a)

or

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 120575119875

+(1199110 1199110)

+ 1198830(1199110 1199110) 119878

+

0(1199110 1199110)

(25b)

with combining

120575119875

+(1199110 1199110) = 119877

cap(1199110 1199110) 119875

minus

0(1199110 1199110) (25c)

In (25a) source matrix 119878

+

0(1199110) signifies the downgoing

wavefield of one physical source (array) at 1199110

However1198830119878

+ stands for the upgoing primary wavefields(one round-trip) and119883

0120575119875

+ stands for the upgoingmultiple-scattering wavefields (many round-trips)

Furthermore from (25a)ndash(25c) it can be simply derivedthat

1198830(1199110 1199110)

= [119868 minus 1198830(1199110 1199110) 119877

cap(1199110 1199110)]

minus1

1198830(1199110 1199110)

(26a)

representing the complexity of119883 relating to1198830 On compar-

ing (25a)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (26b)

with (25b)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) [120575119875

+(1199110 1199110) + 119878

+(1199110 1199110)] (26c)

Based on (26b) it can be concluded that the surface-related multiple-scattering phenomenon is incorporated intoa parameter 119883 However (26c) signifies that the surface-related multiple-scattering is incorporated into the downgo-ing wavefield 120575

119875

+

and the parameter 119883 determined as 1198830

Such variation between mathematical equations (26b) and(26c) assumes an imperative part in the inversion modelingfor seismic imaging [134]

Here Figure 16 represents the mixed shot record array offive sources at or near the surfaces Since during acquisitionzero time delays and large spacing between the sourcesare considered resulting incoherent shooting will becomesimultaneous shooting [136 139 140]The resultants imagingsignifies that a passive seismic recording can be measured asa naturally mixed shot record

312 Passive Seismic Imaging Method Based on DownwardRadiating Natural Sources Initially it is considered thatpseudo sources are set at or close to the surface (119911

0)

signifying that the background noise is considered as thosewavefields generated by the natural sources However in pas-sive seismic imaging response from natural sources has been

Tim

e (s)

30

25

20

15

10

05

00 1000 2000 3000 4000 5000

Lateral distance (m)

Figure 16 A mixed pseudo shot record generated by usingincoherent source array having five source elements at the surface[135 136]

considered as the seismic signal from the subsurface Thesesources might be set anyplace at the surface (119911 = 119911

0) and

in the subsurface (119911 gt 1199110) [137] Henceforth a noise model

has been createdwhichmay consider a continuing happeningseismic background noise as an indicator to determine theinformative data from these noises This concept is knownas seismic interferometry [141] Furthermore a relationshipby utilizing the wavefield diagram (see Figure 9) has beenestablished between the downgoing source wavefield at thesource level (119911

119899) and the up- and downgoing wavefields at

perception level 1199110(119911 = 119911

0) Such relation can be expressed

as

119875

+

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 119911119899)

119878

+

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110) [119882

minus1(1199110 119911119899)

119878

+

(119911119899)]

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110)

119878

+

(1199110 119911119899)

(27a)

where

119882

minus1(1199110 119911119899) = 119883

minus1

0(1199110 1199110)1198830(1199110 1199110) (27b)

Figure 17 describes the feed-forwarded model which isbased on modeling by downward radiating natural sourcesat and below the surface (119899 ge 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

313 Passive Seismic Imaging Method Based on UpwardRadiating Natural Sources In this phase like active seismicbackground noise similar type of natural sourcersquos responseis considered but the direction has been changed to the

14 Journal of Sensors

rarr(z0 zn)

W(zn z0)

Rcap(z0 z0)

rarr(zn)+X0(z0 zn)

120575rarr

(z0 zn)

n = 0 1 2 middot middot middot

Pminus

P+

S+

Figure 17 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

rarrPminus(z0 zn)

W(z0 zn)

Rcap(z0 z0)

rarrS (zn)

+ X0(zn z0)

120575rarrP (z0 zn)

n = 1 2

+

minus

Figure 18 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

contribution of ldquoupwardrdquo radiation Figure 18 depicts theresultants response which describes the correlation betweenthe upgoing source wavefields at the source level (119911

119899) and the

up- and downgoing wavefields at observation level 1199110 Such

result can be expressed as

119875

minus

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 119882(1199110 119911119899)

119878

minus

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899) +

119878

minus

(1199110 119911119899)

(28)

Figure 18 describes the feed-forwarded model which isbased on modeling by upward radiating natural sources atand below the surface (119899 gt 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

314 Statistical Description of the Modeling In the statisticalanalysis of the above designed model the above definedexpressions have been utilized on an exceptionally straight-forward medium Such medium has one horizontal reflectorand a free surface depicted in Figure 19 The stepwiseconstruction of thismedium signifies imaging in Figure 19(a)describing the conventional active seismic record where oneprimary and the surface multiples have been identified andindicated by a mathematical expression in (25b) In continu-ation Figure 19(b) describes the measurement of a responsefrom a downward radiating noise burst by implementing(27a) and (27b) while Figure 19(c) describes the upwardtransmitting patterns by estimating (28)

From these figures and equation implementation it isclearly defined that the occurrence of response and its mul-tiples takes place directly Moreover Figure 19(d) preciselydemonstrates the effect of such multiples that is the noisebursts being the summation of Figures 19(b) and 19(c)respectively

Figure 19 defines the straightforward medium whichhas one horizontal reflector and a stress-free surface HereFigure 19(a) describes the impulsive source at the surfacewhile Figure 19(b) shows at first layer the downward radiatingnoise source Similarly Figure 19(c) shows at first layerthe upward radiating noise source Finally Figure 19(d)establishes the omnidirectional noise source in the first layerof imagingOverall it has been signified that different sourcesdetermine the different resultant responses For exampleFigure 19 clearly proved this statement by demonstrating thatall sources defined here produce the different responses at ornear the subsurface of seismic imaging

32 Example Showing the Processing of Active and PassiveSeismic Imaging and Their Significance In this examplefor a mixed seismic data response inversion method fol-lowed for known and unknown sources is illustrated Herethree reflectors are utilized to measure the response forthe subsurface modeling (see Figure 20(a)) To begin withwithout considering surface-related multiples 119883

0 the mul-

tidimensional impulse response of the subsurface has beenproduced However Figures 20(b)ndash20(d) describe the three-column impulsive response of 119883

0 It results in naturally

occurring mixed recording at the subsurface Therefore inthe next modeling step surface-related multiples have beenimplemented that is from119883

0to119883

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

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[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

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[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

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[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

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RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

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Shock and Vibration

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SensorsJournal of

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Chemical EngineeringInternational Journal of Antennas and

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Navigation and Observation

International Journal of

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DistributedSensor Networks

International Journal of

10 Journal of Sensors

Sensing fingers

Springs

Driving fingers

(a)

A

A998400

Wb Wa

Lb

La

LeffLf

X0

Wf

(b)

Figure 12 Structure of a lateral capacitive accelerometer (a) isometric device view (b) spring parameters (119882119887119882119886 119871119886 119871119887) and fingers

parameters (1198830119882119891 119871119891 119871eff ) [124]

In the electrical domain the noise can be minimizedby reducing the operating bandwidth Additionally a closed-loop feedback electronic circuit is required to compensate thenonlinear response of the mechanical system and to shortenthe bandwidth of the device to 30Hz To minimize the noiseeffect from amplifier the rate of capacitance change withacceleration needs to be maximized [19] Maximizing thesensitivity requires minimizing sensing gap and lowering thenatural resonant frequency [19 92 129]

As previously discussed the minimum detectable accel-eration should be = 802

24= 47 ng This implies that

the maximum mechanical noise 119886119898

should be less than086 gradicHz according to

119886119898

=

119886minradicBW

=

47 ngradic30

= 086 gradicHz (18)

In order to size the design challenges of ultralow noisefloor a case study on accelerometer design with conventionalcomb structure is considered The structure as shown inFigure 12 comprises a fixed rectangular framewith fingers anda moving proof mass fixed on the frame by spring-like shapeat both ends and surrounded by fingers at its both sides

Accelerometers noise performance is generally deter-mined by the damping coefficient and proof mass size assuggested by (5) The dominant damping mechanism in thisstructure is due to the squeeze-film effect [125]Therefore thedamping coefficient 119887 can be written in

119887 = 72119873120583119905 (

119897eff1199090

)

3

(19)

whereby 119873 is the number of comb fingers 119905 is the proofmass thickness 120583 is the viscosity of the air under atmosphericpressure 20∘C = 154 times 10minus6 kgms and 119897eff is the engagedlength of the comb fingers

Moreover the mass 119898 can be expressed in (20) where 119898

defines the mass of the proof mass 120588 is the silicon density =2330 kgm3 119897

119891is the length of comb fingers 119882

119891is the width

of comb fingers and 119860 is the area of the proof mass

119898 = 119905120588 (119860 + 119873119897119891119882119891) (20)

As a result the mechanical noise 119886nm can be expressed bysubstituting (19) and (20) in (17) to obtain

119886nm =

radic4119896119861119879 [72119873120583119905 (119897eff1199090)

3]

98 [119905120588 (119860 + 119873119897119891119882119891)]

(21)

As depicted in Figure 12(a) the proof mass parameters119860 and 119905 typically have large values compared to fingersdimensions 119871eff 119871119891119882119891 and 119883

0[124] As a result the proof

mass is effectively increased by enlarging parameters119860 and 119905The realization of sub-ngradicHz of noise spectral density

through mass maximization has a positive impact on devicesensitivityThis can be explained by the proportional relation-ship between sensitivity and mass as displayed in

119878 =

119881119904

119886in=

4119862119904

2119862119904+ 119862119901

sdot

119881m1199090

sdot

119898

119896

(22)

whereby 119878 is the sensitivity (Vg) 119862119904is the sensing capaci-

tance 119862119901is the parasitic capacitance119881m is maximum output

voltage (V) 119886in is maximum input acceleration (g) and 119896 isthe spring constant (Nm)

The maximization of sensitivity is an important designgoal This is achievable by maximizing the proof mass andminimizing the spring constant as suggested by (22) How-ever the resonant frequency has to be considered Equations(23) and (24) describe the structural dependencies of thespring constant 119896 and the device resonant frequency 119891respectively as follows

119896 = 2

1

(119899 minus 1)

3sdot 119864 (

119882119887

2119871119887

)

3

119905 (23)

119891 =

1

2120587

sdotradic

119896

119898

(24)

where 119899 is the number of mechanical spring turns 119882119887is

the width of single turn spring 119871119887is the length of single

turn spring and 119864 is Youngrsquos Modulus of silicon = 154 times

10minus6 kgms

231 Summarized Analysis of the Type of Accelerometers Forinitial analysis (18)ndash(23) have been solved yielding to the

Journal of Sensors 11

Table 8 Initial design parameters and values

Parameter Value Parameter Value119897eff 80 120583m 119899 8119897119891

85 120583m 1199090

83 120583m119882119891

48 120583m 119905 3318 120583m119873 200 119897

1198872mm

119860 5mm times 5mm 119882119887

75 120583m119898 2120583g 119886nm 085 ngrtHz119891 46Hz 119878 026

values as listed in Table 8 The table shows the parametersand the corresponding values for the design in rows 2ndash6The resulting device performance (noise resonant frequencyand sensitivity) is shown in the last two rows The tableshows that a 5mm times 5mm proof mass area was requiredEven though the sensitivity (026Vg) is lower than state-of-the-art value this device is considered large structure forconventional CMOS technology To improve the sensitivityfurther enlargement for the proof mass is required Thisshows the major challenge of the design

Therefore achieving the noise spectral density of less than1 ngradicHz on a conventional capacitive structure is challeng-ing As a result a novel structure and design optimization isexpected to meet the stringent resolution level requirements

232 Conclusion on the Analysis The excessive demandsfor hydrocarbon have pushed the exploration technologyto the era of passive seismic monitoring The technique iseconomically promising and environmentally friendly butfacing several challenges among which is the high resolutionacquisition using state-of-the-art sensorsaccelerometers

In this paper the technological gap between themeasure-ment resolution of the state-of-the-art sensors and emergingdevices is identified for passive seismic monitoring It showsdesign possibilities using capacitive sensing techniques andmotivates further work in developing optimized sensor solu-tions

Finally a solution has been provided with specificationto design such an accelerometer To enhance the resolutionand sensitivity a dimension in the order of millimeters largerthan conventional MEMS dimensions is required Moreovertechnological issues including reducing parasitic capacitanceby increasing dielectric thickness and reducing air pressurefor less damping impact beyond 1ndash10 Torr are among theconstraints hindering prospective designs

In synopsis piezoelectric accelerometers demonstrate themost astounding estimation range shock limits and oper-ating temperature capacitive accelerometers the least powerutilization and volume and piezoresistive accelerometers thevastest frequency response

3 Sensors in Seismology

Seismic study determines that the effective exploration tech-nique for imaging the geology is active seismic imagingPreviously explosives or vibroseis trucks are utilized for

Nor

mal

ized

ampl

itude

minus1

minus05

0

05

1

0 02 04 06 08 1 12 14

Time (s)

P-wave S-wave

Figure 13 A ldquogoodrdquo occurrence of P- and S-wave arrivals in timedomain [44]

Nor

mal

ized

ampl

itude

minus1minus05

0051

0 02 04 06 08 1 12 14

Time (s)

Figure 14 A random ldquonoiserdquo event at time domain [33]

generating seismic energy sensed by the network of seismicsensors which may provide the information that determinesthe prospective oil and gas traps In view of received sensordata a 3D stratigraphy map is developed This 3D map mayhelp in determining the position of hydrocarbon depositionsMoreover the increasing demand and supply of oil and gasneed industries to explore more hydrocarbons from previous50 to 80 by identifying accurate information about hydro-carbon deposition [44 45] Conventional techniques cannotprovide the correct information about the petrophysicalproperties of reservoir because the rock pores having hydro-carbon affect the physical properties of the rockwhich in turncause poor energy sensed through seismic sensors One ofthe key solutions for accurate information is passive seismicimaging technique This technique uses naturally happeningseismic signals like earth quake microtremors and oceanwaves for subsurface imaging and structuring In comparisonof conventional technique having sensing frequency in therange of 10ndash300Hz passive seismic technique monitors thelower frequency waves (below 10Hz) whichmay travel a longdistance through the earthrsquos crust without attenuation

An example of ldquoGoodrdquo event having occurrences of P-wave and S-wave at time domain is showed in Figure 13 Onthe basis of the discrete and impulsive P-wave and S-wavearrivals the event is termed ldquoGoodrdquo event [33]

Also it is shown clearly that frequency of S-wavedecreases as the frequency of P-wave increases A randomldquonoiserdquo event occurring at time domain with indeterministicproperties of ldquoGoodrdquo events is shown in Figure 14 [33]

In the area of reservoir monitoring passive seismichave applications for recording microseismic signal at nat-ural frequency for the exploration and exploitation of thehydrocarbons (ie oil and gas) [131] The study of passiveseismic at variant frequency identifies that information aboutprediction of hydrocarbon reservoir is found at low frequencyof less than 10Hz [1ndash5 132] as depicted in Table 9

12 Journal of Sensors

Table 9 Technical description of seismic data acquisition technique at low frequency

Frequency range focused Technique used Advantage Disadvantage

Modeling frequency 50ndash60Hz[25]

Spike deconvolution for lowfrequency modeling

(i) Low-cut filter is used toattenuate low frequencies

(ii) Defining technique producesbetter P-wave and S-wave seismic

section

(i) Need for recovery of broadsignal bandwidth

(ii) Poor wavelet extraction andits structure

Modeling frequency 1 KHzAcquired seismic frequency12HzReflectivity at 40Hz [26]

(i) Ultrasonic experiment(ii) Seismic data analysis

(i) Signal is reflected from a thinwater- (S

119908) or oil-saturated (S

ℎ)

layer(ii) Frequency dependent

amplitude and phase reflectionattributes have been utilized forobserving and identifying thin

liquid saturated layers

(i) Strong attenuation in the layeraffects summation of multiples

(ii) Layers with higherattenuation create travel timedelays which increase asfrequency approaches zero

Missing frequency 5ndash10Hz [27]

(i) 3D acoustic inversion(ii) Variable depth streamerseismic data acquisition(iii) 3D elastic inversioncomparison technique

(i) Variable depth streamer fordata acquisition is better for

inversion and provides missinglow frequencies directly

(ii) Left side lobe of the wavelet isproposed to reduceless

interference in the seismic signalresults in less ambiguity in

inversion

(i) There is variation in resultinginversion due to high variation in

acquisition frequency(ii) Broadband inversion may

cause obtained results outside thetarget zone

Reflection lt15HzAmplitude 40Hz [28]

(i) AVO attribute analysis(ii) VSP analysis

(i) Imaging at low frequenciesresults in robust amplitudes for

individual frequencycomponents of propagating

wavelet(ii) Frequency based seismic

imaging permits characterizingthe subsurface fluid reservoirs

(i) Quantitative analysis of AI (asfrequency) requires NMO

stretching(ii) Conventional seismic

processing software does notwork as target-oriented

processing

Based on Table 9 it is clear that the type of geophonesused in active seismic acquisition has greater size and islinearly proportional to the velocity over the resonancefrequency (about 10Hz) [25ndash28] Therefore a new design ofthe accelerometer is defined which offers a minimal signalroll-off small size and weight solution to the larger arrayslayout Also from the table it is identified that passive seismichas high potential benefits but requires special ultra noiselow frequency and short bandwidth sensing capabilitiesSince the existing device and the sensor are unable torecord at this frequency various types of sensor are studied(discussed in Section 4) Based on sensor analysis it isfound that MEMS accelerometers (capacitive) based deviceis the best replacement of existing seismological equipmentCapacitive accelerometers performed well in low bandwidthlow frequency and minimum noise Hence passive seismicexploration is an ongoing and promising research topic withthe benefit of being environmentally friendly and of low cost

31 Comparison of Technical Structure of Active andPassive Imaging

311 Active Seismic ImagingMethod In the acquisition of theactive seismic data a feedback model has been implementedwhich is based on the principal that both sources and

Pminus(z0 z0) Rcap(z0 z0)

X0(z0 z0)

120575P+(z0 z0)

S+(z0)+

X(z0 z0)

Figure 15 A feedforward model representing the upgoing anddowngoing wavefields in conventional seismic acquisition [130]

detectors are normally placed at or near the earthrsquos surfacedepicted in Figure 15 [133] It demonstrates schematically up-and downgoingwavefields happening at the reflecting surface(1199110) while the wavefields are going ldquoalongrdquo the surface being

overlookedAccordingly consider a matrix 119883

0(1199110 1199110) having a mul-

tidimensional transfer function of the subsurface (119911 gt 1199110)

Here each variable of1198830(1199110 1199110) characterized as the impulse

response of the wavefield occurred from a unit dipole sourceat 1199110and is further sensed by a unit pressure sensor at 119911

0 Also

the subscript ldquo0rdquo in 1198830symbolizes that earthrsquos surface has a

free reflection boundary that is a single round-trip (mean

Journal of Sensors 13

two-way time) has been estimated by the seismic signal fromthe subsurface (from 119911

0to 1199110) 1198830(1199110 1199110) has been utilized

as the multidimensional wavefield operator which definesthe wavefields at the reflection free acquisition surface 119911

0

119875

minus

0(1199110 1199110) as

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (25a)

or

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 120575119875

+(1199110 1199110)

+ 1198830(1199110 1199110) 119878

+

0(1199110 1199110)

(25b)

with combining

120575119875

+(1199110 1199110) = 119877

cap(1199110 1199110) 119875

minus

0(1199110 1199110) (25c)

In (25a) source matrix 119878

+

0(1199110) signifies the downgoing

wavefield of one physical source (array) at 1199110

However1198830119878

+ stands for the upgoing primary wavefields(one round-trip) and119883

0120575119875

+ stands for the upgoingmultiple-scattering wavefields (many round-trips)

Furthermore from (25a)ndash(25c) it can be simply derivedthat

1198830(1199110 1199110)

= [119868 minus 1198830(1199110 1199110) 119877

cap(1199110 1199110)]

minus1

1198830(1199110 1199110)

(26a)

representing the complexity of119883 relating to1198830 On compar-

ing (25a)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (26b)

with (25b)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) [120575119875

+(1199110 1199110) + 119878

+(1199110 1199110)] (26c)

Based on (26b) it can be concluded that the surface-related multiple-scattering phenomenon is incorporated intoa parameter 119883 However (26c) signifies that the surface-related multiple-scattering is incorporated into the downgo-ing wavefield 120575

119875

+

and the parameter 119883 determined as 1198830

Such variation between mathematical equations (26b) and(26c) assumes an imperative part in the inversion modelingfor seismic imaging [134]

Here Figure 16 represents the mixed shot record array offive sources at or near the surfaces Since during acquisitionzero time delays and large spacing between the sourcesare considered resulting incoherent shooting will becomesimultaneous shooting [136 139 140]The resultants imagingsignifies that a passive seismic recording can be measured asa naturally mixed shot record

312 Passive Seismic Imaging Method Based on DownwardRadiating Natural Sources Initially it is considered thatpseudo sources are set at or close to the surface (119911

0)

signifying that the background noise is considered as thosewavefields generated by the natural sources However in pas-sive seismic imaging response from natural sources has been

Tim

e (s)

30

25

20

15

10

05

00 1000 2000 3000 4000 5000

Lateral distance (m)

Figure 16 A mixed pseudo shot record generated by usingincoherent source array having five source elements at the surface[135 136]

considered as the seismic signal from the subsurface Thesesources might be set anyplace at the surface (119911 = 119911

0) and

in the subsurface (119911 gt 1199110) [137] Henceforth a noise model

has been createdwhichmay consider a continuing happeningseismic background noise as an indicator to determine theinformative data from these noises This concept is knownas seismic interferometry [141] Furthermore a relationshipby utilizing the wavefield diagram (see Figure 9) has beenestablished between the downgoing source wavefield at thesource level (119911

119899) and the up- and downgoing wavefields at

perception level 1199110(119911 = 119911

0) Such relation can be expressed

as

119875

+

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 119911119899)

119878

+

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110) [119882

minus1(1199110 119911119899)

119878

+

(119911119899)]

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110)

119878

+

(1199110 119911119899)

(27a)

where

119882

minus1(1199110 119911119899) = 119883

minus1

0(1199110 1199110)1198830(1199110 1199110) (27b)

Figure 17 describes the feed-forwarded model which isbased on modeling by downward radiating natural sourcesat and below the surface (119899 ge 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

313 Passive Seismic Imaging Method Based on UpwardRadiating Natural Sources In this phase like active seismicbackground noise similar type of natural sourcersquos responseis considered but the direction has been changed to the

14 Journal of Sensors

rarr(z0 zn)

W(zn z0)

Rcap(z0 z0)

rarr(zn)+X0(z0 zn)

120575rarr

(z0 zn)

n = 0 1 2 middot middot middot

Pminus

P+

S+

Figure 17 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

rarrPminus(z0 zn)

W(z0 zn)

Rcap(z0 z0)

rarrS (zn)

+ X0(zn z0)

120575rarrP (z0 zn)

n = 1 2

+

minus

Figure 18 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

contribution of ldquoupwardrdquo radiation Figure 18 depicts theresultants response which describes the correlation betweenthe upgoing source wavefields at the source level (119911

119899) and the

up- and downgoing wavefields at observation level 1199110 Such

result can be expressed as

119875

minus

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 119882(1199110 119911119899)

119878

minus

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899) +

119878

minus

(1199110 119911119899)

(28)

Figure 18 describes the feed-forwarded model which isbased on modeling by upward radiating natural sources atand below the surface (119899 gt 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

314 Statistical Description of the Modeling In the statisticalanalysis of the above designed model the above definedexpressions have been utilized on an exceptionally straight-forward medium Such medium has one horizontal reflectorand a free surface depicted in Figure 19 The stepwiseconstruction of thismedium signifies imaging in Figure 19(a)describing the conventional active seismic record where oneprimary and the surface multiples have been identified andindicated by a mathematical expression in (25b) In continu-ation Figure 19(b) describes the measurement of a responsefrom a downward radiating noise burst by implementing(27a) and (27b) while Figure 19(c) describes the upwardtransmitting patterns by estimating (28)

From these figures and equation implementation it isclearly defined that the occurrence of response and its mul-tiples takes place directly Moreover Figure 19(d) preciselydemonstrates the effect of such multiples that is the noisebursts being the summation of Figures 19(b) and 19(c)respectively

Figure 19 defines the straightforward medium whichhas one horizontal reflector and a stress-free surface HereFigure 19(a) describes the impulsive source at the surfacewhile Figure 19(b) shows at first layer the downward radiatingnoise source Similarly Figure 19(c) shows at first layerthe upward radiating noise source Finally Figure 19(d)establishes the omnidirectional noise source in the first layerof imagingOverall it has been signified that different sourcesdetermine the different resultant responses For exampleFigure 19 clearly proved this statement by demonstrating thatall sources defined here produce the different responses at ornear the subsurface of seismic imaging

32 Example Showing the Processing of Active and PassiveSeismic Imaging and Their Significance In this examplefor a mixed seismic data response inversion method fol-lowed for known and unknown sources is illustrated Herethree reflectors are utilized to measure the response forthe subsurface modeling (see Figure 20(a)) To begin withwithout considering surface-related multiples 119883

0 the mul-

tidimensional impulse response of the subsurface has beenproduced However Figures 20(b)ndash20(d) describe the three-column impulsive response of 119883

0 It results in naturally

occurring mixed recording at the subsurface Therefore inthe next modeling step surface-related multiples have beenimplemented that is from119883

0to119883

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

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[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

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[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

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[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

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[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

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[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

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[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

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[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

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Journal of Sensors 25

[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

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[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

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[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

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[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

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[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

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[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

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[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

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[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

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[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

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[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

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Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

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Active and Passive Electronic Components

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Acoustics and VibrationAdvances in

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Electrical and Computer Engineering

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Chemical EngineeringInternational Journal of Antennas and

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Navigation and Observation

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DistributedSensor Networks

International Journal of

Journal of Sensors 11

Table 8 Initial design parameters and values

Parameter Value Parameter Value119897eff 80 120583m 119899 8119897119891

85 120583m 1199090

83 120583m119882119891

48 120583m 119905 3318 120583m119873 200 119897

1198872mm

119860 5mm times 5mm 119882119887

75 120583m119898 2120583g 119886nm 085 ngrtHz119891 46Hz 119878 026

values as listed in Table 8 The table shows the parametersand the corresponding values for the design in rows 2ndash6The resulting device performance (noise resonant frequencyand sensitivity) is shown in the last two rows The tableshows that a 5mm times 5mm proof mass area was requiredEven though the sensitivity (026Vg) is lower than state-of-the-art value this device is considered large structure forconventional CMOS technology To improve the sensitivityfurther enlargement for the proof mass is required Thisshows the major challenge of the design

Therefore achieving the noise spectral density of less than1 ngradicHz on a conventional capacitive structure is challeng-ing As a result a novel structure and design optimization isexpected to meet the stringent resolution level requirements

232 Conclusion on the Analysis The excessive demandsfor hydrocarbon have pushed the exploration technologyto the era of passive seismic monitoring The technique iseconomically promising and environmentally friendly butfacing several challenges among which is the high resolutionacquisition using state-of-the-art sensorsaccelerometers

In this paper the technological gap between themeasure-ment resolution of the state-of-the-art sensors and emergingdevices is identified for passive seismic monitoring It showsdesign possibilities using capacitive sensing techniques andmotivates further work in developing optimized sensor solu-tions

Finally a solution has been provided with specificationto design such an accelerometer To enhance the resolutionand sensitivity a dimension in the order of millimeters largerthan conventional MEMS dimensions is required Moreovertechnological issues including reducing parasitic capacitanceby increasing dielectric thickness and reducing air pressurefor less damping impact beyond 1ndash10 Torr are among theconstraints hindering prospective designs

In synopsis piezoelectric accelerometers demonstrate themost astounding estimation range shock limits and oper-ating temperature capacitive accelerometers the least powerutilization and volume and piezoresistive accelerometers thevastest frequency response

3 Sensors in Seismology

Seismic study determines that the effective exploration tech-nique for imaging the geology is active seismic imagingPreviously explosives or vibroseis trucks are utilized for

Nor

mal

ized

ampl

itude

minus1

minus05

0

05

1

0 02 04 06 08 1 12 14

Time (s)

P-wave S-wave

Figure 13 A ldquogoodrdquo occurrence of P- and S-wave arrivals in timedomain [44]

Nor

mal

ized

ampl

itude

minus1minus05

0051

0 02 04 06 08 1 12 14

Time (s)

Figure 14 A random ldquonoiserdquo event at time domain [33]

generating seismic energy sensed by the network of seismicsensors which may provide the information that determinesthe prospective oil and gas traps In view of received sensordata a 3D stratigraphy map is developed This 3D map mayhelp in determining the position of hydrocarbon depositionsMoreover the increasing demand and supply of oil and gasneed industries to explore more hydrocarbons from previous50 to 80 by identifying accurate information about hydro-carbon deposition [44 45] Conventional techniques cannotprovide the correct information about the petrophysicalproperties of reservoir because the rock pores having hydro-carbon affect the physical properties of the rockwhich in turncause poor energy sensed through seismic sensors One ofthe key solutions for accurate information is passive seismicimaging technique This technique uses naturally happeningseismic signals like earth quake microtremors and oceanwaves for subsurface imaging and structuring In comparisonof conventional technique having sensing frequency in therange of 10ndash300Hz passive seismic technique monitors thelower frequency waves (below 10Hz) whichmay travel a longdistance through the earthrsquos crust without attenuation

An example of ldquoGoodrdquo event having occurrences of P-wave and S-wave at time domain is showed in Figure 13 Onthe basis of the discrete and impulsive P-wave and S-wavearrivals the event is termed ldquoGoodrdquo event [33]

Also it is shown clearly that frequency of S-wavedecreases as the frequency of P-wave increases A randomldquonoiserdquo event occurring at time domain with indeterministicproperties of ldquoGoodrdquo events is shown in Figure 14 [33]

In the area of reservoir monitoring passive seismichave applications for recording microseismic signal at nat-ural frequency for the exploration and exploitation of thehydrocarbons (ie oil and gas) [131] The study of passiveseismic at variant frequency identifies that information aboutprediction of hydrocarbon reservoir is found at low frequencyof less than 10Hz [1ndash5 132] as depicted in Table 9

12 Journal of Sensors

Table 9 Technical description of seismic data acquisition technique at low frequency

Frequency range focused Technique used Advantage Disadvantage

Modeling frequency 50ndash60Hz[25]

Spike deconvolution for lowfrequency modeling

(i) Low-cut filter is used toattenuate low frequencies

(ii) Defining technique producesbetter P-wave and S-wave seismic

section

(i) Need for recovery of broadsignal bandwidth

(ii) Poor wavelet extraction andits structure

Modeling frequency 1 KHzAcquired seismic frequency12HzReflectivity at 40Hz [26]

(i) Ultrasonic experiment(ii) Seismic data analysis

(i) Signal is reflected from a thinwater- (S

119908) or oil-saturated (S

ℎ)

layer(ii) Frequency dependent

amplitude and phase reflectionattributes have been utilized forobserving and identifying thin

liquid saturated layers

(i) Strong attenuation in the layeraffects summation of multiples

(ii) Layers with higherattenuation create travel timedelays which increase asfrequency approaches zero

Missing frequency 5ndash10Hz [27]

(i) 3D acoustic inversion(ii) Variable depth streamerseismic data acquisition(iii) 3D elastic inversioncomparison technique

(i) Variable depth streamer fordata acquisition is better for

inversion and provides missinglow frequencies directly

(ii) Left side lobe of the wavelet isproposed to reduceless

interference in the seismic signalresults in less ambiguity in

inversion

(i) There is variation in resultinginversion due to high variation in

acquisition frequency(ii) Broadband inversion may

cause obtained results outside thetarget zone

Reflection lt15HzAmplitude 40Hz [28]

(i) AVO attribute analysis(ii) VSP analysis

(i) Imaging at low frequenciesresults in robust amplitudes for

individual frequencycomponents of propagating

wavelet(ii) Frequency based seismic

imaging permits characterizingthe subsurface fluid reservoirs

(i) Quantitative analysis of AI (asfrequency) requires NMO

stretching(ii) Conventional seismic

processing software does notwork as target-oriented

processing

Based on Table 9 it is clear that the type of geophonesused in active seismic acquisition has greater size and islinearly proportional to the velocity over the resonancefrequency (about 10Hz) [25ndash28] Therefore a new design ofthe accelerometer is defined which offers a minimal signalroll-off small size and weight solution to the larger arrayslayout Also from the table it is identified that passive seismichas high potential benefits but requires special ultra noiselow frequency and short bandwidth sensing capabilitiesSince the existing device and the sensor are unable torecord at this frequency various types of sensor are studied(discussed in Section 4) Based on sensor analysis it isfound that MEMS accelerometers (capacitive) based deviceis the best replacement of existing seismological equipmentCapacitive accelerometers performed well in low bandwidthlow frequency and minimum noise Hence passive seismicexploration is an ongoing and promising research topic withthe benefit of being environmentally friendly and of low cost

31 Comparison of Technical Structure of Active andPassive Imaging

311 Active Seismic ImagingMethod In the acquisition of theactive seismic data a feedback model has been implementedwhich is based on the principal that both sources and

Pminus(z0 z0) Rcap(z0 z0)

X0(z0 z0)

120575P+(z0 z0)

S+(z0)+

X(z0 z0)

Figure 15 A feedforward model representing the upgoing anddowngoing wavefields in conventional seismic acquisition [130]

detectors are normally placed at or near the earthrsquos surfacedepicted in Figure 15 [133] It demonstrates schematically up-and downgoingwavefields happening at the reflecting surface(1199110) while the wavefields are going ldquoalongrdquo the surface being

overlookedAccordingly consider a matrix 119883

0(1199110 1199110) having a mul-

tidimensional transfer function of the subsurface (119911 gt 1199110)

Here each variable of1198830(1199110 1199110) characterized as the impulse

response of the wavefield occurred from a unit dipole sourceat 1199110and is further sensed by a unit pressure sensor at 119911

0 Also

the subscript ldquo0rdquo in 1198830symbolizes that earthrsquos surface has a

free reflection boundary that is a single round-trip (mean

Journal of Sensors 13

two-way time) has been estimated by the seismic signal fromthe subsurface (from 119911

0to 1199110) 1198830(1199110 1199110) has been utilized

as the multidimensional wavefield operator which definesthe wavefields at the reflection free acquisition surface 119911

0

119875

minus

0(1199110 1199110) as

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (25a)

or

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 120575119875

+(1199110 1199110)

+ 1198830(1199110 1199110) 119878

+

0(1199110 1199110)

(25b)

with combining

120575119875

+(1199110 1199110) = 119877

cap(1199110 1199110) 119875

minus

0(1199110 1199110) (25c)

In (25a) source matrix 119878

+

0(1199110) signifies the downgoing

wavefield of one physical source (array) at 1199110

However1198830119878

+ stands for the upgoing primary wavefields(one round-trip) and119883

0120575119875

+ stands for the upgoingmultiple-scattering wavefields (many round-trips)

Furthermore from (25a)ndash(25c) it can be simply derivedthat

1198830(1199110 1199110)

= [119868 minus 1198830(1199110 1199110) 119877

cap(1199110 1199110)]

minus1

1198830(1199110 1199110)

(26a)

representing the complexity of119883 relating to1198830 On compar-

ing (25a)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (26b)

with (25b)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) [120575119875

+(1199110 1199110) + 119878

+(1199110 1199110)] (26c)

Based on (26b) it can be concluded that the surface-related multiple-scattering phenomenon is incorporated intoa parameter 119883 However (26c) signifies that the surface-related multiple-scattering is incorporated into the downgo-ing wavefield 120575

119875

+

and the parameter 119883 determined as 1198830

Such variation between mathematical equations (26b) and(26c) assumes an imperative part in the inversion modelingfor seismic imaging [134]

Here Figure 16 represents the mixed shot record array offive sources at or near the surfaces Since during acquisitionzero time delays and large spacing between the sourcesare considered resulting incoherent shooting will becomesimultaneous shooting [136 139 140]The resultants imagingsignifies that a passive seismic recording can be measured asa naturally mixed shot record

312 Passive Seismic Imaging Method Based on DownwardRadiating Natural Sources Initially it is considered thatpseudo sources are set at or close to the surface (119911

0)

signifying that the background noise is considered as thosewavefields generated by the natural sources However in pas-sive seismic imaging response from natural sources has been

Tim

e (s)

30

25

20

15

10

05

00 1000 2000 3000 4000 5000

Lateral distance (m)

Figure 16 A mixed pseudo shot record generated by usingincoherent source array having five source elements at the surface[135 136]

considered as the seismic signal from the subsurface Thesesources might be set anyplace at the surface (119911 = 119911

0) and

in the subsurface (119911 gt 1199110) [137] Henceforth a noise model

has been createdwhichmay consider a continuing happeningseismic background noise as an indicator to determine theinformative data from these noises This concept is knownas seismic interferometry [141] Furthermore a relationshipby utilizing the wavefield diagram (see Figure 9) has beenestablished between the downgoing source wavefield at thesource level (119911

119899) and the up- and downgoing wavefields at

perception level 1199110(119911 = 119911

0) Such relation can be expressed

as

119875

+

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 119911119899)

119878

+

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110) [119882

minus1(1199110 119911119899)

119878

+

(119911119899)]

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110)

119878

+

(1199110 119911119899)

(27a)

where

119882

minus1(1199110 119911119899) = 119883

minus1

0(1199110 1199110)1198830(1199110 1199110) (27b)

Figure 17 describes the feed-forwarded model which isbased on modeling by downward radiating natural sourcesat and below the surface (119899 ge 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

313 Passive Seismic Imaging Method Based on UpwardRadiating Natural Sources In this phase like active seismicbackground noise similar type of natural sourcersquos responseis considered but the direction has been changed to the

14 Journal of Sensors

rarr(z0 zn)

W(zn z0)

Rcap(z0 z0)

rarr(zn)+X0(z0 zn)

120575rarr

(z0 zn)

n = 0 1 2 middot middot middot

Pminus

P+

S+

Figure 17 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

rarrPminus(z0 zn)

W(z0 zn)

Rcap(z0 z0)

rarrS (zn)

+ X0(zn z0)

120575rarrP (z0 zn)

n = 1 2

+

minus

Figure 18 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

contribution of ldquoupwardrdquo radiation Figure 18 depicts theresultants response which describes the correlation betweenthe upgoing source wavefields at the source level (119911

119899) and the

up- and downgoing wavefields at observation level 1199110 Such

result can be expressed as

119875

minus

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 119882(1199110 119911119899)

119878

minus

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899) +

119878

minus

(1199110 119911119899)

(28)

Figure 18 describes the feed-forwarded model which isbased on modeling by upward radiating natural sources atand below the surface (119899 gt 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

314 Statistical Description of the Modeling In the statisticalanalysis of the above designed model the above definedexpressions have been utilized on an exceptionally straight-forward medium Such medium has one horizontal reflectorand a free surface depicted in Figure 19 The stepwiseconstruction of thismedium signifies imaging in Figure 19(a)describing the conventional active seismic record where oneprimary and the surface multiples have been identified andindicated by a mathematical expression in (25b) In continu-ation Figure 19(b) describes the measurement of a responsefrom a downward radiating noise burst by implementing(27a) and (27b) while Figure 19(c) describes the upwardtransmitting patterns by estimating (28)

From these figures and equation implementation it isclearly defined that the occurrence of response and its mul-tiples takes place directly Moreover Figure 19(d) preciselydemonstrates the effect of such multiples that is the noisebursts being the summation of Figures 19(b) and 19(c)respectively

Figure 19 defines the straightforward medium whichhas one horizontal reflector and a stress-free surface HereFigure 19(a) describes the impulsive source at the surfacewhile Figure 19(b) shows at first layer the downward radiatingnoise source Similarly Figure 19(c) shows at first layerthe upward radiating noise source Finally Figure 19(d)establishes the omnidirectional noise source in the first layerof imagingOverall it has been signified that different sourcesdetermine the different resultant responses For exampleFigure 19 clearly proved this statement by demonstrating thatall sources defined here produce the different responses at ornear the subsurface of seismic imaging

32 Example Showing the Processing of Active and PassiveSeismic Imaging and Their Significance In this examplefor a mixed seismic data response inversion method fol-lowed for known and unknown sources is illustrated Herethree reflectors are utilized to measure the response forthe subsurface modeling (see Figure 20(a)) To begin withwithout considering surface-related multiples 119883

0 the mul-

tidimensional impulse response of the subsurface has beenproduced However Figures 20(b)ndash20(d) describe the three-column impulsive response of 119883

0 It results in naturally

occurring mixed recording at the subsurface Therefore inthe next modeling step surface-related multiples have beenimplemented that is from119883

0to119883

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

[1] A E de Vasconcelos Lopes and L C Nunes ldquoPitfalls of tremor-like signals for hydrocarbon exploration in producing oil fieldsin Potiguar basin northeast Brazilrdquo The Leading Edge vol 29no 7 pp 826ndash830 2010

[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

Journal of Sensors 25

[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

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12 Journal of Sensors

Table 9 Technical description of seismic data acquisition technique at low frequency

Frequency range focused Technique used Advantage Disadvantage

Modeling frequency 50ndash60Hz[25]

Spike deconvolution for lowfrequency modeling

(i) Low-cut filter is used toattenuate low frequencies

(ii) Defining technique producesbetter P-wave and S-wave seismic

section

(i) Need for recovery of broadsignal bandwidth

(ii) Poor wavelet extraction andits structure

Modeling frequency 1 KHzAcquired seismic frequency12HzReflectivity at 40Hz [26]

(i) Ultrasonic experiment(ii) Seismic data analysis

(i) Signal is reflected from a thinwater- (S

119908) or oil-saturated (S

ℎ)

layer(ii) Frequency dependent

amplitude and phase reflectionattributes have been utilized forobserving and identifying thin

liquid saturated layers

(i) Strong attenuation in the layeraffects summation of multiples

(ii) Layers with higherattenuation create travel timedelays which increase asfrequency approaches zero

Missing frequency 5ndash10Hz [27]

(i) 3D acoustic inversion(ii) Variable depth streamerseismic data acquisition(iii) 3D elastic inversioncomparison technique

(i) Variable depth streamer fordata acquisition is better for

inversion and provides missinglow frequencies directly

(ii) Left side lobe of the wavelet isproposed to reduceless

interference in the seismic signalresults in less ambiguity in

inversion

(i) There is variation in resultinginversion due to high variation in

acquisition frequency(ii) Broadband inversion may

cause obtained results outside thetarget zone

Reflection lt15HzAmplitude 40Hz [28]

(i) AVO attribute analysis(ii) VSP analysis

(i) Imaging at low frequenciesresults in robust amplitudes for

individual frequencycomponents of propagating

wavelet(ii) Frequency based seismic

imaging permits characterizingthe subsurface fluid reservoirs

(i) Quantitative analysis of AI (asfrequency) requires NMO

stretching(ii) Conventional seismic

processing software does notwork as target-oriented

processing

Based on Table 9 it is clear that the type of geophonesused in active seismic acquisition has greater size and islinearly proportional to the velocity over the resonancefrequency (about 10Hz) [25ndash28] Therefore a new design ofthe accelerometer is defined which offers a minimal signalroll-off small size and weight solution to the larger arrayslayout Also from the table it is identified that passive seismichas high potential benefits but requires special ultra noiselow frequency and short bandwidth sensing capabilitiesSince the existing device and the sensor are unable torecord at this frequency various types of sensor are studied(discussed in Section 4) Based on sensor analysis it isfound that MEMS accelerometers (capacitive) based deviceis the best replacement of existing seismological equipmentCapacitive accelerometers performed well in low bandwidthlow frequency and minimum noise Hence passive seismicexploration is an ongoing and promising research topic withthe benefit of being environmentally friendly and of low cost

31 Comparison of Technical Structure of Active andPassive Imaging

311 Active Seismic ImagingMethod In the acquisition of theactive seismic data a feedback model has been implementedwhich is based on the principal that both sources and

Pminus(z0 z0) Rcap(z0 z0)

X0(z0 z0)

120575P+(z0 z0)

S+(z0)+

X(z0 z0)

Figure 15 A feedforward model representing the upgoing anddowngoing wavefields in conventional seismic acquisition [130]

detectors are normally placed at or near the earthrsquos surfacedepicted in Figure 15 [133] It demonstrates schematically up-and downgoingwavefields happening at the reflecting surface(1199110) while the wavefields are going ldquoalongrdquo the surface being

overlookedAccordingly consider a matrix 119883

0(1199110 1199110) having a mul-

tidimensional transfer function of the subsurface (119911 gt 1199110)

Here each variable of1198830(1199110 1199110) characterized as the impulse

response of the wavefield occurred from a unit dipole sourceat 1199110and is further sensed by a unit pressure sensor at 119911

0 Also

the subscript ldquo0rdquo in 1198830symbolizes that earthrsquos surface has a

free reflection boundary that is a single round-trip (mean

Journal of Sensors 13

two-way time) has been estimated by the seismic signal fromthe subsurface (from 119911

0to 1199110) 1198830(1199110 1199110) has been utilized

as the multidimensional wavefield operator which definesthe wavefields at the reflection free acquisition surface 119911

0

119875

minus

0(1199110 1199110) as

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (25a)

or

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 120575119875

+(1199110 1199110)

+ 1198830(1199110 1199110) 119878

+

0(1199110 1199110)

(25b)

with combining

120575119875

+(1199110 1199110) = 119877

cap(1199110 1199110) 119875

minus

0(1199110 1199110) (25c)

In (25a) source matrix 119878

+

0(1199110) signifies the downgoing

wavefield of one physical source (array) at 1199110

However1198830119878

+ stands for the upgoing primary wavefields(one round-trip) and119883

0120575119875

+ stands for the upgoingmultiple-scattering wavefields (many round-trips)

Furthermore from (25a)ndash(25c) it can be simply derivedthat

1198830(1199110 1199110)

= [119868 minus 1198830(1199110 1199110) 119877

cap(1199110 1199110)]

minus1

1198830(1199110 1199110)

(26a)

representing the complexity of119883 relating to1198830 On compar-

ing (25a)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (26b)

with (25b)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) [120575119875

+(1199110 1199110) + 119878

+(1199110 1199110)] (26c)

Based on (26b) it can be concluded that the surface-related multiple-scattering phenomenon is incorporated intoa parameter 119883 However (26c) signifies that the surface-related multiple-scattering is incorporated into the downgo-ing wavefield 120575

119875

+

and the parameter 119883 determined as 1198830

Such variation between mathematical equations (26b) and(26c) assumes an imperative part in the inversion modelingfor seismic imaging [134]

Here Figure 16 represents the mixed shot record array offive sources at or near the surfaces Since during acquisitionzero time delays and large spacing between the sourcesare considered resulting incoherent shooting will becomesimultaneous shooting [136 139 140]The resultants imagingsignifies that a passive seismic recording can be measured asa naturally mixed shot record

312 Passive Seismic Imaging Method Based on DownwardRadiating Natural Sources Initially it is considered thatpseudo sources are set at or close to the surface (119911

0)

signifying that the background noise is considered as thosewavefields generated by the natural sources However in pas-sive seismic imaging response from natural sources has been

Tim

e (s)

30

25

20

15

10

05

00 1000 2000 3000 4000 5000

Lateral distance (m)

Figure 16 A mixed pseudo shot record generated by usingincoherent source array having five source elements at the surface[135 136]

considered as the seismic signal from the subsurface Thesesources might be set anyplace at the surface (119911 = 119911

0) and

in the subsurface (119911 gt 1199110) [137] Henceforth a noise model

has been createdwhichmay consider a continuing happeningseismic background noise as an indicator to determine theinformative data from these noises This concept is knownas seismic interferometry [141] Furthermore a relationshipby utilizing the wavefield diagram (see Figure 9) has beenestablished between the downgoing source wavefield at thesource level (119911

119899) and the up- and downgoing wavefields at

perception level 1199110(119911 = 119911

0) Such relation can be expressed

as

119875

+

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 119911119899)

119878

+

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110) [119882

minus1(1199110 119911119899)

119878

+

(119911119899)]

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110)

119878

+

(1199110 119911119899)

(27a)

where

119882

minus1(1199110 119911119899) = 119883

minus1

0(1199110 1199110)1198830(1199110 1199110) (27b)

Figure 17 describes the feed-forwarded model which isbased on modeling by downward radiating natural sourcesat and below the surface (119899 ge 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

313 Passive Seismic Imaging Method Based on UpwardRadiating Natural Sources In this phase like active seismicbackground noise similar type of natural sourcersquos responseis considered but the direction has been changed to the

14 Journal of Sensors

rarr(z0 zn)

W(zn z0)

Rcap(z0 z0)

rarr(zn)+X0(z0 zn)

120575rarr

(z0 zn)

n = 0 1 2 middot middot middot

Pminus

P+

S+

Figure 17 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

rarrPminus(z0 zn)

W(z0 zn)

Rcap(z0 z0)

rarrS (zn)

+ X0(zn z0)

120575rarrP (z0 zn)

n = 1 2

+

minus

Figure 18 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

contribution of ldquoupwardrdquo radiation Figure 18 depicts theresultants response which describes the correlation betweenthe upgoing source wavefields at the source level (119911

119899) and the

up- and downgoing wavefields at observation level 1199110 Such

result can be expressed as

119875

minus

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 119882(1199110 119911119899)

119878

minus

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899) +

119878

minus

(1199110 119911119899)

(28)

Figure 18 describes the feed-forwarded model which isbased on modeling by upward radiating natural sources atand below the surface (119899 gt 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

314 Statistical Description of the Modeling In the statisticalanalysis of the above designed model the above definedexpressions have been utilized on an exceptionally straight-forward medium Such medium has one horizontal reflectorand a free surface depicted in Figure 19 The stepwiseconstruction of thismedium signifies imaging in Figure 19(a)describing the conventional active seismic record where oneprimary and the surface multiples have been identified andindicated by a mathematical expression in (25b) In continu-ation Figure 19(b) describes the measurement of a responsefrom a downward radiating noise burst by implementing(27a) and (27b) while Figure 19(c) describes the upwardtransmitting patterns by estimating (28)

From these figures and equation implementation it isclearly defined that the occurrence of response and its mul-tiples takes place directly Moreover Figure 19(d) preciselydemonstrates the effect of such multiples that is the noisebursts being the summation of Figures 19(b) and 19(c)respectively

Figure 19 defines the straightforward medium whichhas one horizontal reflector and a stress-free surface HereFigure 19(a) describes the impulsive source at the surfacewhile Figure 19(b) shows at first layer the downward radiatingnoise source Similarly Figure 19(c) shows at first layerthe upward radiating noise source Finally Figure 19(d)establishes the omnidirectional noise source in the first layerof imagingOverall it has been signified that different sourcesdetermine the different resultant responses For exampleFigure 19 clearly proved this statement by demonstrating thatall sources defined here produce the different responses at ornear the subsurface of seismic imaging

32 Example Showing the Processing of Active and PassiveSeismic Imaging and Their Significance In this examplefor a mixed seismic data response inversion method fol-lowed for known and unknown sources is illustrated Herethree reflectors are utilized to measure the response forthe subsurface modeling (see Figure 20(a)) To begin withwithout considering surface-related multiples 119883

0 the mul-

tidimensional impulse response of the subsurface has beenproduced However Figures 20(b)ndash20(d) describe the three-column impulsive response of 119883

0 It results in naturally

occurring mixed recording at the subsurface Therefore inthe next modeling step surface-related multiples have beenimplemented that is from119883

0to119883

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

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[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

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[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

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[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

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[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

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[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

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[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

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[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

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[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

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[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

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[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

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[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

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[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

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[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

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Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

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DistributedSensor Networks

International Journal of

Journal of Sensors 13

two-way time) has been estimated by the seismic signal fromthe subsurface (from 119911

0to 1199110) 1198830(1199110 1199110) has been utilized

as the multidimensional wavefield operator which definesthe wavefields at the reflection free acquisition surface 119911

0

119875

minus

0(1199110 1199110) as

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (25a)

or

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 120575119875

+(1199110 1199110)

+ 1198830(1199110 1199110) 119878

+

0(1199110 1199110)

(25b)

with combining

120575119875

+(1199110 1199110) = 119877

cap(1199110 1199110) 119875

minus

0(1199110 1199110) (25c)

In (25a) source matrix 119878

+

0(1199110) signifies the downgoing

wavefield of one physical source (array) at 1199110

However1198830119878

+ stands for the upgoing primary wavefields(one round-trip) and119883

0120575119875

+ stands for the upgoingmultiple-scattering wavefields (many round-trips)

Furthermore from (25a)ndash(25c) it can be simply derivedthat

1198830(1199110 1199110)

= [119868 minus 1198830(1199110 1199110) 119877

cap(1199110 1199110)]

minus1

1198830(1199110 1199110)

(26a)

representing the complexity of119883 relating to1198830 On compar-

ing (25a)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) 119878

+

0(1199110 1199110) (26b)

with (25b)

119875

minus

0(1199110 1199110) = 119883

0(1199110 1199110) [120575119875

+(1199110 1199110) + 119878

+(1199110 1199110)] (26c)

Based on (26b) it can be concluded that the surface-related multiple-scattering phenomenon is incorporated intoa parameter 119883 However (26c) signifies that the surface-related multiple-scattering is incorporated into the downgo-ing wavefield 120575

119875

+

and the parameter 119883 determined as 1198830

Such variation between mathematical equations (26b) and(26c) assumes an imperative part in the inversion modelingfor seismic imaging [134]

Here Figure 16 represents the mixed shot record array offive sources at or near the surfaces Since during acquisitionzero time delays and large spacing between the sourcesare considered resulting incoherent shooting will becomesimultaneous shooting [136 139 140]The resultants imagingsignifies that a passive seismic recording can be measured asa naturally mixed shot record

312 Passive Seismic Imaging Method Based on DownwardRadiating Natural Sources Initially it is considered thatpseudo sources are set at or close to the surface (119911

0)

signifying that the background noise is considered as thosewavefields generated by the natural sources However in pas-sive seismic imaging response from natural sources has been

Tim

e (s)

30

25

20

15

10

05

00 1000 2000 3000 4000 5000

Lateral distance (m)

Figure 16 A mixed pseudo shot record generated by usingincoherent source array having five source elements at the surface[135 136]

considered as the seismic signal from the subsurface Thesesources might be set anyplace at the surface (119911 = 119911

0) and

in the subsurface (119911 gt 1199110) [137] Henceforth a noise model

has been createdwhichmay consider a continuing happeningseismic background noise as an indicator to determine theinformative data from these noises This concept is knownas seismic interferometry [141] Furthermore a relationshipby utilizing the wavefield diagram (see Figure 9) has beenestablished between the downgoing source wavefield at thesource level (119911

119899) and the up- and downgoing wavefields at

perception level 1199110(119911 = 119911

0) Such relation can be expressed

as

119875

+

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 119911119899)

119878

+

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110) [119882

minus1(1199110 119911119899)

119878

+

(119911119899)]

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 1198830(1199110 1199110)

119878

+

(1199110 119911119899)

(27a)

where

119882

minus1(1199110 119911119899) = 119883

minus1

0(1199110 1199110)1198830(1199110 1199110) (27b)

Figure 17 describes the feed-forwarded model which isbased on modeling by downward radiating natural sourcesat and below the surface (119899 ge 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

313 Passive Seismic Imaging Method Based on UpwardRadiating Natural Sources In this phase like active seismicbackground noise similar type of natural sourcersquos responseis considered but the direction has been changed to the

14 Journal of Sensors

rarr(z0 zn)

W(zn z0)

Rcap(z0 z0)

rarr(zn)+X0(z0 zn)

120575rarr

(z0 zn)

n = 0 1 2 middot middot middot

Pminus

P+

S+

Figure 17 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

rarrPminus(z0 zn)

W(z0 zn)

Rcap(z0 z0)

rarrS (zn)

+ X0(zn z0)

120575rarrP (z0 zn)

n = 1 2

+

minus

Figure 18 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

contribution of ldquoupwardrdquo radiation Figure 18 depicts theresultants response which describes the correlation betweenthe upgoing source wavefields at the source level (119911

119899) and the

up- and downgoing wavefields at observation level 1199110 Such

result can be expressed as

119875

minus

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 119882(1199110 119911119899)

119878

minus

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899) +

119878

minus

(1199110 119911119899)

(28)

Figure 18 describes the feed-forwarded model which isbased on modeling by upward radiating natural sources atand below the surface (119899 gt 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

314 Statistical Description of the Modeling In the statisticalanalysis of the above designed model the above definedexpressions have been utilized on an exceptionally straight-forward medium Such medium has one horizontal reflectorand a free surface depicted in Figure 19 The stepwiseconstruction of thismedium signifies imaging in Figure 19(a)describing the conventional active seismic record where oneprimary and the surface multiples have been identified andindicated by a mathematical expression in (25b) In continu-ation Figure 19(b) describes the measurement of a responsefrom a downward radiating noise burst by implementing(27a) and (27b) while Figure 19(c) describes the upwardtransmitting patterns by estimating (28)

From these figures and equation implementation it isclearly defined that the occurrence of response and its mul-tiples takes place directly Moreover Figure 19(d) preciselydemonstrates the effect of such multiples that is the noisebursts being the summation of Figures 19(b) and 19(c)respectively

Figure 19 defines the straightforward medium whichhas one horizontal reflector and a stress-free surface HereFigure 19(a) describes the impulsive source at the surfacewhile Figure 19(b) shows at first layer the downward radiatingnoise source Similarly Figure 19(c) shows at first layerthe upward radiating noise source Finally Figure 19(d)establishes the omnidirectional noise source in the first layerof imagingOverall it has been signified that different sourcesdetermine the different resultant responses For exampleFigure 19 clearly proved this statement by demonstrating thatall sources defined here produce the different responses at ornear the subsurface of seismic imaging

32 Example Showing the Processing of Active and PassiveSeismic Imaging and Their Significance In this examplefor a mixed seismic data response inversion method fol-lowed for known and unknown sources is illustrated Herethree reflectors are utilized to measure the response forthe subsurface modeling (see Figure 20(a)) To begin withwithout considering surface-related multiples 119883

0 the mul-

tidimensional impulse response of the subsurface has beenproduced However Figures 20(b)ndash20(d) describe the three-column impulsive response of 119883

0 It results in naturally

occurring mixed recording at the subsurface Therefore inthe next modeling step surface-related multiples have beenimplemented that is from119883

0to119883

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

[1] A E de Vasconcelos Lopes and L C Nunes ldquoPitfalls of tremor-like signals for hydrocarbon exploration in producing oil fieldsin Potiguar basin northeast Brazilrdquo The Leading Edge vol 29no 7 pp 826ndash830 2010

[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

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[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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DistributedSensor Networks

International Journal of

14 Journal of Sensors

rarr(z0 zn)

W(zn z0)

Rcap(z0 z0)

rarr(zn)+X0(z0 zn)

120575rarr

(z0 zn)

n = 0 1 2 middot middot middot

Pminus

P+

S+

Figure 17 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

rarrPminus(z0 zn)

W(z0 zn)

Rcap(z0 z0)

rarrS (zn)

+ X0(zn z0)

120575rarrP (z0 zn)

n = 1 2

+

minus

Figure 18 Feed-forwarded model for up- and downgoing wavefields modeled based on downward processing [137 138]

contribution of ldquoupwardrdquo radiation Figure 18 depicts theresultants response which describes the correlation betweenthe upgoing source wavefields at the source level (119911

119899) and the

up- and downgoing wavefields at observation level 1199110 Such

result can be expressed as

119875

minus

(1199110 119911119899) = 119883

0(1199110 1199110) 120575

119875

+

(1199110 119911119899)

+ 119882(1199110 119911119899)

119878

minus

(119911119899)

= 1198830(1199110 1199110) 120575

119875

+

(1199110 119911119899) +

119878

minus

(1199110 119911119899)

(28)

Figure 18 describes the feed-forwarded model which isbased on modeling by upward radiating natural sources atand below the surface (119899 gt 0) and recorded at the surface(1199110) Here the response parameter is a real estimation of a

source (array) at the depth level 119911119899

314 Statistical Description of the Modeling In the statisticalanalysis of the above designed model the above definedexpressions have been utilized on an exceptionally straight-forward medium Such medium has one horizontal reflectorand a free surface depicted in Figure 19 The stepwiseconstruction of thismedium signifies imaging in Figure 19(a)describing the conventional active seismic record where oneprimary and the surface multiples have been identified andindicated by a mathematical expression in (25b) In continu-ation Figure 19(b) describes the measurement of a responsefrom a downward radiating noise burst by implementing(27a) and (27b) while Figure 19(c) describes the upwardtransmitting patterns by estimating (28)

From these figures and equation implementation it isclearly defined that the occurrence of response and its mul-tiples takes place directly Moreover Figure 19(d) preciselydemonstrates the effect of such multiples that is the noisebursts being the summation of Figures 19(b) and 19(c)respectively

Figure 19 defines the straightforward medium whichhas one horizontal reflector and a stress-free surface HereFigure 19(a) describes the impulsive source at the surfacewhile Figure 19(b) shows at first layer the downward radiatingnoise source Similarly Figure 19(c) shows at first layerthe upward radiating noise source Finally Figure 19(d)establishes the omnidirectional noise source in the first layerof imagingOverall it has been signified that different sourcesdetermine the different resultant responses For exampleFigure 19 clearly proved this statement by demonstrating thatall sources defined here produce the different responses at ornear the subsurface of seismic imaging

32 Example Showing the Processing of Active and PassiveSeismic Imaging and Their Significance In this examplefor a mixed seismic data response inversion method fol-lowed for known and unknown sources is illustrated Herethree reflectors are utilized to measure the response forthe subsurface modeling (see Figure 20(a)) To begin withwithout considering surface-related multiples 119883

0 the mul-

tidimensional impulse response of the subsurface has beenproduced However Figures 20(b)ndash20(d) describe the three-column impulsive response of 119883

0 It results in naturally

occurring mixed recording at the subsurface Therefore inthe next modeling step surface-related multiples have beenimplemented that is from119883

0to119883

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

[1] A E de Vasconcelos Lopes and L C Nunes ldquoPitfalls of tremor-like signals for hydrocarbon exploration in producing oil fieldsin Potiguar basin northeast Brazilrdquo The Leading Edge vol 29no 7 pp 826ndash830 2010

[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

Journal of Sensors 25

[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Navigation and Observation

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DistributedSensor Networks

International Journal of

Journal of Sensors 15

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(a)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(b)

20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(c)20

15

10

05

0

Tim

e (s)

minus2000 minus1000 0 1000 2000

Offset (m)

(d)

Figure 19 Representing four distinctive estimation configurations and the corresponding upward travelling waves at the surface ( 119875

minus

) [137138]

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

[1] A E de Vasconcelos Lopes and L C Nunes ldquoPitfalls of tremor-like signals for hydrocarbon exploration in producing oil fieldsin Potiguar basin northeast Brazilrdquo The Leading Edge vol 29no 7 pp 826ndash830 2010

[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

Journal of Sensors 25

[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Chemical EngineeringInternational Journal of Antennas and

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Navigation and Observation

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DistributedSensor Networks

International Journal of

16 Journal of Sensors

1200

750

250

0

Dep

th (m

)

0 2000

Lateral position (m)

c = 1500ms

c = 2000ms

c = 3000msc = 2200ms

(a)

20

15

10

05

0

Tim

e (s)

minus500 0 500 1000 1500

Offset (m)

xi

(b) Source at 119909 = 500m20

15

10

05

0

Tim

e (s)

Offset (m)

xj

minus500 0 500 1000minus1000

(c) Source at 119909 = 1000m20

15

10

05

0

Tim

e (s)

minus500 0 500minus1000minus1500

Offset (m)

xk

(d) Source at 119909 = 1500m

Figure 20 A Subsurface modeling to generate active and passive seismic data [137 138]

According to Figure 20 a subsurface model has beencreated such that Figure 20(a) describes the formation of thesurfaces with their respective depths Here pseudo sourceshave been used for imaging placed at the surface (119911 =

0) It also considers the natural sources that are placed inthe subsurface between 119911 = 800 and 119911 = 1000m andrepresented as the green dots In continuing Figures 20(b)ndash20(d) demonstrate the three band-limited impulse responses(three columns of 119883

0) These responses occurred without

considering the internal multiplesFurthermore for clear demonstration first ldquoactiverdquo seis-

mic data are considered imaged by utilizing one incoherentarray of 81 P sources Such sources have been consideredin such a way that each source has known firing times andpositions at the surface (119911

0) Then the aggregate response

of the generated synthetic incoherent source array has beensimulated by superimposing 81 distinct shot records with avariation in delay time response This processing of imaging

is called blending process which results in the recordingtime of the resultant mixed measures up to 35 s From thisrecorded time 5 s has been demonstrated in Figure 21(a)where for active imaging the convolution of the responsehas been implemented by utilizing a nonzero phase sourcewavelet

In the second case ldquopassiverdquo image data has been imple-mented such that it consists of 35 unknown microseismicP sources The modeling of sources is in such a way thateach source has been placed below the second reflectordepicted in Figure 21(a) The reflectors in this modeling haverandom firing times having a response time of 5 s Howeverthe source signature of each hidden source considered avariant dispersive wavelet for convoluting with the responseto generate a passive image The final results estimated asa mixed recording occurred naturally at the subsurface andfinally such recorded time response with data has beenmodeled as shown in Figure 22(a)

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

[1] A E de Vasconcelos Lopes and L C Nunes ldquoPitfalls of tremor-like signals for hydrocarbon exploration in producing oil fieldsin Potiguar basin northeast Brazilrdquo The Leading Edge vol 29no 7 pp 826ndash830 2010

[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

Journal of Sensors 25

[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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DistributedSensor Networks

International Journal of

Journal of Sensors 17

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

(a) Blended minusrarrP

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(b) True minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrP(c) Estimated minus0

150

145

140

135

130

125

120

115

110

105

100

Tim

e (s)

500

1000

1500

2000

Lateral location (m)

rarrE(d) Residual minus0

Figure 21Mixed shot record (a) with and (b) without a reflecting surface (c) Resultant image obtained by subtracting the estimatedmultiplesfrom the input image data (d) Resultant image obtained by subtracting both estimated primaries and multiples from the input image data[140]

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(a) Passive Pminusrarr

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(b) True minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

rarrP(c) Estimated minus0

290

285

280

275

270

265

260

255

250

245

240

Tim

e (s)

0 500 1000 1500

Lateral location (m)

(d) Residual

Figure 22 (a) Simulated passive seismicmeasurements (a) with and (b) without a reflecting surface (c)Measured resultant data by deprivingsurface multiples lead to computing the source signatures (d) Remaining resultant data while subtracting the surface multiples and directsource wavefields [142 143]

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

[1] A E de Vasconcelos Lopes and L C Nunes ldquoPitfalls of tremor-like signals for hydrocarbon exploration in producing oil fieldsin Potiguar basin northeast Brazilrdquo The Leading Edge vol 29no 7 pp 826ndash830 2010

[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

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[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

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Active and Passive Electronic Components

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Submit your manuscripts athttpwwwhindawicom

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Chemical EngineeringInternational Journal of Antennas and

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DistributedSensor Networks

International Journal of

18 Journal of Sensors

70139

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(a)

70575

Frequency (Hz)

PSD

(au

)

0

05

1

15

2

25

3

4

35

1 2 3 4 5 6 7

(b)

Figure 23 Spectrum (solid line) representing the passive seismic wavefield (vertical surface velocities) from a frequency range of 05 to 74Hz[22]

Based on the experimental and modeling analysis activeseismic data responses generate more multiples than passiveseismic response Such multiples may affect the resultantimpulsive response of clear reservoir monitoring by poorimaging Since this model follows active seismic acquisitionit may consider the background noise as a seismic signalwhich provides the important information about the dynam-ics of the subsurface [143] But it may also affect the geologyof the reservoir by generating different multiples at differentbandwidth It also identifies that passive seismic recordingscan also generate the seismic multiples but by unknownnatural resources which may not affect the overall stratig-raphy of the subsurface Henceforth it has been concludedthat the total lack of information about the natural sources(firing time signature and position) becomes a key principaldifference between the active and passive seismic imagingmethods

4 Passive Seismic Surveys

A study analysis of the growing number of stratigraphysurveys over variant oil and gas fields signifies the exis-tence of spectral anomalies in the passive seismic wavefieldthat is microtremors having a high degree of relationshipwith the localization of hydrocarbon reservoirs [22 144ndash151] Such microtremors work as a reservoir indicator tooptimize the well placement during exploration appraisaland development However in consideration of the conven-tional seismic technologies the microtremor which inves-tigates the hydrocarbon reservoir is generally passive Suchmicrotremors work in such a way that they do not requirepseudo seismic sources for excitation A broad review over

a tight gas reservoir and an adjoining exploration area inMexico has been considered for data analysis The data haveseveral hundred stations with three-component broadbandseismometers placing over approximately 200 km2 for thedata analysis [22] Experiments on worldwide sites withknown hydrocarbon reserves were initially reported [2] Atnarrow frequency range of 15ndash4Hz and amplitude 001ndash10 120583ms a tremor-like signal has been observed in definedlocation Similar observations were also found in Volga-Uraloil bearing province in Tarasan [6] and inMexico for tight gasfield (see Figure 23) [22 144]

The reservoir system named Paleocene Wilcox has fourfundamental production intervals such that the top deltaicsequences are considered best producers followed by threemore layers of sandstone The total sand thickness varyingbetween 120 and 30m occurred by block-nose erosion onthe shallowest compartments having faulting blocks andvariation in lateral thickness of the sediments Here 20ultrasensitive portable three-component (3-C) broadbandseismometers (frequency range 003ndash50Hz sampling rate100Hz sensitivity 1500Vms) have been utilized for theacquisition of more than 700 estimations of the omnipresentseismic wavefield at the surface over around 200 km [22]In continuing with the data analysis the data acquisitionhas two-matrix layout acquired continuously over a 3-monthperiod having 1000m node spacing The only differencebetween the twomatrixes is that secondmatrix has staggeredoffset in comparison to the middle of the first matrixwhich may lessen the average spacing between the nodes to700m

According to Figure 23 the dashed line shows thestandard deviation of the mean spectrum Figure 23(a)

Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

[1] A E de Vasconcelos Lopes and L C Nunes ldquoPitfalls of tremor-like signals for hydrocarbon exploration in producing oil fieldsin Potiguar basin northeast Brazilrdquo The Leading Edge vol 29no 7 pp 826ndash830 2010

[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

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[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

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DistributedSensor Networks

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Journal of Sensors 19

shows recorded station named 70139 over a known gasfield while Figure 23(b) recorded a station named 70575over a range with no hydrocarbon potential [22] A linearfrequency scale has been used to estimate the shaded surfaceillustrated as PSD-IZ value Here the amplitudes for bothstations have been compared directly without applying ascaling factor Noise floor variations have been consideredin the data obtained by estimating the individual minimumamplitude of each spectrumwithin a frequency range of 1 and17Hz The survey analysis shows a minimum in this rangesignifying that slight variation in the frequency range hasbeen considered for the next surveys [144] The integral overthis minimum amplitude computes the PSD-IZ value whereIZ describes the integral of the 119911-component It considersthe whole energy anomaly over a well-defined backgroundlevel (ie the minimum within a frequency range of 1 and17Hz) which has not been restricted to peak strength atspecific frequencies Thusly uncertain high amplitude peaksappeared because of human activity at the surface (eg thenarrowband peaks at a frequency range of 25 and 3Hz inFigure 15) which signifies that it has not contributed to thePSD-IZ values [22 144 145]

41 Maximum Spectrum Peaks by Using Frequency ShiftAccording to frequency shift it has been observed that thespectrum over hydrocarbon reservoirs consists of spectralpeaks within a narrow frequency range of 15ndash4Hz recog-nized as oil- and gas-reserves [144] This survey shows thatthe spectral peaks have been appearing over the acquired dataspectra having a variable frequency range (eg at 25 3 4 and5Hz) depicted in Figure 23 However the number of peaksand their relativeabsolute amplitudes have larger variationwith the variation of time and location Such variationcreates a difficulty in the making of consistent map whichfollows the average amplitudes of the estimated spectra [144]Therefore this method focused on estimating the frequencyvalues corresponding to the maximum spectral peak ratherthan amplitude spectra This may help in providing the trueinformation about the anomalies such that amost significantpeak frequency has been estimatedwithin the frequency bandof interest

According to Figure 24 the specific frequency of themax-imum spectra peak has been considered having a range from15Hz to 37Hz by applying standard Kriging interpolationHere the estimated source signature shows independencyfrom the PSD-IZ and VH attributes as shown in Figure 23Finally two areas have been identified which have a relativelyhigh-frequency signature such that [150]

(i) first area signifies the survey having producing area(solid ellipse)

(ii) second area represents an exploration zone (dashedcircle)

Moreover it has been concluded that the data utilizedhere is on the surface a complicated mixture of variantwave types and location However it has been identifiedthat survey area has stable trends which may consist of thepolarization attributes in the frequency band between 1 and

Peak frequency

0 1 2 4(km)

gt24Hz

20ndash24Hz

18ndash20Hz

lt18Hz

Figure 24 A determining survey map of the formation havingfrequency of the maximum peak within a frequency range from15Hz (blue) to 37Hz (red) [22 144]

37Hz In Figure 17 there is a direct correlation between theestimated PSD-IZ values and the computed drainage radiiof the production wells Since the production noise sources(eg tube waves or pumps) have unlikely explanation atthe surface still some ambiguity remains such as formationconduction It is because of the production reservoir whichmay not be strictly suited with a seismic area (ie productionfacilities)

42 Seismic Attributes Predicted Hydrocarbon versus DrilledWells Based on Determined Survey According to the explo-ration zone of this survey one big PSD-IZ energy patternis observed which has been marked with a dashed circle inFigure 16 The interpretation of VH signal and the relativelyhigh frequency at maximum peak in Figure 16 signifies aprecise indicator for hydrocarbons prediction [146] Hencetwo successful wells have been drilled in this determinedzone where generated passive seismic data signifies the exis-tence of gas-bearing sediments (see Figure 25)This resultantoccurrence of gas-bearing represents a lower production ratewhichmay cause the reservoir rock to be less permeable [147]Since the wells have been drilled after the survey has beendetermined the predictive attributes indicating hydrocarbonpresence are not affected by the production activity orother significant human activity in the vicinity Thereforesuccessful production wells at production zone 2 define thezone with a relatively high PSD-IZ value (Figure 25) [22]

Seismic tremors with different spectral densities wererecorded using ultrasensitivemulticomponent seismometersDrilled wells after the survey confirmed that tremor signalswere related to presence of gas in subsurface The exactfield productivity depends on the reservoir permeabilityTherefore it could not be directly inferred from passiveseismic data [1 29] The literature study signifies that the

20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

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[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

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[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

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[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

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[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

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[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

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[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

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[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

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[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

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[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

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[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

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[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

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[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

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[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

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Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

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DistributedSensor Networks

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20 Journal of Sensors

0 1 2 4(km)

0 1 2 4(km)

PSD-IZ0ndash150150ndash500500ndash12401240ndash5000

Well statusWells drilled after the survey

NonproductiveLow productionProducer

(a)

(b)

Figure 25 Correlation example taken from [22] between PowerSpectral Density (PSD) of passive seismic survey and well drilledafter the survey (a) Power spectral Density in119885 direction (PSD-IZ)(b) status of well drilled after the survey [22]

observed tremor signals have been correlated with hydro-carbon reservoir for the supplying seismic-acoustic energyfor filteringmixing hydrocarbon impacts on reservoir sub-surface [2 5 6 8 21 22 44 127] However others haveexpressed some doubts on underlying theory of the techniqueand its applicability to different geologies and its repeatability[24 29 41]

Passive seismic signals are narrow banded (1ndash30Hz asshown in Table 10) of low frequency and of low amplitudefor instance the peak ground acceleration (PGA) for tremorsignals can fall below 80mg for passive seismic [7 22 32]Low cost and environmentally friendly features of passiveseismicmake it an economically viable option It also signifiesfrom Table 10 that capacitive MEMS based accelerometer isbetter than otherMEMS based accelerometers in the carbon-ate reservoir This capacitive accelerometer determines thatself-noise level signifies 98 ngradicHz at periods below 02 s(frequencies above 5Hz)

However analysis and processing of seismic data signifythat the very low end of the seismic spectrum under 10Hzconsists of precise information for the direct identificationof hydrocarbon reservoirs [143] and also acts as a universaldirect hydrocarbon indicator (DHI) [152] Such results deter-mine the improved possibilities for localizing the productionzone accurately potentially helping in reducing costs indrilling and well production

Furthermore passive seismic sensing describes its neces-sity in the low frequency spectral region due to the factthat the man-made seismic energy generator (like vibrators)critically affects the formation and does not have muchcapability to produce sufficient energy in the low frequencies

area neededTherefore it requires a significant type of passiveseismic sensors like geophones and MEMS seismic sensorswith conventional sensing below the frequency spectrumless than 10Hz Hence based on the passive seismic sensingrequirement a survey has been made as shown in Table 11

The survey depicted in Table 11 signifies that passiveseismic may require seismometers having high broadbandor special low frequency geophones such as the IO LF-24and the Geospace HS-10 [31 143 152] However these sensorshave a relatively higher cost of installation and alsomay repre-sent their fragile nature leading to designing a passive seismicsensor of an expensive consideration Hence a low frequencysensor named Molecular Electronic Transducers (MTLF-1040) Low Frequency Sensor has been discovered MTLF-1040 defines improved performance in the low frequencyspectral bandwidth (Table 15) It also produces a highersensitivity than conventional 1Hz and 45Hz geophones withlesser cost estimation at the low frequencies formation [31]

5 Technology Gap of Sensors

Sensors performance in low frequency measurement is poordue to the physical limitations of sensing elements [23 153]The measurement of the tremor signals is demanding highresolutionwhich is inversely affected by device noiseThis canbe explained by recalling the 24-bit modern standard digitaloutput of seismic sensors [8] Considering full scale of 80mgthe minimum detectable acceleration would be 47 ng Theminimum detectable acceleration is a function of the noisefloor and the bandwidth as shown in following expression

119886min =radic119886

2

119899radicBW

(29)

According to (29) for 30Hz bandwidth the collectivenoise floor should therefore be less than 1 ngradicHz Theequation also shows the adverse effect of excessive bandwidthon the minimum detectable acceleration On the otherhand having a large full acceleration would adversely affectthe sensitivity which has been described as the total ratiobetween maximum output voltage 119881m and the maximumacceleration 119886m as shown in

119878 =

119881m119886m

(30)

Additionally sensors from leading technology providers(illustrated in Figure 17 and Table 10) however are not fullycapable of capturing passive seismic signals This is mainlydue to their wide bandwidth [18 23 33] larger full scale [1823] and low noise performance at low frequencies [18 32]

High resolution acquisition for microtremor signals isa crucial market concern for passive seismic hydrocarbonexploration studies The technological gap between appli-cation requirements and performance offered by availableand emerging accelerometers motivates the development ofdedicated sensing technology As a result the measurementresolution is inversely affected This can be explained byrecalling the 24-bit standard output implying a noise densitylt4 ngrtHz [63 153] This noise density has not been met

Journal of Sensors 21

Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

[1] A E de Vasconcelos Lopes and L C Nunes ldquoPitfalls of tremor-like signals for hydrocarbon exploration in producing oil fieldsin Potiguar basin northeast Brazilrdquo The Leading Edge vol 29no 7 pp 826ndash830 2010

[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

Journal of Sensors 25

[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

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Table 10 Hydrocarbon microtremor signal bandwidth

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

15 4 Seismoacousticbackground

Narrowbandlow frequency

tremors[1]

Highly sensitiveground motion

velocityreceivers gasreservoir

1-s or 2-slt1000Vms

The signals weaken at the rim of thereservoirs and are not observed

outside the reservoir areaSeismic-acoustic background noise

differs widely

1 6 Passive seismiclow frequency

Low frequencymicrotremors

[4]

Tight gasreservoir and an

adjacentexploration area

1500Vms

Requiring careful data analysisusing microtremors around

reservoirs with considerable noise(eg production noise) because (a)anomalies caused by noise can bemisinterpreted as being caused by

the reservoir or (b) such ahigh-noise environment can

overwhelm the signal

25 7 MicroseismicLong-periodmicrotremor

[3]

Sedimentarybasin Not specified Nature of the soil showing variation

in resonance properties

1 10 Passive seismiclow frequency

Microtremor[24]

Basement rockwith oil bearing

capabilityNot specified

Variation in the field of microseismsdue to the level of anthropogenic

noise

19 3 Passive seismiclow frequency

3-C broadbandseismometer

[29]Giant oil field Not specified

Identifying low energy attributeshowing low potential

Required improvement in dataacquisition and processing

methods

2 13 Passive seismic Microtremor[17]

Sedimentarybasin of the

lower cretaceous1600Vms Identified wide variation in the data

resolution in depth

1 4 Passive seismiclow frequency

3-C broadbandseismometer

[18]

Appraisal wellwith partiallysaturated oilreservoir

0025 to 5HzAcquired data unable to distinguish

between a purely elastic and aviscoelastic scattering process

1 6 Low frequencypassive seismic

3-C broadbandseismometer [3]

Stackedreservoirs of

lower cretaceous(carbonatereservoir)

2000VmsMicrotremor signal has no clearcorrelation with the microseism

signals

00125 625 Microseismic

Hewlett-Packard (HP)Microelec-

tromechanicalSystems

(MEMS) seismicaccelerometer(capacitivesensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis of self-noise levelsignifies 98 ngradicHz at periods

below 02 s(frequencies above 5Hz)

by current or emerging technologies It also demands adedicated solution for the development of sensing technologyto achieve high resolution signal acquisition for passiveseismic This helps in providing better data acquisition anddata analysis technique for higher success rate of predictionof hydrocarbon reserves

The first column of Table 12 shows the sensing typeof accelerometers The bandwidth acceleration range andnoise floor levels are listed in columns 2ndash4 Recalling fromSection 5 and Table 12 signals required in passive seismicsurvey are having maximum acceleration of lt80mg andbandwidth of 1ndash30Hz with lt4 ngradicHz noise spectral density

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

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[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

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[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

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[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

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[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

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[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

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[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

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[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

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[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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RotatingMachinery

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Submit your manuscripts athttpwwwhindawicom

VLSI Design

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Shock and Vibration

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Navigation and Observation

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DistributedSensor Networks

International Journal of

22 Journal of Sensors

Table 11 Survey based on type of devices used for seismic data acquisition [31]

Parameters

MolecularElectronicTransducers(MET) Sensor

Geophones MEMSaccelerometers Implication

Frequency range 1ndash500Hz 10ndash190Hz DC ndash 1000Hz Better imaging of deep shallowandor narrow layers of deposits

Scale factorstability lt50 ngradicHz lowast 500 ngradicHz Higher data quality

Sensor noise Low Low Moderate Higher data qualitySensitivity High Low Low Longer life in the field

Shock tolerance Very high Moderate High Usable in a wider range ofsurveys

Electromagneticinterference No Yes No No power line pickup better data

with less processing required

Power Low Low High Less expensive to operate longerbattery life

Cost Low-med Low High Lower equipment cost

Table 12 State-of-the-art sensors

Sensor Type Bandwidth (Hz) Full scale (mg) Noise density (ngrtHz)Trillium T40 T120 [32] Velocimeter 003ndash50 mdash mdashGeophone accelerometer [23] Accelerometer 3ndash200 108 15DSU1 [18] Accelerometer 0ndash800 500 40 (gt10Hz)Emerging sensor [33] Accelerometer 1ndash200 80 10

Table 13 Sensors performance summary [6 7 34ndash39]

Type Bandwidth (Hz) Acceleration (g) Noise density(gradicHz)

Capacitive 0ndash30 22 120583ndash20 k 4 nndash357mPiezoresistive 0ndash35 1ndash250 100120583ndash500mPiezoelectric 1ndash60 7ndash25 10mndash110mTunneling 5ndash1 k 1mndash30 15 nndash4m

[38 40 154 155] The data summarized in Table 13 showthe superiority of capacitive sensors to meet passive seismicsensing requirements

6 Conclusions

Empirical studies show that the spectral anomalies withinthe range of 1ndash30Hz are highly correlated to determine thereservoir containing hydrocarbonThe overall study signifiesthat capacitive sensor is more suitable for meeting the passiveseismic sensing requirements with respect to the formation(Table 14) Cost-effective and environmental friendly featuresof passive seismic technique make it economically viableoption

Thus this paper signifies the sensing technology gapassociated with the acquisition of high resolution passiveseismic signals which has been discussed to motivate thededicated solutions for future However passive seismicsensors determine a relatively higher cost of installation and

also may represent their fragile nature at the low frequencybandwidth below 10Hz Therefore Molecular ElectronicTransducers (MTLF-1040) Low Frequency Sensor has beenidentified as an improved solution of the issues with passiveseismic sensors by performing better in the low frequencyspectral bandwidth It also produces a higher sensitivity thanconventional seismometers and geophones with lesser costestimation Since it has low output impedance it reducesoverdamping which makes its compatible with any devicesfor passive seismic sensing more accurately

Overall the whole study signifies the effectively correcteddifference between the active and passive seismic imagingusing a novel accelerometer design such as the following

(i) Active imaging totally depends on a clear signal-to-noise ration because ldquonoise is badrdquo

(ii) Passive imaging performs beyond the noise infometrywhere ldquonoise is goodrdquo since it signifies the informa-tion carrier and driving force

Since it is essential to understand that for reservoirresponse the secondary signal is generated inside the reser-voir as the adaptation product which cannot exist beforethat means it is considered as original source signal recordedwhich cannot be changed and recreated again Therefore apassive seismic method potentially offers a wide range ofpossibilities of recording real source signal with good noiseratio This may help in determining the accurate informationof the reservoir response reservoir monitoring and itsmanagement effectively

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

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[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

Journal of Sensors 25

[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

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Active and Passive Electronic Components

Control Scienceand Engineering

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RotatingMachinery

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Submit your manuscripts athttpwwwhindawicom

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DistributedSensor Networks

International Journal of

Journal of Sensors 23

Table 14

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition Type of device used Type of

reservoir Sensitivity Analysis

00125 625 Microseismic

Hewlett-Packard (HP)MicroelectromechanicalSystems (MEMS) seismicaccelerometer (capacitive

sensor)[30]

Not specified

33616119864 + 7

countsVndash84165119864 + 6

countsV

The analysis ofself-noise level

signifies98 ngradicHz atperiods below

02 s(frequenciesabove 5Hz)

Table 15

Min freq(Hz)

Max freq(Hz)

Type of dataacquisition

Type of deviceused

Type ofreservoir Sensitivity Analysis

1 500 Low frequencypassive seismics

MolecularElectronicTransducers(MTLF-1040)Low Frequency

Sensor[31]

Not specified High

(i) Longer life inthe field withimproved

passive seismicsensing

(ii) Lesser costestimation forinstallation

Table 16 Comparison of existing MEMS accelerometers [30 36ndash38 40]

Manufacturer Model Technology Output Axis Sensitivity Power (mW) Accelerationrange (g)

Frequencyresponse(Hz)

Colibrys

SF 1500 Capacitive Alowast 1 12mvg 100 plusmn3 0ndash1500SF 2005 Capacitive A 1 500mvg 140 plusmn4 0ndash1000SF 3000 Capacitive A 3 12mvg 200 plusmn3 0ndash1000

Digital 3 Capacitivefeedback Dlowast 3 58mgbit 780 plusmn02 0ndash1000

Endevco 86 Piezoelectric A 1 10 vg 200 plusmn05 0002ndash20087 Piezoelectric A 1 10 vg 200 plusmn05 0003ndash200

Kinemetrics ES-T Capacitive A 1 10 vg 144 plusmn025 0ndash200ESU2 Capacitive A 3 10 vg 100 plusmn025 0ndash200

Reftek 131 A Capacitive A 3 2 vg 600 plusmn35 0ndash400

SercelDSU1 Capacitive D 3 Not specified 265 plusmn05 0ndash800DSU2 Capacitive D 3 Not specified 265 plusmn05 0ndash800DUS3 Capacitive D 3 Not specified 265 plusmn05 0ndash800

Alowast = analog Dlowast = digital

Appendix

For more details see Table 16

Competing Interests

The authors declare that they have no competing interests

Acknowledgments

Atul Kumar sincerely would like to thank the supervisorDr M H Md Khir and cosupervisor Mr Wan Ismail Wan

Yusoff for his exemplary guidance and technical assistanceduring this study Atul Kumar also would like to thank Uni-versiti Teknologi PETRONAS for their financial assistance

References

[1] A E de Vasconcelos Lopes and L C Nunes ldquoPitfalls of tremor-like signals for hydrocarbon exploration in producing oil fieldsin Potiguar basin northeast Brazilrdquo The Leading Edge vol 29no 7 pp 826ndash830 2010

[2] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquo

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

Journal of Sensors 25

[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

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RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

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Civil EngineeringAdvances in

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Electrical and Computer Engineering

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The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Chemical EngineeringInternational Journal of Antennas and

Propagation

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DistributedSensor Networks

International Journal of

24 Journal of Sensors

Journal of Volcanology and Geothermal Research vol 128 no 1ndash3 pp 135ndash158 2003

[3] M A Gamal ldquoUsing microtremors for microseismic zonationin Cairorsquos crowded urban areasrdquo Journal of Seismology vol 13no 1 pp 13ndash30 2009

[4] A Goertz B Schechinger B Witten M Koerbe and PKrajewski ldquoExtracting subsurface information from ambientseismic noisemdasha case study from Germanyrdquo Geophysics vol 77no 4 pp KS13ndashKS31 2012

[5] A Kumar M H M Khir and W I W Yusoff ldquoA model basedapproach for integration analysis of well log and seismic data forreservoir characterizationrdquo Geoscience Journal pp 1ndash20 2016

[6] E V Birialtsev E V Eronina D A Rizhov V A Rizhov NY Shabalin and A A Vildanov ldquoExperience in low-frequencyspectral analysis of passive seismic data in volga-ural oil-bear-ing provincerdquo in International Petroleum Technology Conference(IPTC rsquo09) pp 2095ndash2105 December 2009

[7] B BirkeloMDuclos BArtman et al ldquoApassive low-frequencyseismic survey in Abu Dhabi-Shaheen projectrdquo in Proceedingsof the 2010 SEG Annual Meeting pp 2207ndash2211 Denver ColoUSA 2010

[8] N Riahi B Birkelo and E H Saenger ldquoAnalyzing passiveseismic attributes a statistical strategyrdquo in Proceedings of theSEG San Antonio 2011 Annual Meeting pp 1688ndash1692 SanAntonio Tex USA 2011

[9] FMohd-YasinD J Nagel andC E Korman ldquoNoise inMEMSrdquoMeasurement Science and Technology vol 21 no 1 22 pages2010

[10] T B Gabrielson ldquoMechanical-thermal noise inmicromachinedacoustic and vibration sensorsrdquo IEEE Transactions on ElectronDevices vol 40 no 5 pp 903ndash908 1993

[11] Z Djuric ldquoMechanisms of noise sources in microelectrome-chanical systemsrdquoMicroelectronics Reliability vol 40 no 6 pp919ndash932 2000

[12] Z Djuric O Jaksic and D Randjelovic ldquoAdsorption-desorp-tion noise inmicromechanical resonant structuresrdquo Sensors andActuators A vol 96 no 2-3 pp 244ndash251 2002

[13] A Greiner and J Korvink ldquoExtraction of noise parametersfor the macro modelling of MEMSrdquo in Proceedings of theInternational Conference on Advanced Semiconductor Devicesand Microsystems pp 311ndash314 1998

[14] J R Vig and Y Kim ldquoNoise in microelectromechanical systemresonatorsrdquo IEEE Transactions on Ultrasonics Ferroelectricsand Frequency Control vol 46 no 6 pp 1558ndash1565 1999

[15] R P Leland ldquoMechanical-thermal noise inMEMS gyroscopesrdquoIEEE Sensors Journal vol 5 no 3 pp 493ndash500 2005

[16] J Laine and D Mougenot ldquoBenefits of MEMS based seis-mic accelerometers for oil explorationrdquo in Proceedings of theInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo07) pp 1473ndash1477 IEEE LyonFrance June 2007

[17] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipementrdquo Technical Specifications West-ernGeco Crawley UK 2012

[18] D Mougenot and A Cherepovskiy ldquoDSU1 a single sensor thatmakes senserdquo Digital Sensor Unit-1 Sercel pp 1-2 2011

[19] D JMilligan BDHomeijer andRGWalmsley ldquoAnultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proceedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[20] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Milpitas Calif USA 2009

[21] R Holzner P Eschle M Frehner S Schmalholz and YPodladchikov ldquoInterpretation of hydrocarbon microtremors asnonlinear oscillations driven by oceanic background wavesrdquo inProceedings of the SEG Annual Meeting pp 2294ndash2298 SEGNew Orleans La USA 2006

[22] E H Saenger S M Schmalholz M-A Lambert et al ldquoApassive seismic survey over a gas field analysis of low-frequencyanomaliesrdquo Geophysics vol 74 no 2 pp O29ndashO40 2009

[23] WesternGeco ldquoUniQ integrated point-receiver land seismicsystem ground equipmentrdquo Technical Specifications West-ernGeco Crawley UK 2012

[24] F Martini I Lokmer K Jonsdottir et al ldquoA passive low-frequency seismic experiment in the Albertine GrabenUgandardquo Geophysical Prospecting vol 61 supplement 1 pp39ndash61 2013

[25] SMolnar J Cassidy PMonahan and T Onur ldquoEarthquake siteresponse studies using microtremor measurements in south-western British Columbiardquo in Proceedings of the 9th CanadianConference on Earthquake Engineering pp 410ndash419 2007

[26] D J Milligan B D Hom and R G Walmsley ldquoAn ultra-lownoiseMEMS accelerometer for seismic imagingrdquo in Proccedingsof the IEEE Sensors pp 1281ndash1284 Limerick Ireland October2011

[27] J F Tan R R Stewart and JWong ldquoClassification ofmicroseis-mic events via principal component analysis of trace statisticsrdquoCrewes Research Reports pp 1ndash11 2009

[28] S Sarkar H Sadi Kuleli M Nafi Toksoz et al ldquoEight years ofpassive seismic monitoring at a petroleum field in Oman a casestudyrdquo SEG Technical Program Expanded Abstracts pp 1397ndash1401 2008

[29] M Y Ali K A Berteussen J Small and B Barkat ldquoLow-frequency passive seismic experiments in Abu Dhabi UnitedArab Emirates implications for hydrocarbon detectionrdquo Geo-physical Prospecting vol 58 no 5 pp 875ndash899 2010

[30] B D Homeijer D J Milligan and C R Hutt ldquoA brief test of thehewlett-packard mems seismic accelerometerrdquo US GeologicalSurvey Open-File Report 2014ndash1047 2014

[31] Geophysics Internal Sensors METTech httpmettechnologycomProductsMTLF1040pdf

[32] J Thorbecke and K Wapenaar ldquoAnalysis of spurious eventsin seismic interferometryrdquo SEG Technical Program ExpandedAbstracts vol 27 no 1 pp 1415ndash1420 2008

[33] ldquoLecture note on lsquoAssessing MEMS Accelerometers Perfor-mancersquordquo MEM224 Experimental Engineering NorthwesternUniversity 2006

[34] A Ahanchian and B Y Majlis ldquoSimulation of an analogdifferential capacitive accelerometerrdquo in Proceedings of the IEEEInternational Conference on Semiconductor Electronics (ICSErsquo04) pp 331ndash334 December 2004

[35] G L Pavlis ldquoImaging the earth with passive seismic arraysrdquoTheLeading Edge vol 22 no 3 pp 224ndash231 2003

[36] K Wapenaar J van der Neut and E Ruigrok ldquoPassiveseismic interferometry by multidimensional deconvolutionrdquoGeophysics vol 73 no 6 pp A51ndashA56 2008

[37] S Wilson R Jones W Wason D Raymer and P JaquesldquoPassive seismicmakes sense for 4D reservoirmonitoringrdquo FirstBreak vol 22 no 10 pp 59ndash65 2004

[38] Nanometrics Trillium 40 Seismometer User Guide Nanomet-rics Ottawa Canada 2009

Journal of Sensors 25

[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

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Electrical and Computer Engineering

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The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Chemical EngineeringInternational Journal of Antennas and

Propagation

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Navigation and Observation

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DistributedSensor Networks

International Journal of

Journal of Sensors 25

[39] C Bland Henry ldquoAn analysis of passive seismic recordingperformancerdquo Crewes Research Reports vol 18 pp 1ndash9 2006

[40] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory 2009

[41] S I Kaka ldquoPassive microseismic experiments at King FahdUniversity of Petroleum andMinerals in Saudi Arabiardquo Seismo-logical Research Letters vol 83 no 4 pp 680ndash685 2012

[42] A Kannan Design and modeling of a MEMS-based accelerom-eter with pull in analysis [MS thesis] The University of BritishColumbia 2008

[43] M Haris and H Qu ldquoA CMOS-MEMS piezoresistive acceler-ometer with large proof massrdquo in Proceedings of the 5thIEEE International Conference on NanoMicro Engineered andMolecular Systems (NEMS rsquo10) pp 309ndash312 Xiamen ChinaJanuary 2010

[44] S Beiszligner M Puppich S Butefisch S Buttgenbach and TElbel ldquoAnalog force feedback circuit for capacitive microme-chanical acceleration sensorsrdquo inProceedings of the SensorsMay2001

[45] K Zhang Sensing and control of MEMS accelerometers usingKalman filter [MS thesis] Cleveland State University Cleve-land Ohio USA 2010

[46] H Qu D Fang and H Xie ldquoA monolithic CMOS-MEMS 3-axis accelerometer with a low-noise low-power dual-chopperamplifierrdquo IEEE Sensors Journal vol 8 no 9 pp 1511ndash1518 2008

[47] Q Zou W Tan E S Kim and G E Loeb ldquoSingle- andtriaxis piezoelectric-bimorph accelerometersrdquo Journal ofMicro-electromechanical Systems vol 17 no 1 pp 45ndash57 2008

[48] T Cui and J Wang ldquoPolymer-based wide-bandwidth and high-sensitivity micromachined electron tunneling accelerometersusing hot embossingrdquo Journal of Microelectromechanical Sys-tems vol 14 no 5 pp 895ndash902 2005

[49] S Chen C Xue W Zhang J Xiong B Zhang and J Hu ldquoAnew type of MEMS two axis accelerometer based on siliconrdquoin Proceedings of the 3rd IEEE International Conference onNanoMicro Engineered and Molecular Systems (NEMS rsquo08) pp959ndash964 Sanya China January 2008

[50] S Beepy G Ensell M Kraft and N WhiteMEMS MechanicalSensors Artech House Norwood Mass USA 2004

[51] A A Barlian W-T Park J R Mallon Jr A J Rastegarand B L Pruitt ldquoReview semiconductor piezoresistance formicrosystemsrdquo Proceedings of the IEEE vol 97 no 3 pp 513ndash552 2009

[52] D V Dao S Okada T Van Dau T Toriyama and SSugiyama ldquoDevelopment of a 3-DOF silicon piezoresistivemicro accelerometerrdquo in Proceedings of the International Sympo-sium on Micro-NanoMecahtronics and Human Science and the4th Symposium Micro-NanoMechatronics for and Information-Based Society vol 2004 pp 1ndash6 November 2004

[53] A Partridge J K Reynolds B W Chui et al ldquoA high-performance planar piezoresistive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 9 no 1 pp 58ndash66 2000

[54] N Yazdi F Ayazi and K Najafi ldquoMicromachined inertialsensorsrdquo Proceedings of the IEEE vol 86 no 8 pp 1640ndash16581998

[55] S Huang X Li Y Wang et al ldquoA piezoresistive accelerometerwith axially stressed tiny beams for both muchrdquo in Proceedingsof the 12th International Conference on Solid State SensorsActuators andMicrosystems pp 91ndash94 BostonMass USA June2003

[56] W-T Park A Partridge R N Candler et al ldquoEncapsulatedsubmillimeter piezoresistive accelerometersrdquo Journal of Micro-electromechanical Systems vol 15 no 3 pp 507ndash514 2006

[57] A Chaehoi L Latorre P Nouet and S Baglio ldquoPiezoresistiveCMOS beams for inertial sensingrdquo in Proceedings of the IEEESensors Conference pp 451ndash456 October 2003

[58] R Amarasinghe D V Dao T Toriyama and S SugiyamaldquoA silicon micromachined six-degree of freedom piezoresistiveaccelerometerrdquo in Proceedings of the IEEE Sensors vol 2 pp852ndash855 October 2004

[59] E Gallasch D Rafolt M Moser et al ldquoInstrumentation forassessment of tremor skin vibrations and cardiovascular vari-ables in MIR space missionsrdquo IEEE Transactions on BiomedicalEngineering vol 43 no 3 pp 328ndash333 1996

[60] R Amarasinghe D V Dao and S Sugiyama ldquoUltra miniature120583-accelerometer for wearable physical activity monitoring sys-temsrdquo in Proceedings of the International Symposium on Micro-NanoMechatronics and Human Science (MHS rsquo09) pp 467ndash471IEEE Nagoya Japan November 2009

[61] M Messina J Njuguna V Dariol C Pace and G AngelettildquoDesign and simulation of a novel biomechanic piezoresistivesensor with silicon nanowiresrdquo IEEEASME Transactions onMechatronics vol 18 no 3 pp 1201ndash1210 2013

[62] Q Zou W Tan E S Kim and G E Loeb ldquoHighly symmetrictri-axis piezoelectric bimorph accelerometerrdquo in Proceedingsof the 17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 197ndash200 January 2004

[63] S Chen C Xue B Zhang B Xie and H Qiao ldquoA novel MEMSbased piezoresistive vector hydrophone for low frequencydetectionrdquo in Proceedings of the IEEE International Conferenceon Mechatronics and Automation (ICMA rsquo07) pp 1839ndash1844IEEE Harbin China August 2007

[64] P Robert V Nguyen S Hentz et al ldquoMampNEMS a newapproach for ultra-low cost 3D inertial sensorrdquo in Proceedingsof the IEEE Conference on Sensors (SENSORS rsquo09) pp 963ndash966October 2009

[65] M Lemkin and B E Boser ldquoMicromachined fully differentiallateral accelerometerrdquo in Proceedings of the IEEE Custom Inte-grated Circuits Conference pp 315ndash318 May 1996

[66] A Selvakumar F Ayazi and K Najafi ldquoA high sensitivityZ-axis torsional silicon accelerometerrdquo in Proceedings of theInternational Electron Devices Meeting pp 765ndash768 IEEE SanFrancisco Calif USA 1996

[67] J C Lotters W Olthuis P H Veltink and P BergveldldquoTheory technology and assembly of a highly symmetricalcapacitive triaxial accelerometerrdquo in Proceedings of the 10thAnnual International Workshop on Micro Electro MechanicalSystems (MEMS rsquo97) pp 31ndash36 January 1997

[68] J C LottersW Olthuis P H Veltink and P Bergveld ldquoCharac-terisation of a highly symmetrical miniature capacitive triaxialaccelerometerrdquo in Proceedings of the International Conferenceon Solid State Sensors and Actuators (TRANSDUCERS rsquo97) pp1177ndash1180 Chicago Ill USA June 1997

[69] A Selvakumar and K Najafi ldquoA high-sensitivity Z-axis capac-itive silicon microaccelerometer with a torsional suspensionrdquoJournal of Microelectromechanical Systems vol 7 no 2 pp 192ndash200 1998

[70] K Y Park C W Lee H S Jang Y S Oh and B J Ha ldquoCapaci-tive sensing type surface micromachined silicon accelerometerwith a stiffness tuning capabilityrdquo in Proceedings of the 11thAnnual International Workshop on Micro Electro MechanicalSystems pp 637ndash642 January 1998

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

26 Journal of Sensors

[71] H Hamacher H-E Richter and S Drees ldquoA system tomeasureabsolute low frequency acceleration on the International SpaceStationrdquo in Proceedings of the 16th IEEE Instrumentation andMeasurement Technology Conference (IMTC rsquo99) vol 1 pp 249ndash253 Venice Italy May 1999 Cat No99CH36309

[72] J Bernstein R Miller W Kelley and P Ward ldquoLow-noiseMEMS vibration sensor for geophysical applicationsrdquo Journal ofMicroelectromechanical Systems vol 8 no 4 pp 433ndash438 1999

[73] H Takao Y Matsumoto and M Ishida ldquoA monolithicallyintegrated three-axis accelerometer using CMOS compatiblestress-sensitive differential amplifiersrdquo IEEE Transactions onElectron Devices vol 46 no 1 pp 109ndash116 1999

[74] N Yazdi and K Najafi ldquoAll-silicon single-wafer micro-gaccelerometer with a combined surface and bulkmicromachin-ing processrdquo Journal of Microelectromechanical Systems vol 9no 4 pp 544ndash550 2000

[75] HXie andGK Fedder ldquoCMOS z-axis capacitive accelerometerwith comb-finger sensingrdquo in Proceedings of the 13th AnnualInternational Conference on Micro Electro Mechanical Systems(MEMS rsquo00) pp 496ndash501 Miyazaki Japan January 2000

[76] H Takao H Fukumoto and M Ishida ldquoFabrication of athree-axis accelerometer integrated with commercial 08120583m-CMOS circuitsrdquo in Proceedings of the 13th Annual InternationalConference on Micro Electro Mechanical Systems (MEMS rsquo00)pp 781ndash786 IEEE Miyazaki Japan January 2000

[77] V Biefeld B Clasbrummel and J Binder ldquoImplantable low-g accelerometer for the telemetric monitoring of micro-movements in fracture zonesrdquo in Proceedings of the 1stAnnual International IEEE-EMBS Special Topic Conference onMicrotechnologies in Medicine and Biology pp 497ndash501 LyonFrance 2000

[78] J Chae H Kulah and K Najafi ldquoA monolithic three-axissilicon capacitive accelerometer with micro-g resolutionrdquo inProceedings of the 12th International Conference on Solid-StateSensors Actuators and Microsystems (TRANSDUCERS rsquo03) pp81ndash84 June 2003

[79] B Quintal S M Schmalholz and Y Y Podladchikov ldquoLow-frequency reflections from a thin layer with high attenuationcaused by interlayer flowrdquo Geophysics vol 74 no 1 pp N15ndashN23 2009

[80] H Kulah J Chae and K Najafi ldquoNoise analysis and character-ization of a sigma-delta capacitive silicon microaccelerometerrdquoin Proceedings of the 12th International Conference on Solid-StateSensors Actuators andMicrosystems (TRANSDUCERS rsquo03) vol1 pp 95ndash98 IEEE Boston Mass USA June 2003

[81] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometerrdquo in Proceedings of theIEEE 16th Annual International Conference on Micro ElectroMechanical Systems pp 466ndash469 Kyoto Japan January 2003

[82] B V Amini and F Ayazi ldquoA 25-V 14-bit sumΔ CMOS SOIcapacitive accelerometerrdquo IEEE Journal of Solid-State Circuitsvol 39 no 12 pp 2467ndash2476 2004

[83] J Chae H Kulah and K Najafi ldquoAn in-plane high-sensitivitylow-noise micro-g silicon accelerometer with CMOS readoutcircuitryrdquo Journal of Microelectromechanical Systems vol 13 no4 pp 628ndash635 2004

[84] B V Amini S Pourkamali and F Ayazi ldquoA high resolutionstictionless cmos compatible soi accelerometer with a Lownoise Low power 025 120583M cmos interfacerdquo in Proceedingsof the17th IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo04) pp 572ndash575 January 2004

[85] J ChaeHKulah andKNajafi ldquoAmonolithic three-axismicro-g micromachined silicon capacitive accelerometerrdquo Journal ofMicroelectromechanical Systems vol 14 no 2 pp 235ndash2422005

[86] A Sadat H Qu C Yu J S Yuan and H Xie ldquoLow-powerCMOS wireless MEMSmotion sensor for physiological activitymonitoringrdquo IEEE Transactions on Circuits and Systems IRegular Papers vol 52 no 12 pp 2539ndash2551 2005

[87] P Monajemi and F Ayazi ldquoDesign optimization and imple-mentation of amicrogravity capacitiveHARPSS accelerometerrdquoIEEE Sensors Journal vol 6 no 1 pp 39ndash46 2006

[88] Y S Suzuki and Y-C Tai ldquoMicromachined high-aspect-ratioparylene spring and its application to low-frequency accelerom-etersrdquo Journal of Microelectromechanical Systems vol 15 no 5pp 1364ndash1370 2006

[89] R Abdolvand B V Amini and F Ayazi ldquoSub-micro-gravityin-plane accelerometers with reduced capacitive gaps and extraseismic massrdquo Journal of Microelectromechanical Systems vol16 no 5 pp 1036ndash1043 2007

[90] Y W Hsu H T Chien C S Lin L P Liao S Chen andP Chang ldquoA capacitive low-g three-axis accelerometerrdquo inProceedings of the 10th International Conference on ElectronicMaterials and Packaging (EMAP rsquo08) pp 325ndash328 IEEE TaipeiTaiwan October 2008

[91] R Kepenek I E Ocak H Kulah and T Akin ldquoA 120583g resolutionmicroacelerometer system with a second-order Σ minus Δ readoutcircuitryrdquo in Proceedings of the Research in Microelectronics andElectronics (PRIME rsquo08) pp 41ndash44 Istanbul Turkey

[92] A Wung R V Park K J Rebello and G K Fedder ldquoTri-axial high-G CMOS-MEMS capacitive accelerometer arrayrdquo inProceedings of the 21st IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo08) pp 876ndash879 January2008

[93] W T Pike I M Standley W J Karl et al ldquoDesign fabricationand testing of a micromachined seismometer with NANO-Gresolutionrdquo in Proceedings of the 15th International Conferenceon Solid-State Sensors Actuators and Microsystems (TRANS-DUCERS rsquo09) pp 668ndash671 Denver Colo USA June 2009

[94] R G Walmsley L K Kiyama D M Milligan R L Alley DL Erickson and P G Hartwell ldquoMicro-G silicon accelerometerusing surface electrodesrdquo in Proceedings of the IEEE Conferenceon Sensors (SENSORS rsquo09) pp 971ndash974 October 2009

[95] B Boga I E Ocak H Kulah and T Akin ldquoModeling of acapacitivesum-120575MEMSaccelerometer system including the noisecomponents and verification with test resultsrdquo in Proceedingsof the 22nd IEEE International Conference on Micro ElectroMechanical Systems (MEMS rsquo09) pp 821ndash824 January 2009

[96] D Hollocher X Zhang A Sparks et al ldquoA very low cost3-axis MEMS accelerometer for consumer applicationsrdquo inProceedings of the IEEE Sensors pp 953ndash957 Christchurch NewZealand October 2009

[97] Y Hsu S Lin and C Lin ldquoA low-g three-axis accelerometer ICrdquoin Proceedings of the 4th International Microsystems PackagingAssembly and Circuits Technology Conference pp 319ndash322IEEE Taipei Taiwan 2009

[98] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Conference onSensors (SENSORS rsquo09) pp 552ndash554 October 2009

[99] Y Li L Wang and J Liu ldquoCapacitive silicon micro-accelerometer detecting technology researchrdquo in Proceedingsof the International Conference on Measuring Technology and

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Journal of Sensors 27

Mechatronics Automation (ICMTMA rsquo09) pp 186ndash189 Zhangji-ajie China April 2009

[100] Y Hirata N Konno T Tokunaga M Tsugai and H Fuku-moto ldquoA new z-axis capacitive accelerometer with high impactdurabilityrdquo inProceedings of the 15th International Conference onSolid-State Sensors Actuators and Microsystems (TRANSDUC-ERS rsquo09) pp 1158ndash1161 Denver Colo USA June 2009

[101] P Zwahlen A-M Nguyen Y Dong F Rudolf M Pastreand H Schmid ldquoNavigation grade MEMS accelerometerrdquo inProceedings of the 23rd IEEE International Conference on MicroElectro Mechanical Systems (MEMS rsquo10) pp 631ndash634 HongKong January 2010

[102] S S Tan C Y Liu L K Yeh Y H Chiu M S-C Lu and KY J Hsu ldquoDesign of low-noise CMOS MEMS accelerometerwith techniques for thermal stability and stable DC biasingrdquoin Proceedings of the 32nd Annual Custom Integrated CircuitsConference (CICC rsquo10) pp 1ndash4 San Jose Calif USA September2010

[103] C-M Sun M-H Tsai Y-C Liu and W Fang ldquoImplementa-tion of a monolithic single proof-mass tri-axis accelerometerusing CMOS-MEMS techniquerdquo IEEE Transactions on ElectronDevices vol 57 no 7 pp 1670ndash1679 2010

[104] C H Je S Lee M L Lee J Lee W S Yang and C A ChoildquoZ-axis capacitive MEMS accelerometer with moving groundmassesrdquo in Proceedings of the IEEE Sensors pp 635ndash638 IEEEKona Hawaii USA November 2010

[105] B Homeijer D Lazaroff D Milligan et al ldquoHewlett packardrsquosseismic grade MEMS accelerometerrdquo in Proceedings of the 24thIEEE International Conference on Micro Electro MechanicalSystems (MEMS rsquo11) pp 585ndash588 Cancun Mexico January2011

[106] Y Dong P Zwahlen A M Nguyen R Frosio and F RudolfldquoUltra-high precisionMEMS accelerometer closed-loop systemdesignrdquo in Proceedings of the International Solid-State SensorsActuators and Microsystems Conference (Transducers rsquo11) pp695ndash698 Beijing China 2011

[107] Q Hu C Gao Y Zhang J Cui and Y Hao ldquoDesign of a novellow cross-axis sensitivity micro-gravity sandwich capacitanceaccelerometerrdquo in Proceedings of the 6th IEEE InternationalConference on NanoMicro Engineered and Molecular Systems(NEMS rsquo11) pp 642ndash645 IEEE Kaohsiung Taiwan February2011

[108] U Sonmez H Kulah and T Akin ldquoA fourth order uncon-strainedsumΔ capacitive accelerometerrdquo inProceedings of the 16thInternational Solid-State Sensors Actuators and MicrosystemsConference (TRANSDUCERS rsquo11) pp 707ndash710 June 2011

[109] I E Gonenli Z Celik-Butler and D P Butler ldquoSurfacemicromachined MEMS accelerometers on flexible polyimidesubstraterdquo IEEE Sensors Journal vol 11 no 10 pp 2318ndash23262011

[110] Q Hu C Gao Y Hao Y Zhang and G Yang ldquoLow cross-axis sensitivity micro-gravity microelectromechanical systemsandwich capacitance accelerometerrdquo Micro and Nano Lettersvol 6 no 7 pp 510ndash514 2011

[111] D J Young M A Zurcher M Semaan C A Megerian andW H Ko ldquoMEMS capacitive accelerometer-based middle earmicrophonerdquo IEEETransactions on Biomedical Engineering vol59 no 12 pp 3283ndash3292 2012

[112] J Wang Z Yang and G Yan ldquoA silicon-on-glass Z-axisaccelerometer with vertical sensing comb capacitorsrdquo in Pro-ceedings of the 7th IEEE International Conference onNanoMicro

Engineered and Molecular Systems (NEMS rsquo12) pp 583ndash586Kyoto Japan March 2012

[113] F Garcia E L Hixson C I Huerta and H Orozco ldquoSeismicaccelerometerrdquo in Proceedings of the 16th IEEE InstrumentationandMeasurement Technology Conference (IMTC rsquo99) vol 3 pp1342ndash1346 Venice Italy May 1999 Cat No99CH36309

[114] L-P Wang K Deng L Zou R Wolf R J Davis and STrolier-McKinstry ldquoMicroelectromechanical systems (MEMS)accelerometers using lead zirconate titanate thick filmsrdquo IEEEElectron Device Letters vol 23 no 4 pp 182ndash184 2002

[115] L-P Wang R A Wolf Jr Y Wang et al ldquoDesign fabricationand measurement of high-sensitivity piezoelectric microelec-tromechanical systems accelerometersrdquo Journal of Microelec-tromechanical Systems vol 12 no 4 pp 433ndash439 2003

[116] F Gerfers M Kohlstadt H Bar M-Y He Y Manoli andL-P Wang ldquoSub-120583g ultra-low-noise MEMS accelerometersbased on CMOS-compatible piezoelectric AIN thin filmsrdquoin Proceedings of the 4th International Conference on Solid-State Sensors Actuators and Microsystems (TRANSDUCERSand EUROSENSORS rsquo07) pp 1191ndash1194 June 2007

[117] Y Hu and Y Xu ldquoAn ultra-sensitive wearable accelerometer forcontinuous heart and lung sound monitoringrdquo in Proceedingsof the Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBS rsquo12) pp 694ndash697 IEEESan Diego Calif USA September 2012

[118] F A Levinzon ldquoFundamental noise limit of piezoelectricaccelerometerrdquo IEEE Sensors Journal vol 4 no 1 pp 108ndash1112004

[119] C Yeh and K Najafi ldquoA low-voltage tunneling-based siliconmicroaccelerometerrdquo IEEE Transactions on Electron Devicesvol 44 no 11 pp 1875ndash1882 1997

[120] C Yeh and K Najafi ldquoMicromachined tunneling accelerometerwith a low-voltage CMOS interface circuitrdquo in Proceedings ofthe International Solid State Sensors and Actuators Conference(Transducers rsquo97) vol 2 pp 1213ndash1216 1997

[121] C-H Liu and T W Kenny ldquoA high-precision wide-bandwidthmicromachined tunneling accelerometerrdquo Journal of Microelec-tromechanical Systems vol 10 no 3 pp 425ndash433 2001

[122] L Novak P Neuzil J Li and M Woo ldquoUltrasensitive MEMS-based inertial systemrdquo in Proceedings of the IEEE Sensors pp552ndash554 Christchurch New Zealand October 2009

[123] Z Zhang J Wu S Bernard and R G Walmsley ldquoChipon Board development for a novel MEMS accelerometer forseismic imagingrdquo in Proceedings of the IEEE 62nd ElectronicComponents and Technology Conference (ECTC rsquo12) pp 350ndash355 San Diego Calif USA June 2012

[124] H Qu Development of DRIE CMOS-MEMS Process and Inte-grated Accelerometers University of Florida Gainesville FlaUSA 2006

[125] W Kuehnel ldquoModelling of the mechanical behaviour of adifferential capacitor acceleration sensorrdquo Sensors andActuatorsA Physical vol 48 no 2 pp 101ndash108 1995

[126] K T V Grattan and T Sun ldquoFiber optic sensor technology anoverviewrdquo Sensors and Actuators A Physical vol 82 no 1 pp40ndash61 2000

[127] S Elies and S Ebenhoch ldquoPerformance analysis of commercialaccelerometers of different technologiesrdquo in Proceedings of the16th International Conference on Sensor Device Technologies andApplications pp 54ndash59 Venice Italy August 2015

[128] J Fennelly S Ding J Newton and Y Zhao ldquoThermal MEMSaccelerometers fit many applicationsrdquo Sensor Magazin pp 18ndash20 2012

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

28 Journal of Sensors

[129] G Koc and K Yegin ldquoHardware design of seismic sensors inwireless sensor networkrdquo International Journal of DistributedSensor Networks vol 2013 Article ID 640692 8 pages 2013

[130] G M Goloshubin V A Korneev M Vjacheslav and MVingalov ldquoSeismic low-frequency effects from oil-saturatedreservoir zonesrdquo in Proceedings of the SEG International Exposi-tion and 72nd Annual Meeting pp 1ndash4 2002

[131] B J Merchant ldquoMEMS applications in seismologyrdquo in Pro-ceedings of the Seismic Instrumentation Technology SymposiumSandia National Laboratory November 2009

[132] S A Shapiro M Parotidis S Rentsch and E Rothert ldquoReser-voir characterization using passive seismicmonitoring physicalfundamentals and road aheadrdquo in Proceedings of the SEGInternational Exposition and 74th Annual Meeting vol 4 pp 1ndash4 2004

[133] N Martin and R R Stewart ldquoThe effect of low frequencies onseismic analysisrdquoCREWESResearch Report vol 6 pp 1ndash8 1994

[134] M Warner A Ratcliffe T Nangoo et al ldquoAnisotropic 3D full-waveform inversionrdquo Geophysics vol 78 no 2 pp R59ndashR802013

[135] G Goloshubin C Van Schuyver V Korneev D Silin and VVingalov ldquoReservoir imaging using low frequencies of seismicreflectionsrdquoThe Leading Edge vol 25 no 5 pp 527ndash531 2006

[136] A J Berkhout Seismic Migration Imaging of Acoustic Energyby Wave Field Extrapolation A Theoretical Aspects vol 14 ofDevelopments in Solid Earth Geophysics 2nd edition 1982

[137] C J Beasley R E Chambers and Z Jiang ldquoA new lookat simultaneous sourcesrdquo in Proceedings of the 68th AnnualInternational Meeting SEG Expanded Abstracts vol 17 pp 133ndash135 1998

[138] J Stefani G Hampson and E F Herkenhoff ldquoAcquisition usingsimultaneous sourcesrdquo in Proceedings of the 69th Conference ampExhibition EAGE Expanded Abstracts vol 27 no 7 pp 918ndash9232007

[139] A J Berkhout and C P A Wapenaar ldquoA unified approachto acoustical reflection imaging II the inverse problemrdquo TheJournal of the Acoustical Society of America vol 93 no 4 pp2017ndash2023 1993

[140] A J Berkhout ldquoChanging the mindset in seismic data acquisi-tionrdquoThe Leading Edge vol 27 no 7 pp 924ndash938 2008

[141] L T Ikelle ldquoCoding and decoding seismic data modelingacquisition and processingrdquo in Proceedings of the 77th AnnualMeeting SEG Expanded Abstracts vol 26 pp 64ndash67 SanAntonio Tex USA September 2007

[142] D Draganov K Wapenaar and J W Thorbecke ldquoSeismicinterferometry reconstructing the Earthrsquos reflection responserdquoGeophysics vol 71 no 4 pp SI61ndashSI70 2006

[143] P Duncan ldquoIs there a future for passive seismicrdquo First Breakvol 23 pp 111ndash117 2005

[144] S Dangel M E Schaepman E P Stoll et al ldquoPhenomenologyof tremor-like signals observed over hydrocarbon reservoirsrdquoJournal of Volcanology and Geothermal Research vol 128 no 1-3 pp 135ndash158 2003

[145] K Akrawi and G Bloch ldquoApplication of passive seismic (IPDS)surveys in Arabian Peninsulardquo in Proceedings of the EAGEWorkshop on Passive Seismic Exploration andMonitoring Appli-cations Dubai UAE December 2006

[146] E V Birialtsev I N Plotnikova I R Khabibulin and N YShabalin ldquoThe analysis of microseisms spectrum at prospectingof oil reservoir on republic tatarstanrdquo in Proceedings of the 68thInternational Conference and Exhibition (EAGE rsquo06) October2006

[147] R Graf S M Schmalholz Y Podladchikov and E H SaengerldquoPassive low frequency spectral analysis exploring a new fieldin geophysicsrdquoWorld Oil vol 228 no 1 pp 47ndash52 2007

[148] M-A Lambert S M Schmalholz E H Saenger and B SteinerldquoLow-frequency microtremor anomalies at an oil and gas fieldin Voitsdorf Austriardquo Geophysical Prospecting vol 57 no 3 pp393ndash411 2009

[149] G R Rached ldquoSurface passive seismic inKuwaitrdquo inProceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications vol A27 December 2006

[150] A E Suntsov S L Aroutunov A M Mekhnin and BY Meltchouk ldquoPassive infra-frequency microseismic technol-ogymdashexperience and problems of practical userdquo in Proceedingsof the EAGE Workshop on Passive Seismic Exploration andMonitoring Applications article A25 Dubai UAE December2006

[151] P Van Mastrigt and A Al-Dulaijan ldquoSeismic spectroscopyusing amplified 3-C geophonesrdquo in Proceedings of the 70th Inter-national Conference and Exhibition EAGE Extended AbstractsB047 2008

[152] httpwwwaapgorgexplorer200706junpassive seismiccfm[153] A Albarbar A Badri J K Sinha and A Starr ldquoPerformance

evaluation of MEMS accelerometersrdquoMeasurement vol 42 no5 pp 790ndash795 2009

[154] M Peter and M Lansley ldquoWhat receivers will we use for lowfrequenciesrdquo in Proceedings of the SEG San Antonio AnnualMeeting pp 72ndash76 2011

[155] E V Egorov I V Egorov and V M Agafonov ldquoSelf-Noise ofthe MET angular motion seismic sensorsrdquo Journal of Sensorsvol 2015 Article ID 512645 5 pages 2015

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of