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Microseismic Monitoring at IBDP: Systems Review and Current Status Bob Will, Principal Reservoir Engineer, Schlumberger Carbon Services
18 September 2012
Acknowledgements
● Rob Finley, Sallie Greenberg, and Hannes E. Leetaru Illinois State Geological Survey
● US Department of Energy (DOE) ● National Energy Technology Laboratory (NETL) ● Don Lee, Elizabeth Seidlecki
Schlumberger DCS ● Paul Jaques, Dan Raymer
Schlumberger Cambridge Research ● Valerie Smith, Ozgur Senel, Ahsan Alvi
Schlumberger Carbon Services
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© 2012 Schlumberger. All rights reserved. An asterisk is used throughout this presentation to denote a mark of Schlumberger. Other company, product, and service names are the properties of their respective owners.
Outline
1. Project Overview 2. In Ground Instrumentation 3. Recording and Data Handling Systems 4. Uncertainty Modeling 5. Data Processing 6. Data Analysis and Interpretation 7. Geomechanical Applications 8. Summary
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● Injection of ~1000 tonnes/day CO2 began November, 2011.
● Approximately 1,000,000 tons to be injected over a 3-year period.
● Microseismic monitoring system has been in place and recording since May, 2011.
● Additional geoscience data acquisition includes petrophsyical logging, whole core, 3D surface seismic, and repeat 3D VSP
Project Overview
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In-Ground Equipment Configuration
Clamping Device for the Sensors One Piece C-section Nickel Alloy
Natural state
Location of geophone with 4 sensors
Deployable state Released state
PS3 Deployment
Permanent Seismic Sensor System Flowing Well
Data Collection System Overview
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Microseismic Integrated Data Acquisition System
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PS3 Level 3 PS3 Level 2 PS3 Level 1
Geophysical Monitoring
Well
GeoRes System (96 Channels)
Levels
Sensor Inputs
31 x 3C Geophone
Levels
Tubing Hanger Pass Through
Downhole Junction Box
Injection Well
• Continuous SEG-2 data from the GeoRes is archived via XMetal into 10-second blocks.
• Triggered event data is saved to a separate folder.
XMetal Event Detection
Software
Data Storage
Raw Data Triggered
Event Data
Data Example
Uncertainty Modeling
● Uncertainty in event location is dependent upon many factors ― observation geometry ― measurement quality ― and earth elastic properties.
● Uncertainty analysis is vital for understanding the quality of monitoring results and/or for optimizing system design.
● Uncertainty of the IBDP event locations was modeled using two scenarios; ― Case 1 – Geophysical monitoring well observations only ― Case 2 – Geophysical monitoring well AND deeper PS3 observations
● Modeling results show the importance of deeper PS3 observations.
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1. Maximum Theoretical Uncertainty = Maximum of X, Y and Z direction uncertainty 2. Assumptions:
P time picking error: 1 ms, P azimuth error: 5 deg S time picking error: 2 ms, S azimuth error: 10 deg
3. Uncertainty scale is from 0 to 150 ft - from blue to red 4. Receivers included in the Case-1 model:
Uncertainty of Microseismic Event Location (Case1)
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Perspective View
1. Maximum Theoretical Uncertainty = Maximum of X, Y and Z direction uncertainty 2. Assumptions:
P time picking error: 1 ms, P azimuth error: 5 deg S time picking error: 2 ms, S azimuth error: 10 deg
3. Uncertainty scale is from 0 to 50 ft - from blue to red 4. Receivers included in the Case-2 model: (4-Component Geophones treated as 3-Component)
Uncertainty of Microseismic Event Location (Case1)
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Perspective View
1. Maximum Theoretical Uncertainty = Maximum of X, Y and Z direction uncertainty 2. Assumptions: P time picking error: 1 ms, P azimuth error: 5 deg S time picking error: 2 ms, S azimuth error: 10 deg 4. Uncertainty scale is from 0 to 50 ft - from blue to red 5. Receivers included in the Case-2 model: (4-Component Geophones were treated as 3-Component Geophones)
All depths are TVDSS
Data Processing – Velocity Model Verification
PerfDiff New XLOC
Diff New YLOC
Diff New ZLOC
Diff New Distance
ft ft ft ft1 -‐0.75 -‐71.88 97.97 121.5132 -‐20.31 -‐105.38 70.98 128.668634 31 -‐101.25 76 130.34025 36.72 -‐112.88 137.97 182.00546 50.19 -‐118 174.36 216.43587 55.88 -‐61.75 58.05 101.51578 24.22 -‐57.62 4.37 62.655969 8.88 -‐52.38 -‐34.03 63.0916810 50 479.62 114.36 495.594111 12.34 330.38 27.05 331.7151
Data Analysis and Interpretation – Seismic
Data Analysis and Interpretation – RTAC
RTAC* real-time acquisition and control software
Microseismicity and Mechanical Earth Models
18 Courtesy of L. Bennett
Geophone Well
Treatment Well
● Microseismic monitoring may reveal fracture trends due to injection activities
● Alternately, Mechanical Earth Models (MEM) may predict zones of weaker rock where fracturing may occur or predict orientation of potential fracturing
● When microseismic activity differs from MEM predictions, then refinement in the models are necessary to further understand the reservoir
Mt Simon Geomechanics Model Workflow
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FEM simulations with time
steps
Reservoir Simulation
MDT* pressure
Core test results
Stress test Petrophysics
Geological model
Seismic Inversion
3D MEM 1D MEM
Embed reservoir
model
Single material model
Pre-injection stress
calibration
Analysis of results
Mechanical Property Propagation Using Seismic Inversion
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3D Strain and Location of 3 Cells Examined for Stress Path
Summary
● In-ground equipment configuration takes advantage of the injection well plus multi-use geophysical monitoring well.
● Real-time data handling systems provide secure remote access to up-to-date information facilitating rapid data processing turn-around.
● Analytical uncertainty modeling estimates event location integrity.
● Integrated geoscience and operational data interpretation and visualization methods are used to understand correlations and potential causal relationships.
● Numerical mechanical modeling techniques are utilized to develop predictive capability.
● The Illinois Basin – Decatur Project microseismic monitoring system provides an advanced field laboratory providing information vital for improving our understanding of induced seismicity potential related to CO2 sequestration operations.
