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High oil prices and concerns about future oil supply are leading
to arenewed interest in enhanced oil recovery (EOR), a group of
tech-nologies that can significantly increase recovery from
existing oil
reservoirs. Most of the experience with EOR is still in the
United
States, principally with CO2 flooding in the Permian Basin in
west
Texas and with the several thermal processes in the San
Joaquin
Valley in California. A listing of these projects is compiled
every 2years.1 But worldwide applications are growing. Thermal
recovery of
bitumen in Alberta, Canada, is increasing rapidly, and thermal
pro-
jects have been successful in Venezuela, Indonesia, and
elsewhere.
Chemical and polymer floods are being implemented in China.
New applications increasingly will be worldwide. Each one
willdepend on careful planning to design an EOR project specific to
the
properties of the oil, the reservoir conditions, and the
availability of injectants. In many situations, new EOR
technology will be necessary.
The processes being applied in the United States were tailored
for those
conditions and do not necessarily translate to other geologic
provinces.This article attempts to distill past experience to
define the state of the
art in planning EOR projects. It is grounded in more than 30
years of
experience by the authors in a wide variety of EOR
applications.
The Planning ProcessSuccessful EOR project management depends on
good planning.
“Prior proper planning prevents poor performance,” they say, and
it
is especially true when EOR is involved. Planning includes:
• Identifying the appropriate EOR process.
• Characterizing the reservoir.• Determining the engineering
design parameters.
• Conducting pilots or field tests as needed.
• Finishing with a plan to manage the project to meet or
exceed
expectations.
From the outset, and at every step along the way, we strongly
rec-ommend that careful attention be paid both to economic
studies
and to reservoir simulation as the reservoir characterization
and
engineering design progresses. In this way, the chances of
success
are greatly improved. Fig. 1 illustrates the interaction of all
three.
Economics is the ultimate project driver. After all, unless the
pro- ject is comfortably profitable, it should not be pursued
in the first
place. But reliable economics need good performance
predictions.
Good simulation models need good data. And what data are
need-
ed is determined by which project elements the economics is
sensi-tive to. Each guides and depends on the others.
Reservoir-Performance ModelingGood simulation models provide the
performance data needed for
profitability studies. Together, they greatly reduce risk of
wasted or
misdirected efforts. There is a five-step process in developing
areservoir performance model.
• Select appropriate simulator.
• Collect valid data.
• History match.
• Predict EOR-project performance.
• Conduct sensitivity studies.
As a rule, modeling EOR processes requires more data and
moretime than primary- or secondary-recovery processes. The
impor-tance of reservoir simulation was driven home early in our
careers.
Years ago, after a moderately successful field pilot, we
implemented
an expansion project using improved technology. The
economics
was favorable and was supported by extensive laboratory data.
But
the expansion project was a complete failure. Not only did we
notrecover any oil, but we also could not even explain the causes.
It was
later, after reservoir simulators were developed for this
process, that
we were able to model the project and explain what happened.
If
good simulators had existed and been used at the outset, we
could
have saved ourselves a lot of time and money. One experience
likethis makes you a lifetime believer in reservoir simulation.
Simulators are not perfect, of course. They are very good at
pro-ducing a performance prediction consistent with what is
known
about the reservoir and the recovery process. But they
cannot
include what is not known. For this reason, simulation models
needto be kept up to date as new information is gained. Comparing
sim-
ulation predictions to actual results is the best way to
uncover
important information not previously identified.
Economic StudiesProfitability is the primary driver. It
justifies implementation of the
EOR process and governs how it should be designed. Profitability
is
strongly influenced by product prices, which as we all know are
high-
ly variable and impossible to predict. Over a long period of
time, the
average wellhead price in the United States has averaged U.S.
$20/bblin today’s constant dollars. Over the last 30 years,
however, the aver-
age has been closer to $25/bbl. Either of these should provide a
good
initial starting point, wherever you think future prices are
headed.
It is important to begin economic analyses early in the
process-
selection step. Start with simple economic screening models to
aidin the choice of process, and add sophistication as the design
pro-
gresses. Economics can be used to guide the engineering
design,
help design any pilot, and help manage ongoing surveillance.
Process SelectionEOR processes are designed to do one of two
things—improve
sweep efficiency or improve displacement efficiency. The
former
overcomes reservoir heterogeneities or poor mobility ratios.
Appropriate EOR processes in these cases are polymer flooding
orone of the thermal methods. The latter overcomes capillary forces
torecover oil left behind by primary recovery or waterflooding.
EOR
processes applicable to these reservoirs are chemical flooding,
mis-
cible gasflooding, immiscible gasflooding, or microbial
processes.
For a quick guide on which to choose, see the papers by Taber
etal.
in the SPE literature.2,3 While selecting a process, it is
important to
include simple performance models and screening economics.
Reservoir CharacterizationMany an EOR project has failed because
of surprises in the geolog-
ic and petrophysical description of the reservoir. Your Earth
model-
ers are your friends. Work with them to find out as much as
possi-
Planning Successful EOR Projects
Management
J. Roger Hite, SPE, Business Fundamentals Group; S.M.
Avasthi, SPE, Avasthi & Assocs. Inc.; and Paul L. Bondor, SPE,
BonTech
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ble about depositional environment, discontinuities, layering,
and
the size and shape of the container. Even relatively small
details can
be important. Channel boundaries, clay drapes, and minor
fractur-ing or faulting can have a big impact on flow paths.
Mineralogy may
be important in understanding fluid/rock interactions.In one
case, the initial wells in a deltaic channel sequence were
well correlated in the beginning. Subsequent wells wound up
out-
side the channel, however. Suddenly, large blocky sands looked
thinand shaley, spelling disappointment and disaster for this EOR
pro-
ject. In another, a moderately large CO2-injection project
failed
because the residual-oil saturation was not as large as had been
esti-
mated. Log-inject-log data indicated a lower number, but the
high-
er number indicated by material balance was chosen for design
pur-poses. It turned out that the more accurate number was the
lower
one. The result was meager oil recovery.
Not understanding the reservoir adequately, and therefore not
tak-
ing reservoir and process uncertainty properly into account, is
proba-
bly the most common cause of failure in past EOR pilots and
projects.
Engineering DesignDesign parameters include those at the
microscale (e.g., miscibility
pressures and mobilities) and the macroscale (e.g., reservoir
pres-
sure and temperature, volume of injectant, and placement of
wells).Particular care should be paid to the interaction of
reservoir (both
rock and fluids) and the selected process.
As the amount and accuracy of data improves,
more-sophisticat-
ed performance models and economic tools are appropriate.
Sensitivity studies can be used to help define which parameters
are
important to know and how accurate they need to be.Here, a good
understanding of the value of information comes into
play. The sensitivity studies will show that some parameters do
not influ-
ence the economic results very much. These can be given much
lessattention, or, perhaps, can be ignored. Others will have a
strong influence
on profitability and, therefore, will warrant better
understanding.Remember, you need to know only enough to make the
right decisions
and correct choices. Beyond that, data and information have no
value.
Pilots, Field TestsIf there are important parameters and
variables that are not wellunderstood, a field test or pilot may be
needed. In our experience,
the best field tests are those designed to gather specific,
targeted
information—that is, data identified by the sensitivity studies
as
being important for the success of the project but which are not
suf-
ficiently known from available sources. Some data are hard to
mea-
sure in the laboratory or difficult to deduce from history
matching.These might include such factors as injectivity,
residual-oil satura-
tion, and displacement efficiency. When these are critical for
suc-
cess, a field test is justified.
“Oil-in-tank” pilots are generally not the best. “Oil-in-tank”
pilots
are field tests in which success is measured by whether the
designedamount of oil is recovered in the stock tank. They are
often difficult to
interpret with confidence, and they generally take years to
complete.
During that time, there are inevitably changes in the operation
of the
reservoir that complicate interpretation. Wells are
reconditioned orreplaced, injection rates change, or pressures
change. The impact of these changes on the performance of the
field test is seldom clear. Also,
field tests are usually done in a portion of a field. Swept
volumes must
be estimated and are likely to change during the test as a
result of the
operational changes listed above. Even in the absolute failure
case, in
which no oil is recovered, such tests are less than helpful.
They estab-lish that the project did not work but do not provide
answers as to why,
nor do they provide information on how to improve next time.
The best pilots are designed to use observation or monitor wells
to
monitor specific events—for example, saturation, temperature, or
pres-
sure changes over time vs. simulated expectations. These field
tests typ-ically take months to complete, not years, and provide
specific answers
to identified questions. The answers can then be used to improve
per-formance models and economic studies to make smart
decisions.
Project ImplementationEnsuring successful EOR projects does not
end when the valves are
turned on. Ongoing surveillance is most important and should
be
part of the project design. Good surveillance should be a
partner-
ship between operations and engineering. If this is a new
process,
operations personnel will need adequate training in what to
expect,what to watch for, and what to measure. The importance of
good
eyes and ears on the ground, reliable data, and careful quality
con-
trol should be emphasized.
Active surveillance plays a strong role in achieving
targets.
Observation wells for monitoring performance, frequent
wellreviews, computerized databases, and teamwork are all key.
EOR
projects are not business as usual. Good use can be made of the
sim-
ulation and economics models developed during the planning
phase. Kept up to date, they can guide improvements and
adjust-
ments for years to come.As with all technology implementations,
change management can
be important—aligning people with a new way of doing things.
This
means new work processes, better training, perhaps a new
organiza-
tion, and a work culture that encourages success. (The
importance
of change management will be addressed in one of the sessions at
thismonth’s SPE Digital Energy Conference, 23–24 March, in
Houston.)
Conclusion
Successful EOR projects need good engineering design data,
perfor-mance models, and economic studies that proceed in parallel.
Startsimple at the outset, and add sophistication as the design
proceeds.
By keeping all three in play, projects can be designed to
achieve opti-
mal performance and profitability.
References1. “Annual EOR Survey,” Oil & Gas Journal, 15
April 2004.
2. Taber, J.J., Martin, F.D., and Seright, R.S.: “EOR Screening
Criteria
Revisited: Part 1—Introduction to Screening Criteria and
Enhanced
Recovery Field Projects,” SPERE (August 1997).
3. Taber, J.J., Martin, F.D., and Seright, R.S.: “EOR Screening
Criteria Revisited:
Part 2—Applications and Impact of Oil Prices,” SPERE (August
1997).
JPT
EOR Process
Selection
Geologic Studies
Design Parameters
Lab Data (R&D)
Field Date
Pilots / Field
Testing
Project
Implementation
Analog Data
Analytic
Tools
Coarse
Simulation
Fine
Simulation
Screening
Detailed
Economic
Models
Modeling Engineering Data Economics
EOR Process
Selection
Geologic Studies
Design Parameters
Lab Data (R&D)
Field Date
Pilots / Field
Testing
Project
Implementation
Analog Data
Analytic
Tools
Coarse
Simulation
Fine
Simulation
Screening
Detailed
Economic
Models
Modeling Engineering Data Economics
EOR Process
Selection
Geologic Studies
Design Parameters
Lab Data (R&D)
Field Date
Pilots / Field
Testing
Project
Implementation
Analog Data
Analytic
Tools
Coarse
Simulation
Fine
Simulation
Screening
Detailed
Economic
Models
Modeling Engineering Data Economics
Fig. 1—Economic studies, reservoir characterization
andengineering design, and reservoir performance modeling
proceed in parallel, each supporting the other.
