Download - Simulation 1 Overview
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Introduction to
Simulation
Prepared by:
Thomas W. Engler, Ph.D.,P.E.Fall 2009
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Why develop a reservoir simulation
model?
provide detailed performance predictions
for multiphase, heterogeneous reservoirs
Evaluate single well performance
Improve/optimize reservoir management
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Modeling Approaches
1. Analogy
2. Physicala. Elemental core
b. Scaled packed
sand, cut stone
c. Field pilot single
pattern
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Modeling Approaches
3. Mathematical
Vol( u)in ( u)out
10
100
1000
0.1 1.0 10.0 100.0
time
Pressure
Material Balance Statistical
Decline Curves
-0.00025x -0.00035x
-0.0052x
1
10
100
1000
Aug-87 May-90 Jan-93 Oct-95 Jul-98 Apr-01
Time (months)
Rate(mscf/d)
Analytical
Numerical
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Comparison
Simulation to Field Pilots
Lack of repeatability
(one shot proposition)
Time for evaluation of
pilot results can belengthy
Costly
Real conditions Results: may be used
to modify model
Can repeat frequently
from initial conditions
Time to evaluate
results is fast Lower cost?
Simulates field
conditions Results: May be used
to design pilot.
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Comparison
Simulation to Lab models
Core experiments use
actual reservoir rock
and fluids.
Results distinguishmechanisms of fluid
flow
Measurement/human
error
Scale????
Imaginary reservoir,
requires physical
model results
Numerical dispersion Grid orientation
effects
Solution techniqueaccuracy
Scale????
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Scale
oqo
wqw
pb
gh
o
w
pc
gh
Simulation scale
Reservoir scaleCore scale
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Comparison
Numerical to Analytical
Zero-dimensional
tank models
No variations in
parameters withregard to space or
time
Multi-dimensional
Allows for variations
of parameters
Based onfundamental
equations
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Planning
StepProblem Definition
Data Review
Data Acquisition
Model Design
History Matching
PredictionEditing, analysis, reporting
Time
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Problem Definition
assemble information about the reservoir
and operations
define practical objectives and scope of
study
preliminary analysis of the reservoir
mechanics, e.g., coning, gravity
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Data review and acquisition
review of quality and quantity of data,
sources of data
assess if sufficient data is available to meetobjectives, or revise objectives or obtain
more data
sensitivity of reservoir performance toparameters!
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Model Design
Individual well or full-field model? Radial or
cartesian?
Type of reservoir fluid? Type of process to model?
Quality of geologic and petrophysical data?
Time and cost constraints?
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History Matching
adjust input variables to validate model
through matching performance parameters
A successful history match does not
guarantee a field match
Uncertainty.nonuniqueness
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Prediction
Predict future performance to make better
management decisions
Perform sensitivity analysis and observe
impact of results
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Prediction-Example
Medford