Download - Introduction to Reservoir Simulation
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PCB3053RESERVOIR MODELLING AND SIMULATION
MAY 2015
Dr. Mohammed Abdalla Ayoub
Ch. 1.1: Introduction to Reservoir Simulation
Petroleum Engineering Department (GPED)
UNIVERSITI TEKNOLOGI PETRONAS
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Outline
Todays class presentation will cover the following:
Brief introduction about reservoir modeling and simulation.
1- Reasons to perform reservoir modeling.
2- Types of Computer Modeling
3- Simulation approaches.
4- Types of Numerical Models.
5- Modeling Concepts
6- Reservoir Simulation Steps.
Reservoir simulator classifications
Why it is accepted?.
Introduction To Commercial Reservoir Simulators
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Introduction
Reservoir modeling
Is often defined as the allocation of resources to optimize hydrocarbon
recovery from a reservoir while minimizing capital investments and
operating expenses.
The primary objective in a reservoir management study is to determine the
optimum conditions needed to maximize the economic recovery of
hydrocarbons from a prudently operated field.
Reservoir modeling is the most sophisticated methodology available for
achieving the primary reservoir management objective.
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Introduction, cont,
Reasons to perform a model study:
Several reasons to perform a model study. From a commercialperspective, is the ability to generate cash flow predictions.
From two perspectives:
1- corporate impacts
Cash Flow Prediction
Need Economic Forecast of Hydrocarbon Price
2-Reservoir Management
Maximize the economic recovery of hydrocarbon.
Minimize the operation expenses
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History Matching
Prediction
Geological Model
Reservoir Simulation Model
Reduce Operation Expenses
Increase Recovery
Introduction, Cont,
Prediction of Future Performance
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Introduction, cont, Need Data !
John, R. Fanchi Principles of Applied Reservoir Simulator
Available Data
Not Enough Data: Analogy with other
reservoirs
Correlation Assumption
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Integrated Model
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Introduction, cont,
Gridding
Honor geology
Preserve numerical accuracy
Be easy to generate
Gurpinar, 2001
Wolfsteiner et al., 2002
Prevost 2003
Khalid Aziz, Petroleum reservoir simulation 8
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Introduction, cont,
Reservoir Sampling and Scales
Soft Data: Seismic Data related to interpretation
Hard Data: Core and well log measurements
Conceptual scales:
Giga scale Include information associated with geophysical techniques,
such as reservoir architecture
Mega scale Deals with reservoir characterization and it includes well
logging, well testing and 3D seismic analysis
Macro scale Core analysis and fluid property analysis
Micro scale Includes pore scale data obtained from techniques such as thin
section analysis and measurement of grain size distribution
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Introduction, cont,
Upscaling
There are many techniques and levels, which are available for
upscaling purpose. Make sure to select the best and optimum
level of and techniques to minimize the associated errorsGurpinar, 2001
Khalid Aziz, Petroleum reservoir simulation 10
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Summary
To summarize the need for reservoir simulation :
To obtain accurate performance predictions for a hydrocarbon reservoir under
different operating conditions.
In a hydrocarbon-recovery project (which may involve a capital investment of
hundreds of millions of dollars), the risk associated with the selected development
plan must be assessed and minimized.
Factors contributing to the risk:
1. The complexity of the reservoir because of heterogeneous and anisotropic rock
properties;
2. Regional variations of fluid properties and relative permeability characteristics;
3. The complexity of the hydrocarbon- recovery mechanisms; and
4. The applicability of other predictive methods with limitations that may make them
inappropriate (can be controlled through proper use of sound engineering practices
and judicious use of reservoir simulation).
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Reservoir Simulator
Reservoir simulators are computer programs that solve the equations for
heat and mass flow in porous media, subject to appropriate initial and
boundary conditions.
The number and type of equations to be solved depends on:
geological characteristics of the reservoir (single or double
porosity),
characteristics of the oil, and
oil recovery process to be modeled.
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Types of Computer Modeling
The reservoir
model Fluid flow Equation within the reservoir. The reservoir is modeled by subdividing the reservoir
volume into an array, or grid, of smaller volume elements, which called: gridblock, cell, or node.
The well model Fluid flow that represents the extraction of fluids from the reservoir or the injection of fluids into
the reservoir.
The well bore
mode
Fluid flow from the sand face to the surface
The surface
model Constraints associated with surface facilities, such as platform and separator limitations.
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Simulation Approaches
Broadly classified, there are two simulation approaches we can take:
analytical (Physical) and numerical (mathematical).
The analytical approach, as is the case in classical well test analysis,
involves a great deal of assumptionsin essence, it renders an exact
solution to an approximate problem.
The numerical approach, on the other hand, attempts to solve the more
realistic problem with less stringent assumptionsin other words, it
provides an approximate solution to an exact problem.
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The Simulation Process
Recovery process
Nonlinear PDENonlinear Algebra
Equations
Solution starts here!!!
linear Algebra Equations
Pressure, Saturation Distributions,
and Well Rates
Numerical Reservoir Simulation Process
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Types of Numerical Models
Black oil
Compositional
Chemical flood
Thermal
Dual porosity (fracture)
Gas model (gas gathering system)
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Types of Numerical Models, cont, Black oil model
Depletion Water Injectiono Component: oil water gas
o Phase: Oil water gas
Gas injection to increase or maintain reservoir pressure Miscible flooding as the injection gas goes into solution with oil Carbon dioxide flooding, with the gas soluble in both oil and water Thick reservoirs with a compositional gradient caused by gravity Reservoirs with fluid compositions near the bubble-point High-pressure, high temperature reservoirs Natural-fracture reservoir modeling.o Component: C1,C2, .So2, H2S, N2,..
o Phase: Oil water gas
Polymer and surfactant injectiono Component: Water oil surfactant alcohol
o Phase: Agues oleic micro-emulsion
Compositional model
Chemical model
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Modeling Concepts
1. Developing study objectives.
2. Develop or select an appropriate simulator.
3. Review, collect and estimate appropriate data.
4. Make preliminary runs to establish model parameters and limitations.
5. Match available history.
6. Predict performance under different operating scenarios.
7. Analyze results and prepare a report.
8. Plan additional work.
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Reservoir Simulation Steps
Essential steps in a simulator are:1. Read input data (include reservoir description)
2. Initialize
3. Start time-step calculations
linearize equation,
start iteration loop (Newtonian iterations),
solve linear equations by direct or iterative methods,
test for convergence, and
repeat iterations if necessary.
4. Print and plot results at appropriate times
5. End if specified constraints are violated
6. Increment time and go to step 3 if end is not reached
7. End when run complete
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Historical Developments
Evolution of reservoir engineering and reservoir simulation
is outlined in this section. The comments that follow are
divided into three categories:
Traditional Reservoir Engineering (1930 -)
Early Reservoir Simulation (1955 1970)
Modern Reservoir Simulation (1970 onward)
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Analogy - Well Productivity- Recovery Factors
- Reservoir Data
Experimental - measure the reservoir characteristics inthe laboratory models
- Scale these results to the entire
hydrocarbon accumulations
Mathematical - Basic conservation laws andconstitutive equations
- Material Balance (continuity equation)
- Equation of motion (momentum
equation)
- material balance+ decline curve+
statistical approaches+ analytical
methods(pressure-transient and
BuckleyLeverett methods)
- Finite Element
- Finite Difference
Reservoir Models Used: History of
Simulation
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Reservoir Simulator Classifications
They can be classified in different approaches based on:
1. Type of reservoir fluids being studied (include gas, black oil, and
compositional simulators) and the recovery processes being modeled (include
conventional recovery (black oil), miscible displacement, thermal recovery,
and chemical flood simulators).
2. The number of dimensions (1D, 2D, and 3D), the number of phases (single-
phase, two-phase, and three-phase), and the coordinate system used in the
model (rectangular, cylindrical, and spherical).
3. Rock structure or response (ordinary, dual porosity/permeability, and coupled
hydraulic/thermal fracturing and flow).
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Why it is accepted???
The widespread acceptance of reservoir simulation can be attributed to
the advances in:
A. computing facilities
B. mathematical modeling
C. numerical methods
D. solver techniques, and
E. visualization tools
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Eclipse Reservoir Simulator
Commercial reservoir simulator for over 25 years
Black-oil
Compositional
Thermal
Streamline
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Eclipse Reservoir Simulator
Local Grid Refinement
Gas Lift Optimization
Gas Field Operations
Gas Calorific Value-Based
Control
Geomechanics
Coalbed Methane
Networks
Reservoir Coupling
Flux Boundary
Environmental Traces
Open-ECLIPSE Developer's Kit
Pseudo-Compositional
EOR Foam
EOR Polymer
EOR Solvent
EOR Surfactant
Wellbore Friction
Multisegmented Wells
Unencoded Gradients
Parallel ECLIPSE
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