PCB3053RESERVOIR MODELLING AND SIMULATION

MAY 2015

Dr. Mohammed Abdalla Ayoub

Ch. 1.1: Introduction to Reservoir Simulation

Petroleum Engineering Department (GPED)

UNIVERSITI TEKNOLOGI PETRONAS

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

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

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

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

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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