introduction to pcb3053

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PCB/PAB3053RESERVOIR MODELLING AND SIMULATION

SEPT 2013

Dr. Mohammed Abdalla Ayoub

Introduction to Reservoir Simulation

Petroleum Engineering Department (GPED)

UNIVERSITI TEKNOLOGI PETRONAS



About the Course

Learning Objectives and outcomes

At the end of this course, students should be able to:

1. To organize the workflow for reservoir simulator.

2. To apply basic equations of fluid flow in porous media to

various type of reservoir simulator.

3. To apply finite different schemes and matrix solver in a Black

Oil Simulator.

4. To perform simulation study using a commercial simulator.



In details

At the end of this course you :

• Be able to describe what is meant by a simulation model, saying what

analytical models and numerical models are.

• Be familiar with what specifically a reservoir simulation model is.• Be able to describe the simplifications and issues that arise in going from the

description of a real reservoir to a reservoir simulation model.

• Be able to describe why and in what circumstances simple or complex

reservoir models are required to model reservoir processes.

• Be able to list what input data is required and where this may be found.

• Be able to describe several examples of typical outputs of reservoir

simulations and say how these are of use in reservoir development.

• Know the meaning of all the highlighted terms ‐ or terms referred to history

matching, black oil model, transmissibility, pseudo relative permeability etc.



Course objectives

And finally (the ultimate goals) you will be able:

To build a model of the reservoir and to examine its performance in terms of

production and pressure.

To predict future performance

To find ways to increase ultimate recovery or to recover the hydrocarbons more

economically (profitability).



Weekly Timetable

ClassLab

Tutorial



Subject Synopses

Students are introduced to:

Basic equations of fluid in porous media for single and multi‐phase flowin 1, 2 and 3 dimensional Cartesian and polar coordinate systems.

Various Finite‐Difference

‐Approximations to obtain an algebraic system

of equations.

Different solution procedures including direct and iterative methods.

The IMPES solution procedure.

An introduction to compositional simulation and EOS. Upscaling and pseudo functions concepts.

The students will perform different simulation run to study the relation between input parameters on simulation results.



Course Outcomes

• Identify the different steps (workflow) for developing areservoir simulator

• Recognize the basic equations of fluid flow in porous media andtheir application in different types of reservoir simulators

• Apply different schemes of finite difference approximation fordifferent grid type and different BC’s and the different

solution procedure• Identify the data needed for simulation study and explain the

relationship between simulation parameters and simulator

performance



Course Outline

Week1 Date Chapter Remarks

1 23/9/2013 Introduction & fundamental (2 hours)

2 30/9/2013 Basic equations (5 hours)

5 17/10/2013 Finite Difference Approximation (6 hours)

Mid -Semester Break (7 – 10 November)

10 11/11/2013 Matrix Solvers (2 hours) TEST 1 (week 9)

11 18/11/2013 Black Oil Simulation (6 hours) Project

12 9/12/2013 Solution Methods (3 hours)

13 19/12/2013 Compositional simulation (2 hours)

16 26/12/2013 Pseudo Functions and Upscaling (1 hour) TEST2 (week16)

Study Week (28 Dec-01Jan 2014)

The F inal examination i s comprehensive



Course Policy• Course instructor: Dr. Mohammed Abdalla Ayoub, [email protected],

x7086

(the E-learning usage will be the medium and it is encouraged to communicate through itas much as possible)

•Punctuality: – Class : Do not be later than the lecturer

– Assignments: due date and time are strictly enforced. Submissions are to be made via E-Learning , and deadlines will be according to E-Learning time. Advisable to submit earlier and just 30 minutes or less before deadline.

•

Quizzes will be unannounced but some will be online through e-learning (maximumtrials of two will be given to each student in a predefined period)

• Attendance will be recorded and barring of students from the final exam for attendanceof less than 90% will be enforced. Tutorials when scheduled are included in the teachinghours.

•E-Learning: It is the

students’ responsibility to refer to E-Learning daily for anyinstruction that may be given outside the class

mailto:[email protected]










Teaching Mode

• Syllabus and outcomes are attached

• There will a lot of discussion and group work. Reading

assignment materials will be considered part of theclasses and can be included in the test and/or finalexamination.

• Fundamental classes will concentrate more on developing

strong background about simulation concepts. Manyassessments will be considered including pop-quizzes,assignments and presentations.



• Final Exam 40%

• Course work 60%

Assessment



Coursework’s Grade Distribution

Item Number

Marks

Assignments 4 8

Quizzes

5-6

9

Test 1 1 15

Test 2 1 15

project 2 10

Others (observations, innovations … etc.) Unspecified 3

Total 60



Outline

About thi s class

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.

Historical Developments (about the progress in reservoir simulation‐ from the beginning to current practices).

Reservoir models used: history of simulation

Reservoir simulator classifications

Why it is accepted?.

Introduction To Commercial Reservoir Simulators



Introduction

Reservoir modeling

It exists within the context of the reservoir management function. Although not

universally adopted, reservoir management 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.



Introduction, cont…,

Reasons to perform a model study:

• from a commercial perspective, 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



History Matching

Prediction

Geological Model

Reservoir Simulation Model

Reduce Operation Expenses

Increase Recovery


Prediction of Future performance



Introduction, cont…, Need Data !

John, R. Fanchi Principles of Applied Reservoir Simulator

Available Data

Not Enough Data: – Analogy with other

reservoirs – Correlation

– Assumption



Integrated Model




Gridding

• Honor geology

• Preserve numerical accuracy

• Be easy to generate

Gurpinar, 2001

Wolfsteiner et al., 2002

Prevost 2003

Khalid Aziz, Petroleum reservoir simulation




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




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 errors

21

Gurpinar, 2001

Khalid Aziz, Petroleum reservoir simulation



Summary

To summar ize 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).



Reservoir Modeling

What is Reservoir modeling:

It is the application of a computer simulation system to the description of fluid

flow in a reservoir.

The computer simulation system is usually just one or more computer

programs.

To minimize confusion, the computer simulation system is called the

reservoir simulator, and the input data set is called the reservoir model.

• Reservoir simulation combines physics, mathematics, numerical analysis,

reservoir engineering, and computer programming (engineering experience

and practice) to develop a tool for predicting hydrocarbon-reservoir

performance under various operating conditions.



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.



Types of Computer Modeling

The reservoir

modelFluid 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



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 assumptions — in 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 assumptions — in other words, it provides an

approximate solution to an exact problem.



Types of Numerical Models

Black oil

Compositional

Chemical floodThermal

Dual porosity (fracture)

Gas model (gas gathering system)

f i l d l



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 bubblepoint

High-pressure, high temperature reservoirs

Natural-fracture reservoir modeling.

o Component: C1,C2, ….So2,H2S,N2,..

o Phase: Oil water gas

Polymer and surfactant injection

o Component: Water oil surfactant alcoholo Phase: Aqueous 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.



Reservoir Simulation Steps

Essential steps in a simulator are:1. Read input data (include reservoir description)2. Initialize3. Start timestep 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 times5. End if specified constraints are violated6. Increment time and go to step 3 if end is not reached7. End when run complete



Reservoir Simulation Steps, cont…,

Or simply the Method can be repeated as:

– dividing the reservoir into a number of blocks

– Basic data is provided for each block

– Wells are positioned within the arrangement of blocks

– The required offtake rate is specified as a function of time

– The appropriate equations are solved to give the pressure and saturations for each block as well as

the production of each phase from each well



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)



Traditional Reservoir Engineering (1930 -)

Computations with slide rules and mechanical calculators

Representation of reservoir by a single block

One-dimensional analytical solutions for linear two-phase flow and

radial single phase flow



Early Reservoir Simulation (1955 - 1970)

Simulation took months to years for one reservoir

Key word driven interfaces

Difficult work flows integrating maps and nodal analysis

Expert users and long time frames

Not applicable for most assets and real time reservoir management

Applied to top 5% of all assets or less

Assets with long lead times before development

Larger assets and most assets had good permeability

Good economics with or without simulation



Modern Reservoir Simulation (1970 - )

• High level of confidence and high cost

• Large number of blocks with local grid refinement and irregular shape

• Efficient methods for solving nonlinear equations

• Robust methods for solving large systems of linear equations

• Multi-component fluid description

• Improvements in the understanding of complicated processes

• Use of graphics and workstations

• Availability of supercomputers

• Improvements in handling of wells



Today!!!

And today:

Models constructed in minutes to hours to days by everyday engineers

Modern interfaces greatly facilitate work flows

Mapping and nodal analysis seamlessly integrated

Real time reservoir management possible

Smaller offshore and tight reservoirs are the norm

Require optimal development to be economic



• Analogy - Well Productivity

- Recovery Factors

- Reservoir Data

• Experimental - Measure the reservoir characteristics in

the laboratory models

- Scale these results to the entire

hydrocarbon accumulations

• Mathematical - Basic conservation laws and

constitutive equations

- Material Balance (continuity equation)

- Equation of motion (momentumequation)

- material balance + decline curve+

statistical approaches+ analytical

methods (pressure-transient and

Buckley – Leverett methods)

- Finite Element

- Finite Difference

Reservoir Models Used: History of

Simulation



Reservoir simulator classifications

can be classified in different approaches based on:

1. Type of reservoir fluids being studied (include gas, black oil, and compositionalsimulators) 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 coupledhydraulic/thermal fracturing and flow).



RECOVERY PROCESS

PRIMARY

1- Gas Cap Expansion

2- Solution gas drive

3- Rock expansion

4- Water drive

5- Gravity drainage

SECONDARY

1- Water flood2- Pressure maintenance

ENHANCED

Miscible:

1- Hydrocarbon flood2- Co2 flood

3- Alcohol flood

4- Enriched gas drive

5- Vaporizing gas drive

Thermal:

1- Steam injection

2- In-situ combustion

3- Wellbore heating

4- hot water injection

Chemical:

1- Alkaline

2- Surfactant

3- Polymer

4- Foam



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



Introduction To Commercial ReservoirSimulators

ECLIPSE

GPRS

SENSOR

NEXUS

UTCHEM

Boast 3

COMET3

…

Objective

Accuracy

Time Limitations

User friendly

Easy to integrate

…



Eclipse reservoir simulator

• Commercial reservoir simulator for over 25 years

•Black-oil

• Compositional

• Thermal

• Streamline



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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