Ch 1 Introduction to Reservoir Modelling Simulation

RESERVOIR MODELLING & SIMULATION PCB3053

JANUARY 2016 Chapter 1 (Introduction to Reservoir Modelling & Simulation)

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Course Background Lecturers • Mr Juhairi Aris bin Muhamad Shuhili • Dr Mohammed Idrees Ali

Reference Material Basic Applied Reservoir Simulation by Turgay Ertekin

Course Code PCB 3053

Assessment • Individual Lab Project (15%) • Eclipse Project (7.5%)

• Lab Report (5%) • Presentation (2.5%)

• CMG Project (7.5%)

Class Participation will contribute up to 5% - Mr. Aris

• Lab Report (5%) • Presentation (2.5%)

• Pop Quizzes (2.5%) • Tutorials (2.5%) • Assignment (10%)

• Assignment 1 (5%) (Mr. Juhairi Aris) • Assignment 2 (5%) (Dr. Mohammed Idrees Ali)

• Test 1 (15%) (Mr. Juhairi Aris) • Test 2 (15%) (Dr. Mohammed Idrees Ali) ---------------------------------------------------------Total coursework 60% Final exam 40% • Attendance must be more than 90% • 2 Lectures, 1 Tutorial and 1 Lab Session per week (except for the first week). • Software: Schlumberger Eclipse and CMG

Enlightenment • Outcome-Based Education (OBE) • Engineering Accreditation Council (EAC) • Board of Engineers Malaysia (BEM) • The Institution of Engineers Malaysia (IEM)

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Course Outcomes • Identify the different steps (workflow) for developing a reservoir simulator • Identify the basic equations of fluid flow in porous media applied to various type of reservoir simulator. • Apply simple finite different schemes and matrix solver in a Black Oil Simulator. • Conduct simulation study using a commercial simulator

Course Schedule Week 1

Chapter

Lecturer

Chapter 1: Introduction to Reservoir Modelling & Simulation

Mr. Juhairi Aris

2-3

Chapter 2: Principles & Application of Finite Difference

Mr. Juhairi Aris

3-5

Chapter 3: Matrix Solver

Mr. Juhairi Aris

Chapter 4: History Matching & Error Analysis

Mr. Juhairi Aris

6-10

Chapter 5: Effects of Simulation Parameters on the Performance of a Simulator.

Dr. Mohammed Idrees Ali

10-12

Chapter 6: Introduction to Compositional Simulators

Dr. Mohammed Idrees Ali

12-14

Chapter 7: Analysis of a full field simulation project from workflow of the project

Dr. Mohammed Idrees Ali

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Course Tentative (Mr Juhairi Aris) Tentative

Date Release Date – Week 3

Assignment 1 – Chapter 1 – 2 Submission Date – Week 4 Test 1 – Chapter 1 to 4

Week 6 – During Tutorial Eclipse Project – Week 7

Lab Report Submission & Presentation

CMG Project – Week 12

Pre-requisites • Reservoir Engineering 1 (Compulsory) • Structural Programming and Database System (Compulsory) • Reservoir Rock & Fluid Properties (Highly Recommended) • Vector Calculus (Highly Recommended) • Computational Method (Highly Recommended) • Differential Equation (Highly Recommended)

Chapter Learning Outcome • To discuss the importance of reservoir simulation. • To describe different types of simulation models/methods. • To differentiate the function of each type of simulation model.

• To explain how a simulator works and the evolution of reservoir simulation over the time.

Chapter Learning Outcome • 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 list what input data is required and where this may be found. • Be able to compare the differences between what reservoir simulations can do at the appraisal and in the mature stages of reservoir development. • Know all the types of reservoir simulation models (simulators) and what type of problem or reservoir process each is used to model. • Know the key steps of the reservoir simulation study required for the field development plan (FDP). 10

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Reservoir Simulation • Reservoir simulation is an important and useful tool in reservoir management. Reservoir engineer can utilise it under different operating conditions to predict the reservoir performance. This is the main advantage of reservoir simulation. Prediction of performance accuracy is really important because oil and gas project usually costs huge capital. • Reservoir simulation can be done at any stage. • Reservoir simulation is done by solving the partial differential equations for single or multiphase flow using complex numerical method. • Reservoir simulation is divided into 2 main branches which are history matching and performance forecasting. • Reservoir simulation is defined as the process of using the behaviour of a model of the reservoir to represent or approximate the behaviour of the true reservoir.

Reservoir Simulator • Reservoir simulators use numerical methods and high-speed computers to model multidimensional fluid flow in reservoir rock. • Main components of a simulator • • • • •

Geological model Reservoir model Fluid model Petro-physical model Mathematical model.

Mathematical Model • A mathematical model is described by a set of partial differential equations (PDEs) which describe mass transport in region occupied by the reservoir together with initial and boundary conditions. • The set of PDEs plus the initial and boundary conditions is referred to an initial boundary value problem. • If the model is sufficiently simple, we may be able to solve the IBVP analytically • For example, if we assume linear, incompressible steady-state flow in homogeneous reservoir, neglect capillary pressure and gravity effects, we can solve for the saturation profile and compute performance, analytically. • For instance, most well testing theory is based on models which have analytical or semi-analytical solutions. • For most problems, of interest, however, the IBVP cannot be solved analytically and thus we use a numerical model (or simulator), which is based on the application of numerical methods to obtain an approximate solution of the IBVP

Data Needed • Reservoir properties • • • •

Permeability & Porosity Thickness Dimensions & Geometry Initial pressure & Saturations

• Fluid properties • Viscosity & Density • Formation Volume Factor

• Petro-physical properties • Relative Permeability • Capillary Pressures • Compressibility

• Past production history • • • • • •

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WOR GOR Pressure Rate Temperatures in the case of non-isothermal flow Concentrations in the case of tracer flow

Faults, fluid contacts • OWC and GOC

Data Considered by Reservoir Modelling Methods

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Reservoir Simulation Reservoir simulation requires knowledge from several disciplines • Engineering • Physics • Chemistry • Mathematics • Computer programming

Heterogeneity & Anisotropy • Heterogeneity refers to the variation of permeability with respect to location. • Anisotropy refers to the variation of permeability with respect to direction. The vertical permeability is usually lower than horizontal permeability due more variation of strata vertically than horizontally. • In real case, a reservoir is always heterogeneous and anisotropic. • Reservoir simulation is the only technique in modelling fluid flow which considers heterogeneity and anisotropy. This is another advantage of reservoir simulation.

Heterogeneity & Anisotropy

Material Balance vs Reservoir Simulation Material Balance

Reservoir Simulation

Consider a single tank size

Consider from 1000 – 1000000 million cells

Doesn’t incorporate heterogeneity

Cater for heterogeneity

Flow parameters are not introduced

Darcy’s flow is a main equation

Doesn’t need static modelling

Static modelling must be done before reservoir simulation

Utilizes conservation of volume principle

Uses Darcy, Continuity, EOS, Partial Differential Equation and numerical method

Easy and less expensive

Higher cost and more effort needed

Less Accurate

More Accurate (very accurate if history matched)

Vector & Scalar Quantities • Scalar quantities have only magnitude such as pressure, length and time. • Vector quantities have both magnitude and direction such as displacement and velocity.

Pressure & Potential • In 1-D flow horizontal flow, the effect of gravity is often neglected. However, in vertical flow the effect of gravity plays an important role in determining the direction of flow. • The resultant direction of flow can be computed by taking into consideration of pressure difference and gravitational force. The combined term of pressure difference and gravitational force is known as potential term. •

Permeability Tensor • In an anisotropic media, pressure difference can be applied in all 3 directions and in each direction, the permeability can be measured in 3 directions. • This will result in a 3 x 3 matrix tensor. Tensor is actually a generic term. Scalar is zero rank tensor while vector is first rank tensor. Scalar will form 1 x1 matrix while vector will form 3 x 1 matrix. • In the case of permeability, the matrix formed is a symmetrical matrix. It means the Kxy = Kyx, Kxz = Kzx, and Kzy = Kyz.

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Clear Objectives Examples of Reservoir Study Goals Typical Goals for New Fields (Appraisal Stage): • Define reservoir’s internal & external boundaries • Define reservoir pay, volume, & reserves

• Determine optimum number, location, & configuration of wells • Optimize timing and sizing of facilities • Select optimum recovery process • Estimate potential recovery performance • Anticipate future produced fluid & operational changes

• Determine critical gas and water coning rates 26

Key Steps in a Simulation Study 1. Clear Objectives

Compare & Adjust

2. Reservoir Characterization 3. Model Selection 4. Model Construction 5. Model Validation 6. Predictions 7. Documentation 27

Clear Objectives Examples of Reservoir Study Goals Typical Goals for Mature Fields: • Monitor fluid contact movement

• Evaluate productivity degradation • Evaluate historical reservoir performance. Determine why performance did not match predicted recovery

• Determine source of produced water and/or gas. Identify wells with workover potential • Monitor reservoir sweep to locate by-passed oil

• Specify infill drilling requirements • Estimate benefits of secondary recovery or EOR • Determine connectivity between multiple reservoirs 28

Key Steps in a Simulation Study 1. Clear Objectives

Compare & Adjust

2. Reservoir Characterization 3. Model Selection 4. Model Construction 5. Model Validation 6. Predictions 7. Documentation 29

Reservoir Characterization Three Inter-Dependent Components

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Reservoir Characterization

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Reservoir Characterization

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Reservoir Characterization

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Key Steps in a Simulation Study 1. Clear Objectives

Compare & Adjust

2. Reservoir Characterization 3. Model Selection 4. Model Construction 5. Model Validation 6. Predictions 7. Documentation 34

Model (Simulator) Selection Aspects of Model 1. Process 2. Dimensionality 3. Approach

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Model (Simulator) Selection Determine the Process 1. In reservoir simulation, fluid flows through one grid block to another. The pressure, saturation and sometimes the compositions are monitored while the fluids flow through the cells. In black oil simulation, the composition change is neglected while in compositional simulation, the composition change is considered. 2. The Black Oil Model 3. Compositional simulation is involved when phase change is prominent such as for volatile oil, condensate gas or whenever an Enhanced Oil Recovery process (EOR) is involved. 4. More Complex Reservoir Simulation Models: • The Chemical Flood Model • Thermal Models • Dual-Porosity Models of Fractured Systems • Coupled Hydraulic, Thermal Fracturing and Fluid Flow Models

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Model (Simulator) Selection The Black Oil Model: It treats the three phases - oil, gas and water - as if they were mass components where only the gas is allowed to dissolve in the oil and water. This gas solubility is described in oil and water by the gas solubility factors (or solution gas-oil ratios), Rso and Rsw, respectively.

Schematic of a grid block in a black oil simulator

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Model (Simulator) Selection The Black Oil Model: Reservoir processes that can be modelled using the black oil model include: • Recovery by fluid expansion - solution gas drive (primary depletion). • Water flooding including viscous, capillary and gravity forces (secondary recovery). • Immiscible gas injection. • Some three phase recovery processes such as immiscible wateralternating- gas (WAG). • Capillary imbibition processes.

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Model (Simulator) Selection The Compositional Model: A compositional reservoir simulation model is required when significant inter-phase mass transfer effects occur in the fluid displacement process. This model usually defines three phases (gas, oil and water) but the actual compositions of the oil and gas phases are explicitly acknowledged due to their more complicated PVT behavior. That is, the separate components (C1, C2, C3, etc.) in the oil and gas phases are explicitly tracked.

The view of phases and components taken in compositional simulation. Cij is the mass concentration of component i in phase j (j = gas, oil or water) 39

Model (Simulator) Selection The Compositional Model: Examples of reservoir processes that can be modelled using a compositional model include: • Miscible Gas injection (first contact or multi- contact miscibility, e.g. in CO2 flooding).

• The modelling of gas injection into near critical reservoirs. • Gas recycling processes in condensate reservoirs.

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Model (Simulator) Selection The Chemical Flood Model: • This model has been developed primarily to model alkaline, polymer and surfactant (or combined) displacement processes. • Polymer flooding can be considered mainly as extended water flooding with some additional effects in the aqueous phase which must be modelling e.g. polymer component transport, the viscosification of the aqueous phase, polymer adsorption, permeability reduction etc. •

Surfactant, flooding however, involves strong phase behaviour effects where third phases may appear which contain oil/water/surfactant emulsions.

• Extended chemical flood models are also used to model foam flooding. 41

Model (Simulator) Selection The Chemical Flood Model: Examples of reservoir processes that can be modelled using a chemical flood model include: • Polymer flooding which can be thought of as an “enhanced waterflood” to improve the mobility ratio and hence improve the microscopic sweep efficiency and also to reduce streaking in highly heterogeneous layered systems; • Polymer/surfactant flooding where the main purpose of the surfactant is to lower interfacial tension (IFT) between the oil and water phases and hence to “release” or “mobilize” trapped residual oil; the polymer is for mobility control behind the surfactant slug; • Low-tension polymer flooding (LTPF) where a more viscous polymer containing injected solution also contains some surfactant to reduce IFT; the combined effect of the lower IFT and viscous drive fluid improves the sweep and also helps to mobilize some of the residual oil; • Alkali flooding where a solution of sodium hydroxide is injected into the formation. The sodium hydroxide may react with certain components in the oil to produce natural "soaps" which lower IFT and which may help to mobilize some of the residual oil; 42

Model (Simulator) Selection The Chemical Flood Model: Examples of reservoir processes that can be modelled using a chemical flood model include: • Foam flooding where a surfactant is added during gas injection to form a foam which has a high effective viscosity (lower mobility) in the formation than the gas alone which may then displace oil more efficiently. • Another near-wellbore process that can be modelled using such simulators in water shut-off using either polymer-crosslinked gels or so-called “relative permeability modifiers”.

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Model (Simulator) Selection Thermal Models: Examples of reservoir processes that can be modelled using thermal models include: • Steam “soaks” where steam in injected into the formation, the well is shut in for a time to allow heat dissipation into the oil and then the well is back produced to obtain the mobilized oil (because of lower viscosity). This is known as a “Huff n’ Puff” process.

• Steam “drive” where the steam is injected continuously into the formation from an injector to the producer. Again, the objective is to lower oil viscosity by the penetration of the heat front deep into the reservoir. • In situ combustion where - as noted above - an actual combustion process is initiated in the reservoir by injecting oxygen or air. Part of the oil is burned (oxidized) to produce heat and combustion gases that help to drive the (unburned) oil from the system. This is not a common improved oil recovery method but a number of field cases showing at least technical success have been reported in the SPE literature. 44

Model (Simulator) Selection Dual-Porosity Models of Fractured Systems: • These models have been designed explicitly to simulate multiphase flow in fractured systems where the oil mainly flows in fractures but is stored mainly in the rock matrix. • Such models attempt to model the fracture flows (and sometimes the matrix flows) and the exchange of fluids between the fractures and the rock matrix. • The models have been applied to model recovery processes in massively fractured carbonate reservoir such as those found in many parts of the Middle East and elsewhere in the world. • There is quite considerable field experience of modelling such systems in certain companies but there are also doubts over the validity of such models to model flow in fractured systems. 45

Model (Simulator) Selection Aspects of Model 1. Process 2. Dimensionality 3. Approach

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Model (Simulator) Selection Determine the Dimensionality  Use 1D models for linear or radial flow in only one direction  Use 2D models for linear or radial flow in two directions: Radial, areal, cross-sectional  Use 3D models for situations for linear or radial flow in three directions: Pattern element, segment, fullfield

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Model (Simulator) Selection Aspects of Model 1. Process 2. Dimensionality 3. Approach

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Model (Simulator) Selection Determine the Approach

Detailed Geologic Description (May be matched to historic performance)

Higher Uncertainty Properties (Model depends on correlations and assumed data)

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Key Steps in a Simulation Study 1. Clear Objectives

Compare & Adjust

2. Reservoir Characterization 3. Model Selection 4. Model Construction 5. Model Validation 6. Predictions 7. Documentation 50

Model Construction Converting the Geological Model into a Simulation Model 1.

Quality Control (QC) the geological model for errors and problems

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Scale-up the geological model

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Output the geological model in simulation format

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Output fault information for simulation

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Output well data for simulation

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Output production data in simulation formats and link to wells

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Key Steps in a Simulation Study 1. Clear Objectives

Compare & Adjust

2. Reservoir Characterization 3. Model Selection 4. Model Construction 5. Model Validation 6. Predictions 7. Documentation 52

Model Validation

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Model Validation Two important ideas for the proper validation of reservoir models: • History Matching must not be achieved at the expense of parameter modifications that are physically and/or geologically wrong • Even when a model is fully validated, simulation results will still have some degree of uncertainty

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Key Steps in a Simulation Study 1. Clear Objectives

Compare & Adjust

2. Reservoir Characterization 3. Model Selection 4. Model Construction 5. Model Validation 6. Predictions 7. Documentation 55

Predictions Important considerations when making reservoir model predictions: • Prediction cases shouldn’t exceed capabilities of the model. • Predictions need to be consistent with field practices. • Simulation yields a non-unique solution with inherent uncertainties from:  Lack of validation (e.g., reservoirs with sparse geologic or engineering data).  Modeling or mathematical constraints because of compromises made in model selection.  Inherent uncertainties in reservoir characterization and/or scale– up to model dimensions.

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Key Steps in a Simulation Study 1. Clear Objectives

Compare & Adjust

2. Reservoir Characterization 3. Model Selection 4. Model Construction 5. Model Validation 6. Predictions 7. Documentation 57

Documentation Methods to document studies • Technical memorandum • Formal report • Presentation • Store data files • Share lessons learned with future project teams

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Acknowledgement • Prof. Mustafa Onur, UTP (2012-2013) • Dr. Abdalla Ayoub, UTP (2013-Present) • Dr. Mohammed Idrees Ali, UTP (2014-Present)