PETROENG 3001 - Reservoir Simulation

North Terrace Campus - Semester 2 - 2014

The course gives the theoretical basis and practical fundamentals for numerical simulation and analytical modelling of fluid flow in petroleum reservoirs. The partial differential equations required for modelling of single-phase and multi-phase fluid flow in porous media are derived. The governing systems are used for development of several analytical models which serve for reservoir evaluation and analysis. A particular attention is given to empirical functions of transport properties and phase equilibrium that the models contain and which are input functions into reservoir simulators. The numerical methods for solving the basic governing equations using finite difference methods are presented. Input data requirements and applications of simulation models for history matching and prediction of field performance will be discussed. Practical applications are directed to commercial reservoir simulator Eclipse.

  • General Course Information
    Course Details
    Course Code PETROENG 3001
    Course Reservoir Simulation
    Coordinating Unit Australian School of Petroleum
    Term Semester 2
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 4 hours per week
    Assumed Knowledge MATHS 1012, MATHS 2201, MATHS 2104, PHYSICS 1100, PETROENG 2009, MECH ENG 2021, COMP SCI 1201, PETROENG 3025
    Restrictions Available to BE(Petroleum) students only
    Course Description The course gives the theoretical basis and practical fundamentals for numerical simulation and analytical modelling of fluid flow in petroleum reservoirs. The partial differential equations required for modelling of single-phase and multi-phase fluid flow in porous media are derived. The governing systems are used for development of several analytical models which serve for reservoir evaluation and analysis. A particular attention is given to empirical functions of transport properties and phase equilibrium that the models contain and which are input functions into reservoir simulators. The numerical methods for solving the basic governing equations using finite difference methods are presented. Input data requirements and applications of simulation models for history matching and prediction of field performance will be discussed. Practical applications are directed to commercial reservoir simulator Eclipse.
    Course Staff

    Course Coordinator: Dr Mohammad Sayyafzadeh

    Course Coordinator: Dr Mohammad Sayyafzadeh
    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    1 The ability to understand the basic concepts of numerical and analytical reservoir simulation
    2 The ability to simulate simple cases of reservoir development and to learn in more details the Reservoir Simulator Eclipse
    3 Understand key aspects of reservoir simulation in development of oil and gas fields
    4 The ability to formulate fluid flow in porous media
    5 The ability to solve the governing equations, numerically using finite difference methods
    6 Formulate different strategies of field development based on reservoir simulation
    7 Predict main indicators of the recovery from an oil or gas field under given recovery method
    8 Describe main assumption of major mathematical models for oil and gas production
    9 The ability to tune uncertain parameters of reservoir models using history data
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)
    Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised. 1, 2, 3, 9
    The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 4, 5, 6, 10
    An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 6, 10
    A proficiency in the appropriate use of contemporary technologies. 2, 6, 7
    A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life. 3
    A commitment to the highest standards of professional endeavour and the ability to take a leadership role in the community. 2, 8
  • Learning Resources
    Required Resources

    Not applicable

    Recommended Resources
    1. Crichlow, Henry B., "Modern Reservoir Engineering: A Simulation Approach", Prentice-Hall Inc., New Jersey, 1977.
    2. Aziz, A. & Settari, A., "Petroleum Reservoir Simulation", Applied Science Publishers Ltd., London, 1979.
    3. Ertekin, T., Abou-kassem, J. & King, G., "Basic Applied Reservoir Simulation" SPE, 2001.
    4. Peaceman, D.W., "Fundamentals of Numberical Reservoir Simulation", Elsevier Scientific Publishing Co., 1977.
    5. Thomas, G.W., "Principles of Hydrocarbon Reservoir Simulation", International Human Resources Development Corporation, 1982.
    6. Bedrikovetsky P.G., 1993, Mathematical Theory of Oil & Gas Recovery (With applications to ex-USSR oil & gas condensate fields), Kluwer Academic Publishers, London-Boston-Dordrecht, 600 p.
  • Learning & Teaching Activities
    Learning & Teaching Modes

    Lectures supported by problem-solving tutorials developing material covered in lectures

    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    Lectures 3 hours/week

    Tutorials 1 hour/week

    Homework assignments 5 hours/week

    Home Reading 3 hours/week

    Learning Activities Summary

     I. OVERVIEW AND INTRODUCTION - week 1-2
    Reservoir simulation in petroleum engineering activity

    Reservoir simulation in the sequence of petroleum geoscience and engineering disciplines

    The importance of forecasting reservoir performance

    Methods that provide a forecast, decline curve analysis, streamline simulation and grid-based simulator

    The goals of carrying out reservoir simulation in Petroleum discipline

    A review on the data required for reservoir simulation, porosity, permeability, saturation, pressure, relative permeability, capillary pressure, hysteresis of relative permeability and capillary pressure, three-phase relative permeability, well skin, fluid viscosity, formation volume factor, gas solubility and rock compressibility

    Reservoir simulation in all stages of petroleum development: exploration, secondary migration and formation of petroleum accumulations, exploration welling, appraisal, depletion, preliminary geological model, data from several wells, well interference, secondary recovery, tracer and breakthrough data.

    Direct and inverse problems. Modelling and history matching

    Classification of models in reservoir simulation: single phase models, two-phase flows, black oil model, compositional model, thermal model.

    Commercial reservoir simulators.

    II. TRANSPORT PHENOMENA LAWS IN POROUS MEDIA- weeks 2-3
    Mass conservation law, energy conservation law and the conservation of momentum law

    Darcy’s law - Isotropic and anisotropic media - extended darcy and equation of state (EoS)

    III. NUMERICAL METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS - week 4
    Discretisation, Taylor series, first and second derivative approximation

    Finite difference, implicit and explicit

    Jacobi Iterative method, Fauss-Seidel method

    Boundary value problem and Initial value problem

    Linearisation, Pseudo pressure

    IV. SINGLE PHASE FLOW - weeks 5-6
    Primary recovery. Depletion (pressure blowdown). Mathematical model.

    Example of closed system: flow of gas in reservoirs, 1d, 3d, initial and boundary conditions. Model = mass conservation + EoS + Darcy´s law

    Mass conservation law for single-phase flow

    Darcy´s law for single-phase flow of Newtonian and non- Newtonian fluids, with gravity, accounting for inertial effects, in anisotropic rocks

    Rock compression, Terzhagy eq. Slightly compressible fluid and rock

    Compressibility of fluid/rock and pseudo pressure

    Formulation of single-phase flow in porous-media, oil reservoirs and gas reservoirs

    Analytical model for 1d flow towards well

    V. NUMERICAL METHODS FOR A SINGLE PHASE FLOW - week 7
    Finite difference methods for single phase flow. First- and second difference quotinets. Grid systems. Treatment of initial and boundary conditions. Steady state flows – elliptic problems. Unsteady state flow of compressible fluids – parabolic problems

    VI. TWO PHASE FLOW - week 8
    Derivation of basic equations. Small-scale and large scale approximations

    Features: relative permeability, capillary pressure, phase viscosities and densities. Compressible and incompressible phases

    Formulation of multi-phase flow in porous media, two-phase and three-phase

    VII. NUMERICAL METHODS FOR MULTI PHASE FLOW - weeks 9-10
    Multiphase displacement – hyperbolic problems. Mixed type problems. Formulation of initial and boundary conditions

    Finite difference methods. Matrix solvers. IMPES

    Consistency, stability and convergence. Grid orientation effects

    VIII. WELL MODELLING - week 11
    Well index. Boundary conditions on the well. Pieceman’s condition. Dietz’s factors

    Piecemen’s condition. Rarefied grid.

    IX. HISTORY MATCHING - week 11-12
    Inverse Modelling

    Parameterisation, objective funcation formation, and calibration

    Tuning Alogorithm

    Bayesian formulation and Uncertainty Quantification

    Optimisation algorithms

    Reparameterisation

    Ensamble Kalman Filter

    X. ADVANCED RESERVOIR SIMULATION- week 12
    Compositional models in petroleum exploration. Secondary migration of oil and gas

    Simulationof fractured reservoirs and unconventional resources

    Upscaling

    Steamline Simulation

    Specific Course Requirements

    Not Applicable

  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary

    The course will be assessed with a weighting of 10% based on the results in-class tests and/or quizzes, 15% on assignments, 25% on practical project, and 50% on final exam.

    Assessment Related Requirements

    Compulsory attendance at tutorials is required. Attendance at lectures is highly recommended.

    There will be 2 in-term tests that will count towards the final assessment.

    Dates of the in-term tests will be given via MyUni two weeks in advance.

    Alternative test dates for students who cannot be present on the date of the test on medical and compassionate grounds can be requested through the Course Coordinator.

    Assessment Detail

    Final exam is comprehensive and covers all materials in the course.

    Submission

    Submission of Work for Assessment
    Practical and field class exercises should be submitted in hardcopy with a completed copy of the assessment coversheet that is available from the school office. This should be signed to indicate you have read the above university policy statement on plagiarism, collusion and related forms of cheating.

    Extensions for Assessment Tasks
    Extensions of deadlines for assessment tasks may be allowed for reasonable causes. Such situations would include compassionate and medical grounds of the severity that would justify the awarding of a supplementary examination. Evidence for the grounds must be provided when an extension is requested. Students are required to apply for an extension to the Course Co-ordinator before the assessment task is due. Extensions will not be provided on the grounds of poor prioritising of time.

    Penalty for Late Submission of Assessment Tasks
    Assessment tasks must be submitted by the stated deadlines. There will be a penalty for late submission of assessment tasks. The submitted work will be marked ‘without prejudice’ and 10% of the obtained mark will be deducted for each working day (or part of a day) that an assessment task is late, up to a maximum penalty of 50% of the mark attained. An examiner may elect not to accept any assessment task that a student wants to submit after that task has been marked and feedback provided to the rest of the class.

    Provision of Feedback to Students
    Exercises will be returned to students within two weeks of their submission.

    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

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  • Policies & Guidelines
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