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Geostatistics


Number of points (ECTS):  5
Course starts:  Autumn
Teaching semester:  1
Evaluation:  Autumn
Course code:  MPG170-1

Faculty of Science and Technology
Department of Petroleum Engineering

Subject teacher(s)
Svein M. Skjæveland head of department
Reidar Brumer Bratvold principal coordinator

Introduction

The objective of this course is to teach the basic science, technology and related assumptions involved in applying geostatistics to carry out an integrated reservoir characterization study. It will prepare students to understand and interpret techniques that are most frequently used in commercial software and will also include an introduction to and use of commercial software applications (but the emphasize in the course is on methods and models used in the software and not the software usage itself). The emphasis is on providing students with knowledge of the fundamentals of geostatistics as well as providing an introduction to commonly used commercial reservoir characterization applications. The core of the course is around data analysis and constructing static geology models. Data sources, quality, relevance and choice of modeling techniques will be covered. This is followed by classical gridding, mapping and contouring. Kriging is introduced as a data-driven (variograms) form of classical mapping (estimation) and a means of data integration. Simulation techniques are introduced as a means of modeling heterogeneity and uncertainty. Scaling (grids and properties) for the purpose of reservoir simulation is the final topic.

The second part of the course will focus on the integration and application of all the major ideas through the use of commercial reservoir characterization applications.

Learning outcome

After completing this course the student should be able to:

  • understand the role of geostatistic in reservoir characterization.
  • understand the main methods used in geostatistics and what they can and cannot do.
  • have the skills needed to use the basic geostatistical methods to analyze data and to estimate and simulate reservoir properties conditioned on data.
  • understand where geostatistics fit within the overall reservoir-modeling workflow.
  • Contents

  • Overview of Geostatistics for Reservoir Characterization.
  • Data Sources, Quality and Analysis.
  • - Types, scales, uncertainty.

    - Short review of Probability.

    - Univariate and bivariate Statistics.

    - Measuring & Modeling Spatial Continuity (Variograms).

  • Framework Modeling - Mapping, Contouring, Faults.
  • Grid Types, Design and their relation to reservoir features and model purpose.
  • Geostatistical Estimation.
  • - Geostatistical Concepts.

    - Kriging.

    - Estimation of Dependent Variables.

  • Geostatistical Simulation.
  • - Simulation versus Estimation.

    - Sequential Indicator Simulation.

    - Object Modeling.

  • Up-gridding & Up-scaling.
  • - Simple averages, Pressure solver.

  • Commercial applications.
  • - Integrated Reservoir Characterization Case Study.

    Prerequisites

    Applicants for single subjects need to meet the requirements for admission to the master programme in Petroleum Geosciences Engineering.

    Recomended prerequisites
    MOT320 Mathematical Statistics - Petroleum

    Exame  
    Assessment Weight Duration Supporting materials
    Portfolio evaluation: tests, exercises, class participation1 / 1

    The grade for the course will be based on tests (40%), exercises (40%) and class participation (20%). Class participation will be evaluated subjectively. As the instructor, I value attendance, punctuality, familiarity with the required readings, and classroom questions or comments that are relevant and insightful. Differences in technical background or skill are not a criterion. In general, I evaluate classroom participation on the basis of the extent to which you contribute to a positive and effective learning environment (for yourself and others). Demonstrating mastery of advanced topics at inappropriate times does not contribute to a positive learning environment. Correcting me when I make a mistake, however, or asking what may appear to be a naive question, quite often contribute positively. ("Dumb" questions, which rarely are that, are usually shared by many students, and asking one can keep the class on track).

    Because the course consists of continuous practical evaluation, no final exam is offered for this course. If a student fails the course or wants to improve the grade, she/he needs to take the course over again.

    Available for private candidates: No

    Only available to students in

    - Bachelor level at the Faculty of Science and Technology.

    - Master level at the Faculty of Science and Technology.

    - PhD level at the Faculty of Science and Technology.

    Method of work

    Lectures and exercises.



    Literature

    Selected papers + book to be decided prior to course start.





    Year 2010/2011
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