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Decision Analysis 1


Number of points (ECTS):  5
Course starts:  Spring
Teaching semester:  1
Evaluation:  Spring
Course code:  MPE630-1

Faculty of Science and Technology
Department of Petroleum Engineering

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

Introduction

Everyone makes decisions, but few people think about how they do it. Yet, psychological research shows that we are prone to many different errors of thought that degrade our decision making ability. In this course we will discuss the principles and fundamental concepts for the normative theory of decision making under uncertainty. We will develop a language, set of theories, and tools to transform complex decisions into ones where the course of action is clear. The course follows the typical chain of considerations that attends most exploration and development projects. The skills learnt will be applicable to exploration and production decisions and from relatively small investments, such as whether or not to core a well, to major major field development or exploration program decisions.

Learning outcome

After completing this course the student should be able to:

  • know how to bring engineering principles to bear on decision making.
  • appreciate the challenges we face when making decisions in the face of uncertainty.
  • use the principles of decision analysis to make better decisions in your personal and professional life.
  • communicate your choices and recommendations clearly.
  • recognize and account for the human biases and errors that most often affect decision making.
  • Contents

  • Pobability.
  • Probability as a measure of belief.
  • Bayes` theorem.
  • Probabilistic relevance.
  • Axioms of choice under uncertainty.
  • Utility theory.
  • Risk preference.
  • Normative vs descriptive theories of decision making.
  • Certain equivalents.
  • Value of perfect information.
  • Value of imperfect information.
  • Probabilistic assessment.
  • Influence diagrams.
  • Decision trees.
  • Probabilistic sensitivity analysis.
  • Heuristics and biases in decision making.
  • Prerequisites

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

    Recomended prerequisites

    Some knowledge of probability and statistics.

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

    The grade for the course will be based on tests (50%), exercises and quizzes (30%) 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 innappropriate 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 studies at the Faculty of Science and Technology.

    - Master studies at the Faculty of Science and Technology.

    - PhD studies at the Faculty of Science and Technology.

    Student evaluation

    Questionnare and continuous feedback during lectures.



    Method of work

    Lectures and exercises.



    Literature

    Bratvold, R.B., S.H. Begg, and J.M. Campbell: Decision-Making under Uncertainty, SPE, 2009 + selected papers.





    Year 2010/2011
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