| Number of points (ECTS): | 5 |
| Course starts: | Spring |
| Teaching semester: | 1 |
| Evaluation: | Spring |
| Course code: | DPE360-1 |
Faculty of Science and Technology
Department of Petroleum Engineering
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 field development or exploration program decisions.
Learning outcome
At the end of the course the student is expected 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
- Be able to structure, evaluate, and communicate an unstructured decision problem from the real world
Contents
-Probability
-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
No
Recomended prerequisites
Some knowledge of probability and statistics
| Assessment | Weight | Duration | Supporting materials |
|---|---|---|---|
| Folder evaluation with Tests, Exercises, Class participation and Project | 1 / 1 | No printed or written means are allowed. Definite, basic calculator allowed |
The grade for the course will be based on midterm test (20%) Final test (30%), exercises amd quizzes (20%), class participation (10%), and project work (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.)
Available for private candidates: NoOnly available to students in
Lectures, exercises and project work
Literature
Bratvold, R.B., and S.H. Begg,: Decision-Making under Uncertainty, SPE, 2009 + selected papers
