Making Good Decisions

215 Pages·2010·3.783 MB·English

by  Reidar B. Bratvold, Steve Begg

Making Good Decisions
Making Good Decisions
Reidar B. Bratvold
University of Stavanger
Steve H. Begg
University of Adelaide
Society of Petroleum Engineers
© Copyright 2010 Society of Petroleum Engineers
All rights reserved. No portion of this book may be reproduced in any form or by any
means, including electronic storage and retrieval systems, except by explicit, prior
written permission of the publisher except for brief passages excerpted for review and
critical purposes.
ISBN 978-1-55563-258-8
ISBN 978-1-61399-226-5 (Digital)
Society of Petroleum Engineers
222 Palisades Creek Drive
Richardson, TX 75080-2040 USA
http://store.spe.org
[email protected]
1.972.952.9393
Preface
Decision making touches every one of us, professionally and in our personal lives,
from relatively minor decisions to the truly significant. The number of petroleum
companies using decision analysis to support their decision making has grown rap-
idly; however, most petroleum engineers and geoscientists have not been trained in
the subject or are not aware of its full potential. Decision analysis provides both an
overall framework for how to think about difficult problems and a set of tools that
can be used to construct and analyze a model of the decision situation. The end goal
is to gain sufficient insight and understanding to identify the best course of action.
There are many general books on decision making, but the few that are specific
to the oil and gas industry are mainly focused on exploration and at best address
only a subset of decision making topics. This book is intended as an introduction
to the topic for the practicing engineer, geoscientist, team leader, or manager—
one that focuses the key ideas yet has sufficient depth to guide a real application;
one that enables meaningful participation in the decision-making process; or one
that serves as a quick refresher. But the material is also meant to be accessible
to petroleum-industry professionals in other roles, such as legal, accounting,
commercial, or business development, who may need to know the best practices in
decision making.
Although the book is an introduction, it reflects aspects of current research, our
own and others, that are of practical benefit. Our goal is to provide a text that is
simple and accessible but without glossing over important or subtle details. We hope
to impart a good conceptual understanding of the main tools and methodologies,
of why they are important, and of the wide range of decisions to which they are
applicable. Although the content rests upon the academic discipline known as
Decision Science, a subtopic of the broader field of Management Science, theoretical
aspects are introduced only as needed to provide insight. The mathematical content
is presented at a level that should be accessible to most petroleum engineers and
geoscientists. However, you will be required to think—and thinking exercises the
mind more deeply than just following mathematical recipes.
We hope that reading the book gives you an appreciation of the power, practicality,
and usefulness of decision analysis; enables you to make better decisions at work
and at home; and makes you better informed than the majority of your peers and
superiors, thus increasing your value to your organization.
We did not start out as decision analysts. Many people contributed to our current
understanding of the topic, and we particularly owe gratitude to our friends and
collaborators Eric Bickel and John Campbell. We would also like to thank former
students and colleagues, too numerous to list, for stimulating discussions and the
insights we gained from them. Several people have, at various stages, reviewed the
book and suggested valuable improvements. Thanks to Eivind Damsleth, Jim Dyer,
Frank Koch, Marco Thiele, and Gardner Walkup for their constructive suggestions.
We also thank Mary Ellen Yarossi for graciously providing the information from the
IPA database that we refer to in Chapter 1, and Helge Haldorsen for suggesting the
title. Finally, we would like to thank the SPE editors and staff for their diligent work
in improving the book’s readability and keeping this project on track.
Reidar B. Bratvold Steve H. Begg
University of Stavanger, Norway University of Adelaide, Australia
Contents
Preface
1 . Decision Making and Uncertainty in
the Exploration and Production Industry . . . . . . . . . . . . . . . . . . . . 1
1.1 Introduction ......................................... 1
1.2 Decisions in the Exploration and Production (E&P) Industry .... 2
1.3 Decision Making ..................................... 5
1.4 Uncertainty and Decision Making ........................ 9
1.5 Using Models ........................................ 15
1.6 Subsequent Chapters ................................. 16
1.7 Suggested Reading ................................... 16
2 . How to Make Good Decisions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.1 Introduction ......................................... 17
2.2 High-Level Decision-Making Methodology .................. 17
2.3 Decision Elements .................................... 21
2.4 A Decision-Making Methodology ......................... 28
2.5 Phase 1: Framing or Structuring ......................... 29
2.6 Phase 2: Modeling and Evaluating ....................... 37
2.7 Phase 3: Assessing and Deciding ........................ 45
2.8 Assessing Decision Quality ............................. 52
2.9 Summary ........................................... 56
3 . Quantifying Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3.1 Introduction ......................................... 59
3.2 Uncertain Variables ................................... 60
3.3 The Nature of Probability ............................... 61
3.4 The Basics .......................................... 65
3.5 Updating Probabilities With New Information ................ 77
3.6 Probability Models .................................... 80
3.7 Summary ........................................... 91
3.8 Suggested Reading ................................... 92
4 . Monte Carlo Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
4.1 Introduction ......................................... 93
4.2 Procedure .......................................... 94
4.3 Sensitivity Analysis ................................... 100
4.4 Dependencies ....................................... 102
4.5 Expected Value Revisited .............................. 105
4.6 Suggested Reading ................................... 107
5 . Structuring and Solving Decision Problems . . . . . . . . . . . . . . . . . 109
5.1 Decision-Tree Elements ............................... 109
5.2 Building Decision Trees ................................ 112
5.3 Tree Size and Compact Notation ......................... 117
5.4 Solving Decision Trees ................................ 120
5.5 Risk Profiles ......................................... 122
5.6 Sensitivity Analysis ................................... 126
5.7 Decision Trees in the Context of Decision-Making
Methodology ......................................... 128
5.8 Summary ........................................... 129
5.9 Suggested Reading ................................... 129
6 . Creating Value From Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
6.1 Updating Probabilities With New Information ................ 132
6.2 Value of Information ................................... 136
6.3 Value of Flexibility ..................................... 151
6.4 Discussion .......................................... 157
6.5 Implementation Issues ................................. 157
6.6 Additional Reading .................................... 159
7 . Behavioral Challenges in Decision Making . . . . . . . . . . . . . . . . . . 161
7.1 Introduction ......................................... 161
7.2 The Two Decision Systems ............................. 161
7.3 Biases in Judgment and Decision Making .................. 163
7.4 Eliciting and Encoding Probabilities ....................... 176
7.5 Summary—Why We Need Help .......................... 181
7.6 Suggested Reading ................................... 182
Appendix A ............................................. 183
Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
Subject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
Chapter 1
Decision Making and
Uncertainty in the Exploration
and Production Industry
1.1 Introduction
This book is about how to make good decisions, specifi cally within the upstream oil
and gas industry but also more generally for any kind of decision.
Informally, decision making can be defi ned as “choosing the alternative that best fi ts
a set of goals.” Easy? This apparently simple statement raises many questions such as:
What, and whose, are the “goals”? Have I missed good alternatives? How do I measure
“fi t”? How do I defi ne “best”? This book describes a series of tools and processes that
will enable you to answer these questions for many decisions.
Good decision making is not a natural ability, “wired-in” following some evolution-
ary design (Hastie and Dawes 2001). Choosing wisely is a skill, which, like any other
skill, can be improved through learning and practice. Whether at work or at home, if
you apply the principles in this book, you will improve your decision-making skills
and thereby your chances of getting good outcomes. Table 1.1 provides an indication
of the sorts of decisions, large and small, broad and narrow, to which these principles
apply.
We will address the many factors required to make good decisions and will empha-
size the role of uncertainty, showing how its appropriate consideration can lead to
different decisions from those we would make if we ignored it. In particular, we seek
to put to rest the fallacies that “we must have a single number to actually make a deci-
sion” and “one cannot make a decision when presented with a range of possible out-
comes and their probabilities.” Indeed, we show that one can make better decisions
using this information. Moreover, the decisions are often more quickly and easily
reached, and the decision maker will move on to their implementation with greater
confi dence in having made the right ones. Dealing with uncertainty is, therefore, an
integral part of evaluating a decision. It should not be merely a bit of risk/uncertainty/
sensitivity analysis tacked onto the end of a study after the main courses of action
(decisions) have been chosen.
2 Making Good Decisions
TABLE 1.1—EXAMPLES OF THE TYPES OF DECISIONS TO WHICH THE PRINCIPLES
IN THIS BOOK CAN BE APPLIED

Work Personal
Fund a research program Buy a house/car/TV
Choose seismic interpretation software Accept a job offer
Acquire exploration acreage Embark upon a career
Partner on a project or go it alone Attend a course
Hire a new engineer or drilling contractor Select a holiday destination
Drill an extra appraisal well Purchase stock in a company
Do a reservoir simulation study Choose a school for the kids
Construct a larger platform with room for extra Undertake surgery
wells to capture OOIP upside potential Choose a partner
Acquire information to reduce uncertainty or
build flexibility to manage its impacts
Choose best field development concept
Choose an infill well location
Choose a new type of flow meter
Decide when and how to abandon
Determine strategy for the organization
1.2 Decisions in the Exploration and Production (E&P) Industry
Life is the art of drawing suffi cient conclusions from insuffi cient premises.
—Samuel Butler (Russo and Schoemaker 2002)
The E&P industry is about exploring, appraising, and producing oil and gas. The E&P
life cycle goes from early basin assessment and exploration through appraisal, devel-
opment, production—and, fi nally, abandonment. Before, during, and after each phase
are a number of decision points that require the commitment of company time and
resources. These commitments can range from minor (i.e., a few days of work, or the
expenditure of a few thousand dollars) to enormous (i.e., thousands of people working
on a billion-dollar investment over many years).
Good performance does not necessarily indicate good decision making and uncer-
tainty management. The pertinent question is, “How does performance compare to
what it could have been?” There are times when the effects of poor decision making
and uncertainty management are largely obscured as a result of high oil and gas prices.
Times of lower prices are more revealing. Many of the E&P investments made in the
1980s and 1990s would have resulted in major losses if commodity prices stayed at the
USD 10–12 level of 1999 and the early 2000s. In the period 2005 through mid-2008,
there was a tremendous upswing in commodity prices, resulting in most of these proj-
ects delivering profi ts that were signifi cantly better than anyone imagined when the
investment decisions were made. Having no reason to suspect that the quality of deci-
sion making suddenly improved at the same time oil prices rose, we conclude that the
industry continues to underperform. As Ed Merrow of Independent Project Analysis
observes (2010): “Although many companies used corporate planning prices in the