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Making Good Decisions is written for petroleum engineers and geoscientists—using industry language and recognizable E&P examples. The authors are well-credentialed and well-known in the petroleum evaluation community.
This book is pleasing to hold. It is nicely typeset with abundant illustrations, printed on quality paper, and well-bound. Among the 207 pages, I counted 71 pages with color figures. It’s well worth the US$70 member price. The book is intended for people who have had at least one statistics course. However, the needed probability and statistics concepts are reasonably well-explained, and a general E&P background seems sufficient.
There is a surprising breadth of information in the book. The book is pleasant though not light reading. The reader is expected to work through numeric examples. Any prior decision analysis background will be useful. Well-chosen quotes, an expanded “two girls” problem, and an optical illusion figure (analogous to perception biases) were especially entertaining.
Chapters 1 and 2 provide an overview of decision making. Their three-phase decision process is sound. Framing the problem receives appropriate emphasis.
Chapters 3-5 cover the central techniques: quantifying uncertainty, Monte Carlo simulation and decision tree analysis. Influence diagrams are presented in several chapters to show decision structuring and value of information concepts. The probability concepts are especially well-presented with playing cards, cell arrays, and Venn diagrams.
Chapter 6 is “Creating Value from Uncertainty.” Value of information (VoI) opportunities exist in most decision situations. Bratvold and Begg couple VoI with value of flexibility (VoF). VoF in the simplest view is routine project risk management. In an expanded view, VoF encompasses VoI and real options thinking. Guidance toward acquiring and interpreting additional information is excellent, especially the use of sensitivity analysis to screen whether further analysis effort may be worthwhile.
Chapter 7, my favorite, is about behavioral challenges. The authors nicely review common biases and judgment elicitation challenges.
There were a few distractions in this first edition.
I feel multi-criteria decision making is overplayed; Instead, they could have talked about using monetary-equivalents for considerations ancillary to NPV.
Surprisingly, the authors revealed a simple equivalent to Bayes’ rule (eqn. 3.1) early on, yet apply a typical textbook Bayes’ formula (more complex) for worked examples.
It would help if the formula variables were replaced with letter symbols matching the problems. I suspect legions of the professors’ students will suggest improvements in an eventual second edition.
The book embeds abundant references throughout, both for attribution and for additional study. The eight-page bibliography includes many recent works. Most chapters end with suggestions for further reading. Several of the works that especially interest me are additional papers by Bratvold and/or Begg and their associates.
I recommend this book for all E&P professionals interested in decision analysis—regardless of background. Reading it was a pleasure, and I found myself looking forward to each concept explanation and the next application example. For me, buying and reading the book was a good decision, and I’m pleased with the learning (good outcome).
—John Schuyler, March 2011.
Copyright © 2011 by John R. Schuyler. All rights reserved. Permission to copy with reproduction of this notice.