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This is a major rework of Paul Newendorp's 1975 best-seller, which became the standard reference in the field. This book is now structured as a handbook of over 330 important concepts in risk and economic decision analysis. As the title suggests, well over half the examples apply to petroleum exploration investment decisions. Perhaps 80% of the topics are generally applicable to capital investment, project management, and operations decisions.
Topics in the book represent a composite of evaluation practices and problem-solving approaches now commonly used in oil & gas and other capital-intensive industries. Several important and practical techniques were first published in the first edition.
Decision analysis methods apply to any type of decision. The emphasis here is on quantitative methods useful in capital investment decisions and decisions to acquire additional information. This will be of special interest to anyone involved in the evaluation of property acquisitions, geophysical surveys, prospect drilling, and field development decisions. This book is intended for petroleum geologists, engineers, geophysicists, evaluation and planning analysts, and managers. This is not a first book in decision analysis. We presume the reader has a general familiarity with management, economics, decision analysis, and knowledge of the oil & gas industry.
As a handbook we are focusing on what is most important and practical. Major topic area include the decision analysis process, key concepts in probability and statistics (including Bayes' rule and easy equivalents), decision policy (including risk policy expressed as a utility function), popular economic metrics and concepts, project and enterprise modeling, decision tree analysis, Monte Carlo simulation, and various special topics. Value of information problems receive special attention. Over 270 figures help illustrate the concepts.
The expected value (EV) concept is central throughout. Most often we assume a decision policy that maximizes EV. Most of the discussion presumes a business context and measuring outcome as net present value (NPV). We also describe approaches for multi-criteria decision making including HSE.
Expected monetary value (EMV = EV NPV) is the principal decision criterion used in most examples. The EV calculation incorporates judgments about risks and uncertainties expressed as probabilities and probability distributions. EV is the cornerstone of formal, quantitative analysis for decisions under uncertainty. The key calculation methods are decision trees and Monte Carlo simulation. Small decision trees can be solved with a hand calculator, while larger trees and Monte Carlo simulation usually require a computer. Software supporting these methods is now widely available as Microsoft® Excel® spreadsheet add-ins and for other platforms.
The material is organized into seven sections: Decision Analysis Process, Probability and Statistics, Decision Policy, Economic Matters, Modeling, Decision Tree Analysis, and Monte Carlo Simulation. Throughout, real-world exploration examples are presented to illustrate the risk and decision analysis methods.
This revised 3.0 edition features a larger page format, an updated and expanded bibliography, and an extensive glossary. We also offer additional material online, including extended discussions, software resources, and example Excel spreadsheets.
- Sales Rank: #164523 in Books
- Published on: 2013-08-12
- Original language: English
- Number of items: 1
- Dimensions: 11.00" h x 1.33" w x 8.50" l, 2.95 pounds
- Binding: Paperback
- 588 pages
About the Author
Dr. Paul Newendorp began his career in 1959 as a petroleum engineer. He later earned MS and PhD in Petroleum Engineering from U. of Oklahoma. In 1968, he developed a two-week short course on petroleum exploration economics and risk analysis. The course was based, in part, on his doctoral research on decision theory and earlier industry work experience. During his 21 years of teaching, Paul was active in developing and promoting use of decision theory methods applied to exploration investments. He pioneered many ideas, particularly with Monte Carlo simulation, that are now standard practice. Paul served in various SPE leadership roles and received numerous awards.
John Schuyler has over 39 years of business experience in training, consulting, analysis, and management. His industry experience has been mostly in the petroleum industry, and also includes finance, mining, manufacturing, pharmaceuticals, and government.
John’s short courses deal with portfolio management, capital investments, project design, and under decisions under uncertainty. He has presented over 300 industry courses for over 24 years, mostly in association with PetroSkills, LLC.
His previous work experience includes VP and petroleum evaluation engineer for Security Pacific Bank; Manager-Business Systems for Cities Service Co.'s Petrochemicals Division; Senior Management Consultant with a national accounting firm; Planning and Evaluation Analyst for Cities Service Oil Company; and VP - Administration, CFO, and co-founder of a small commercial products company.
He holds an M.B.A. from U. of Colorado and B.S. and M.S. degrees in Mineral-Engineering Physics from Colorado School of Mines. He has earned the following: CAM, CCP, CMA, CMC, CPIM, DRMP, PMP, and PE (Colorado). He is a member of AACE, IMA, IMC, INFORMS, PMI, RMAG, SPE and SPEE.
John written over 40 conference papers, articles and handbook chapters published in the professional literature. In addition to revising this book, he has written Risk and Decision Analysis in Projects, Second Edition (2001, Project Management Institute).
Most helpful customer reviews
3 of 3 people found the following review helpful.
Excellent reference for decision and risk analysis for major projects
By John K. Hollmann
Decision and risk analysis for major capital projects can be daunting. There is so much to understand in terms of statistics, models, bias, finance and economics, software tools and so on. If you think it would be great to have a reference book that was a kind of printed Wikipedia or Cliff’s Notes for these topics with lots of short, spot-on descriptions, discussions, examples and tips, then this book will make your day, as it did mine. My copy is already loaded with stickies.
The book is built around the expected value concept of decision analysis in consideration of uncertainty. While the book’s examples are for exploration and production, the majority of the text is generic to any major process industry project; the decision analysis process and tools are the same. It will likely be of most value to those with experience in quantitative decision analysis; however, it does provide a “getting started” guide that walks the beginner through the basis topics starting with the decision analysis process.
I am not the strongest on probability and statistics and found this book to be a great review of what one needs to know in these areas for analysis and modeling. It also includes lots or rules of thumb waiting for your sticky notes. There is good coverage of modeling, decision trees, and simulation; i.e., the basic analysis toolkit. But it also has good coverage of the process, decision policy and engineering economics (context). While it focuses on business and monetary analysis, it also covers non-monetary considerations and multi-criteria decision making including HSE. It also does not skip on the human side of decision making; i.e., bias. It’s a very balanced treatment.
Some other features include extensive description of software available for various aspects of decision analysis, an extensive bibliography and glossary, and a detailed index to help you find things. It also provides access codes to get supplementary materials in the author’s company website (the “tips” there are also great reading!). For those interested in AACE International’s Decision and Risk Management Professional (DRMP) certification, which has a similar quantitative focus, this text will be an excellent study reference for the decision management, eng econ, and probability and stats parts of the exam.
In summary, it hits the target as a great handbook that those practicing in or supporting decision analysis on major process industry projects will want to have handy.
0 of 1 people found the following review helpful.
Four Stars
By surbro wang
nice quality and something new
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