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Rothamsted Repository DownloadA - Papers appearing in refereed journals

Lark, R. M. 2011. Statistical methods for estimating petroleum resources.

Journal of the Royal Statistical Society, Series A (Statistics in Society).

174, pp. 513-513.

The publisher's version can be accessed at:

• https://dx.doi.org/10.1111/j.1467-985X.2010.00681_13.x

The output can be accessed at: https://repository.rothamsted.ac.uk/item/8w847.

© Wiley.

08/04/2019 13:32 repository.rothamsted.ac.uk library@rothamsted.ac.uk

Book Reviews 513

auto-regressive time dependence. Autologistic andlatent variable specifications are also described,and the final section has some appealing spatialimplementations of compartmental models of infec-tion dynamics.

The book has relatively few errors: mostly minortypographical mistakes. It was sometimes frustrat-ingly difficult to cross-reference the relevant appen-dix code from the main text. Overall, though, Irecommend the book. It taught me new ideas andclarified existing ones. I shall continue to use it andI expect it to be useful for other statisticians with aninterest in spatial analysis.

Neal AlexanderLondon School of Hygiene and Tropical Medicine

E-mail: neal.alexander@lshtm.ac.uk

Statistical Methods for Estimating PetroleumResourcesP.-J. Lee, 2008Oxford, Oxford University Pressxxii + 234 pp., $125.00ISBN 978-0-195-33190-5

Given the importance of petroleum resources it isnot surprising that their extraction has deployed sig-nificant statistical effort. This ranges from the pre-diction of global and national peak oil productionto geostatistical characterization of single reservoirs.This book is concerned with the analysis of existingdata on the sizes of known single reservoirs within agiven region to estimate that region’s total resourcepotential. The book is primarily concerned withthe suite of methods for resource estimation thatcomprises the late P.-J. Lee’s PETRIMES software.

Chapter 2 introduces basic concepts, chiefly theplay. A play is a set of petroleum deposits or poolswhich can be treated as a single population becausethey were deposited under comparable geologicalconditions. The novice reader must work hard toextract this definition, but it is critical to what fol-lows because the methods in PETRIMES are gearedto characterizing single plays. Quantities such asthe sizes of individual pools within a play, or thenumber of pools, are treated as random variables.The data that are available for a play are the sizesof the individual pools so far discovered, and theorder in which they were discovered. It is assumedthat these data arise from non-random samplingaccording to a discovery process model such that,for example, the larger pools are expected to bediscovered earlier in the sequence. Two approachesare taken to the estimation of the volume of un-discovered resources. In the first the play under in-

vestigation is regarded as a sample drawn from asuperpopulation. This is what PETRIMES does.Alternatively the pools in the play can be treatedas a finite population without proposing an under-lying model.

Chapter 3 delves into the methods in greaterdetail, focusing on mature plays, i.e. plays in whichsufficient pools have been discovered to providedata for the application of discovery process mod-els. The estimation of superpopulation models forpool size and, from these, directly useful estimatesof the total resources of the play are described.Chapter 4 explores a wider range of models, andChapter 5 outlines approaches that are used forunexplored or partially explored plays. Chapter 6sets the methodology in the context of the overallprocess of assessing the resources of a region; thenChapter 7 reviews approaches outside the scope ofPETRIMES.

The statistical reader will complain about someof the terminology and notation, but I found theintimate mix of statistics with geology intriguing.For statisticians who are involved with this, or anal-ogous problems in resource estimation, it will beinvaluable.

© Rothamsted Research Ltd

R. M. LarkRothamsted Research

HarpendenE-mail: murray.lark@bbsrc.ac.uk

Introduction to Spatial EconometricsJ. LeSage and R. K. Pace, 2009Boca Raton, CRC Pressxiv + 354 pp., $89.95ISBN 978-1-420-06424-7

Since the seminal and influential book of Anselin(1988) there has not been a comprehensive treat-ment of spatial econometric models. Without anydoubt, the book by LeSage and Pace is a welcomeaddition to the spatial econometrics literature andwill surely be a compulsory reference in this field.Although some good books on spatial statisticshave come up in recent years, none of them isas specific as this one. An interesting but muchshorter contribution by the same authors appearedin the updated Handbook of Spatial Statistics, aninteresting reference edited by Gelfand et al. (2010).

The text is structured in 10 chapters. The intro-ductory chapter deals with a brief treatment ofspatial dependence and spatial auto-regressiveprocesses, including a discussion of the spatialweight matrices that play an important role in