Statistics for Petroleum Engineers and Geoscientists

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9780131318557: Statistics for Petroleum Engineers and Geoscientists
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A complete guide to statistics for petroleum industry professionals who develop and use reservoir models for fluid flow. This book will help petroleum professionals develop more accurate models, leading to lower sampling costs. It starts with a detailed description of methods for exploring the statistical and geological relationships of data, including histograms, averages, confidence intervals, and measures of variability. Next, the book presents procedures for producing flow models. Linear regression, Kriging, simulated annealing, and other methods are described. The last chapter covers a variety of geological environments, presenting case studies, and shows how the statistical procedures discussed can be used to develop reliable flow models. This is an ideal book for petroleum engineers, geoscientists, hydrologists, and faculty and students in these and related fields.

From the Back Cover:

Statistics and geology form a powerful partnership. Practicing engineers, geoscientists and hydrologists who are comfortable with both disciplines can understand and model geosystems much more accurately. With both sets of tools at their disposal, professionals can have much greater success in solving difficult interwell property distribution problems—and achieving higher recovery.
This text has two goals: to help practicing professionals and students understand the diagnostic potential of statistics for modeling fluid flow in reservoirs; and to introduce the important features of statistical modeling.
The book first presents extensive coverage of diagnostic topics from the geoscientist's point of view. This coverage includes histograms, averages, and confidence intervals. Topics discussed in detail include:
*Univariate and single-variable distributions

*Measures of heterogeneity and variability

*Estimators, their desirable properties, and potential biases

Once important aspects of geosystem behavior have been detected and quantified, the book presents a variety of modeling methods, notably linear regression, which has surprising utility, even for experienced professionals. Kriging, conditional simulation, analysis of spatial relationships, simulated annealing, and a variety of other methods are also reviewed.
A final chapter presents several field modeling studies, ranging from the highly deterministic to the strongly random, in which the combination of statistical diagnosis and geology was essential to the modeling approach chosen.
Real field and outcrop data sets are used throughout, and the book presents extensive guidance on interpreting statistical results properly, helping the practitioner recognize and avoid misleading results.

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