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Geostatistics: Modeling Spatial Uncertainty (Wiley Series in Probability and Statistics), by Jean-Paul Chils, Pierre Delfiner
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Praise for the First Edition
". . . a readable, comprehensive volume that . . . belongs on the desk, close at hand, of any serious researcher or practitioner." —Mathematical Geosciences
The state of the art in geostatistics
Geostatistical models and techniques such as kriging and stochastic multi-realizations exploit spatial correlations to evaluate natural resources, help optimize their development, and address environmental issues related to air and water quality, soil pollution, and forestry. Geostatistics: Modeling Spatial Uncertainty, Second Edition presents a comprehensive, up-to-date reference on the topic, now featuring the latest developments in the field.
The authors explain both the theory and applications of geostatistics through a unified treatment that emphasizes methodology. Key topics that are the foundation of geostatistics are explored in-depth, including stationary and nonstationary models; linear and nonlinear methods; change of support; multivariate approaches; and conditional simulations. The Second Edition highlights the growing number of applications of geostatistical methods and discusses three key areas of growth in the field:
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New results and methods, including kriging very large datasets; kriging with outliers; nonse??parable space-time covariances; multipoint simulations; pluri-gaussian simulations; gradual deformation; and extreme value geostatistics
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Newly formed connections between geostatistics and other approaches such as radial basis functions, Gaussian Markov random fields, and data assimilation
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New perspectives on topics such as collocated cokriging, kriging with an external drift, discrete Gaussian change-of-support models, and simulation algorithms
Geostatistics, Second Edition is an excellent book for courses on the topic at the graduate level. It also serves as an invaluable reference for earth scientists, mining and petroleum engineers, geophysicists, and environmental statisticians who collect and analyze data in their everyday work.
- Sales Rank: #1756547 in eBooks
- Published on: 2012-02-08
- Released on: 2012-02-08
- Format: Kindle eBook
Review
"This is a book that the geostatistical community has been waiting for long since" "I can recommend anyone interested in geostatistics to get the volume...I am convinced that it will be the volume to cite in the next decade or more." (Journal of Geodsy, November 2000)
Reviews the most up-to-date geostatistical methods and the types of problems they address. Emphasizes the statistical methodologies employed in spatial estimation. Presents simulation techniquesand digital models of uncertainty.
"...a readable, comprehensive volume that should be useful for many years. It belongs on the desk, close at hand, of any serious researcher or practitioner." (Mathematical Geology, Vol. 35, No. 3April 2003)
From the Back Cover
A novel, practical approach to modeling spatial uncertainty.
This book deals with statistical models used to describe natural variables distributed in space or in time and space. It takes a practical, unified approach to geostatistics-integrating statistical data with physical equations and geological concepts while stressing the importance of an objective description based on empirical evidence. This unique approach facilitates realistic modeling that accounts for the complexity of natural phenomena and helps solve economic and development problems-in mining, oil exploration, environmental engineering, and other real-world situations involving spatial uncertainty.
Up-to-date, comprehensive, and well-written, Geostatistics: Modeling Spatial Uncertainty explains both theory and applications, covers many useful topics, and offers a wealth of new insights for nonstatisticians and seasoned professionals alike. This volume:
* Reviews the most up-to-date geostatistical methods and the types of problems they address.
* Emphasizes the statistical methodologies employed in spatial estimation.
* Presents simulation techniques and digital models of uncertainty.
* Features more than 150 figures and many concrete examples throughout the text.
* Includes extensive footnoting as well as a thorough bibliography.
Geostatistics: Modeling Spatial Uncertainty is the only geostatistical book to address a broad audience in both industry and academia. An invaluable resource for geostatisticians, physicists, mining engineers, and earth science professionals such as petroleum geologists, geophysicists, and hydrogeologists, it is also an excellent supplementary text for graduate-level courses in related subjects.
About the Author
JEAN-PAUL CHIL�S is a senior research scientist with the Bureau de Recherches G�ologiques et Mini�res (the French Geological Survey) in Orleans, France.
PIERRE DELFINER is a scientific advisor in geosciences with Total Exploration Production in Paris, France.
Most helpful customer reviews
25 of 26 people found the following review helpful.
Highly recommended!
By Tilmann Gneiting
Highly recommended! This is easily the most comprehensive, scholarly, and up-to-date work in the area.
The authors cover the entire range of geostatistics - structural analysis (variogram fitting), kriging, multivariate and nonlinear methods, conditional simulation, scale effects, and inverse problems. The chapter on geostatistical simulation is particularly impressive, and much unpublished work of Georges Matheron and the Center for Geostatistics at Fontainebleau, France, is made available here for the first time. Practical and theoretical aspects of geostatistics balance each other very nicely.
This is not an introductory text - there are other books in the area which are custom-tailored to beginners - but it is an invaluable, and very carefully written, reference. For anyone applying geostatistical techniques in environmental sciences, earth sciences, engineering, or related fields, this book is a must-have!
14 of 15 people found the following review helpful.
the reference book in geostatistics
By rivoirard
There are a large number of books on geostatistics, usually introductory books dealing with parts of the subject. The volume by Chiles and Delfiner is THE comprehensive reference book in geostatistics that has been missing up to now.
It covers every part of geostatistics. After a useful introduction and preliminaries, different chapters are devoted successively to structural analysis, kriging, the intrinsic model of order k, multivariate methods, nonlinear methods, conditional simulations, scale effects and inverse problems.
Within each section, the book offers an accurate perspective of the different geostatistical methods. Practical approaches as well as theoretical developments are jointly considered, providing a sound basis to the user.
The writing is fluent, with an extensive documentation and a most helpful index.
The book will benefit those who want to know more about a specific method, as well as those who are looking for different approaches to a given problem. It will be valuable for academics and students, as well as scientists, engineers and practitioners from different domains such as mining, hydrogeology, oil exploration, soil science, forestry, and environmental sciences.
2 of 2 people found the following review helpful.
Definitive
By John Vann
This is a comprehensive and definitive text on geostatistics. Although the more theoretical sections are marked as optional, be warned that it is not for the feint-hearted. However, the cases are very worthwhile, the coverage and depth is very good and the mathematical rigour is evident. The discussions of applications is good (in my view) and the explanations mostly lucid. In the traditions of the French school, much mathematics is presumed to be evident or obvious, when for us mortals it is actually hard work. But this book rewards the diligent reader. For the professional Geostatistician or serious student it is a mandatory text.
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