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Geostatistics: Modeling Spatial Uncertainty by Jean-Paul Chiles — book cover

Geostatistics: Modeling Spatial Uncertainty

by Jean-Paul Chiles
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Overview

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:

  • New results and methods, including kriging very large datasets; kriging with outliers; nonseparable space-time covariances; multipoint simulations; pluri-gaussian simulations; gradual deformation; and extreme value geostatistics
  • Newly formed connections between geostatistics and other approaches such as radial basis functions, Gaussian Markov random fields, and data assimilation
  • 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.

About the Author, Jean-Paul Chiles

Jean-Paul Chilès is Deputy Director of the Center of Geosciences and Geoengißfineering at MINES ParisTech, France.

Pierre Delfiner is Principal of PetroDecisions, a consulting firm based in Paris, France.

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Editorials

From the Publisher

“Summarizing, Chile’s and Delfiner’s book certainly deserves recommendation to anyone interested in geostatistics, either as a geostatician or as a researcher in modeling spatial uncertainty.” (Computers & Geosciences, 1 February 2013)

Journal of Geodsy

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.

Booknews

Deals with statistical models used to describe natural variables distributed in space or in time and space, integrating statistical data with physical equations and geological concepts while stressing the importance of an objective description based on empirical evidence. This 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 situations involving spatial uncertainty. Of interest to geostatisticians, physicists, mining engineers, and earth science professionals. Annotation c. by Book News, Inc., Portland, Or.

Book Details

Published
April 3, 2012
Publisher
Wiley, John & Sons, Incorporated
Pages
734
Format
Hardcover
ISBN
9780470183151

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