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Look Inside Value of Information in the Earth Sciences
eBook forthcoming

Value of Information in the Earth Sciences
Integrating Spatial Modeling and Decision Analysis

$140.00 (C)

  • Date Published: January 2016
  • availability: In stock
  • format: Hardback
  • isbn: 9781107040267

$ 140.00 (C)

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About the Authors
  • Gathering the right kind and the right amount of information is crucial for any decision-making process. This book presents a unified framework for assessing the value of potential data gathering schemes by integrating spatial modelling and decision analysis, with a focus on the Earth sciences. The authors discuss the value of imperfect versus perfect information, and the value of total versus partial information, where only subsets of the data are acquired. Concepts are illustrated using a suite of quantitative tools from decision analysis, such as decision trees and influence diagrams, as well as models for continuous and discrete dependent spatial variables, including Bayesian networks, Markov random fields, Gaussian processes, and multiple-point geostatistics. Unique in scope, this book is of interest to students, researchers and industry professionals in the Earth and environmental sciences, who use applied statistics and decision analysis techniques, and particularly to those working in petroleum, mining, and environmental geoscience.

    • This book is the first to focus on value of information exclusively in the Earth sciences
    • Describes ideas for blending decision analysis and spatial statistics to support information gathering practices
    • Problem sets and projects with associated data and code available online makes this book a valuable resource for classroom teaching and self-learning by hands-on practice
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    Reviews & endorsements

    'The book’s authors have made a mindful attempt at teaching a relatively complicated topic, and one of growing importance, to a non-expert audience composed of geoscientists. … This book is written while keeping researchers, graduate students, and practitioners in earth-science-related industries in mind. Hence, the mathematical rigor is kept at a level that is appropriate for such an audience, without too much emphasis on details. It is a well-organized volume that uses a number of numerical examples to illustrate the applicability of VOI analysis to earth-science problems. Additional data sets and Matlab codes are available as online supplementary material. Hence, it is well suited for self-learning. … I strongly recommend it to anyone using or researching the application of decision analysis techniques like VOI analysis in managing earth resources.' Amit Padhi, The Leading Edge

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    Product details

    • Date Published: January 2016
    • format: Hardback
    • isbn: 9781107040267
    • length: 396 pages
    • dimensions: 253 x 180 x 22 mm
    • weight: 0.92kg
    • contains: 137 b/w illus. 22 tables
    • availability: In stock
  • Table of Contents

    1. Introduction
    2. Statistical models and methods
    3. Decision analysis
    4. Spatial modeling
    5. Value of information in spatial decision situations
    6. Earth sciences applications
    7. Problems and projects
    Appendix. Selected statistical models and sampling methods

  • Resources for

    Value of Information in the Earth Sciences

    Jo Eidsvik, Tapan Mukerji, Debarun Bhattacharjya

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  • Authors

    Jo Eidsvik, Norwegian University of Science and Technology, Trondheim
    Jo Eidsvik is Professor of Statistics at the Norwegian University of Science and Technology (NTNU), Norway, and has previous industry work experience from the Norwegian Defense Research Establishment and Statoil.

    Tapan Mukerji, Stanford University, California
    Tapan Mukerji is Associate Professor (Research) in the Department of Energy Resources Engineering and the Department of Geophysics at Stanford University. He is a co-author of The Rock Physics Handbook and Quantitative Seismic Interpretation.

    Debarun Bhattacharjya, IBM T. J. Watson Research Center, New York
    Debarun Bhattacharjya is Research Staff Member in the Cognitive Computing Research group at the IBM T. J. Watson Research Center, New York. He applies his expertise in decision analysis towards developing algorithms and tools for both research and consulting purposes.

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