Value of Information in the Earth Sciences: Integrating Spatial Modeling and Decision Analysis - Tapa dura

'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

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.