Value of Information (VOI) is a concept in decision theory for analyzing the value of obtaining additional information to solve a problem. Gathering the right kind and the right amount of information is crucial for any decision-making process. Already commonly used in medicine, economics, and finance, VOI is becoming increasingly popular with Earth scientists.
This book presents a unified framework for assessing the value of potential data gathering schemes by integrating spatial modeling and decision analysis, with a focus on the Earth sciences. The authors discuss and compare 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 multi-point statistics. Numerous examples illustrate the applicability of VOI to topics such as energy, geophysics, geology, mining, and environmental science. Real datasets and Matlab codes are also provided as online supplementary material here. Unique in its 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.
Matlab files and datasets