This website accompanies the book entitled Multiple-point Geostatistics: Stochastic Modeling with Training Images, First Edition, by Gregoire Mariethoz and Jef Caers, © 2014 John Wiley & Sons, Ltd. It can be purchased on the website of Wiley or through other channels such as Amazon or Bookdepository.
On these pages you will find additional resources under the form of a library of training images, links to research codes and updated bibliographic references. These training images are the source files of the examples that we have used in the book, and are available to download and use for testing methods and for benchmarking computer codes.
The book provides a comprehensive introduction to multiple-point geostatistics, where spatial continuity is described using training images. Multiple-point geostatistics aims at bridging the gap between physical modelling/realism and spatio-temporal stochastic modelling. The book provides an overview of this new field in three parts. Part I presents a conceptual comparison between traditional random function theory and stochastic modelling based on training images, where random function theory is not always used. Part II covers in detail various algorithms and methodologies starting from basic building blocks in statistical science and computer science. Concepts such as non-stationary and multi-variate modeling, consistency between data and model, the construction of training images and inverse modelling are treated. Part III covers three example application areas, namely, reservoir modelling, mineral resources modelling and climate model downscaling. This book will be an invaluable reference for students, researchers and practitioners of all areas of the Earth Sciences where forecasting based on spatio-temporal data is performed.