Multiple-point geostatistics : stochastic modeling with training images

著者

    • Mariethoz, Gregoire
    • Caers, Jef

書誌事項

Multiple-point geostatistics : stochastic modeling with training images

Gregoire Mariethoz, Jef Caers

Wiley Blackwell, 2015

  • : hardback

大学図書館所蔵 件 / 全3件

この図書・雑誌をさがす

注記

Includes bibliographical references and index

内容説明・目次

内容説明

This 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.

目次

Preface, vii Acknowledgments, xi Part I Concepts I.1 Hiking in the Sierra Nevada, 3 I.2 Spatial estimation based on random function theory, 7 I.3 Universal kriging with training images, 29 I.4 Stochastic simulations based on random function theory, 49 I.5 Stochastic simulation without random function theory, 59 I.6 Returning to the Sierra Nevada, 75 Part II Methods II.1 Introduction, 87 II.2 The algorithmic building blocks, 91 II.3 Multiple-point geostatistics algorithms, 155 II.4 Markov random fields, 173 II.5 Nonstationary modeling with training images, 183 II.6 Multivariate modeling with training images, 199 II.7 Training image construction, 221 II.8 Validation and quality control, 239 II.9 Inverse modeling with training images, 259 II.10 Parallelization, 295 Part III Applications III.1 Reservoir forecasting - the West Coast of Africa (WCA) reservoir, 303 III.2 Geological resources modeling in mining, 329 Coauthored by Cristian Perez, Julian M. Ortiz, & Alexandre Boucher III.3 Climate modeling application - the case of the Murray-Darling Basin, 345 Index, 361

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