Multiple-point Geostatistics

Stochastic Modeling with Training Images

Professor Gregoire Mariethoz, Jef Caers (Autoren)

Buch | Hardcover

376 Seiten

2014
Wiley-Blackwell (Verlag)
978-1-118-66275-5 (ISBN)

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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.

Gregoire Mariethoz is Professor Assistant at the Faculty of Geosciences and Environment of the University of Lausanne, Switzerland, and Adjunct Senior Lecturer in Water Resources Engineering at the University of New South Wales, Australia. Jef Caers is Professor of Energy Resources Engineering at Stanford University, USA and Director of the Stanford Center for Reservoir Forecasting. His previous book publications include Petroleum Geostatistics (SPE) and Modeling Uncertainty in the Earth Sciences (Wiley-Blackwell).

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 P´erez, Julian M. Ortiz, & Alexandre Boucher

III.3 Climate modeling application – the case of the Murray–Darling

Basin, 345

Index, 361

Erscheint lt. Verlag	12.12.2014
Verlagsort	Hoboken
Sprache	englisch
Maße	178 x 253 mm
Gewicht	943 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
Themenwelt	Naturwissenschaften ► Geowissenschaften ► Geologie
ISBN-10	1-118-66275-X / 111866275X
ISBN-13	978-1-118-66275-5 / 9781118662755
Zustand	Neuware