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Multiple-point geostatistics[electro...
~
Caers, Jef.
Multiple-point geostatistics[electronic resource] :stochastic modeling with training images /
纪录类型:
书目-语言数据,印刷品 : Monograph/item
[NT 15000414] null:
551.01/5195
[NT 47271] Title/Author:
Multiple-point geostatistics : stochastic modeling with training images // Gregoire Mariethoz, Jef Caers.
作者:
Mariethoz, Gregoire.
[NT 51406] other author:
Caers, Jef.
出版者:
Chichester, West Sussex ; : John Wiley & Sons, Ltd,, 2015.
面页册数:
1 online resource (xi, 364 p.) : : ill. (some col.)
标题:
Geology - Statistical methods.
标题:
Geological modeling.
ISBN:
9781118662946 (electronic bk.)
ISBN:
1118662946 (electronic bk.)
ISBN:
9781118662953 (electronic bk.)
ISBN:
1118662954 (electronic bk.)
[NT 15000227] null:
Includes bibliographical references and index.
[NT 15000229] null:
"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"--
电子资源:
http://onlinelibrary.wiley.com/book/10.1002/9781118662953
Multiple-point geostatistics[electronic resource] :stochastic modeling with training images /
Mariethoz, Gregoire.
Multiple-point geostatistics
stochastic modeling with training images /[electronic resource] :Gregoire Mariethoz, Jef Caers. - Chichester, West Sussex ;John Wiley & Sons, Ltd,2015. - 1 online resource (xi, 364 p.) :ill. (some col.)
Includes bibliographical references and index.
"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"--
ISBN: 9781118662946 (electronic bk.)
LCCN: 2014036103Subjects--Topical Terms:
613988
Geology
--Statistical methods.
LC Class. No.: QE33.2.S82 / M37 2015
Dewey Class. No.: 551.01/5195
Multiple-point geostatistics[electronic resource] :stochastic modeling with training images /
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stochastic modeling with training images /
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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"--
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"The topic of this book concerns an area of geostatistics that has commonly been known as multiple-point geostatistics because it uses more than two-point statistics (correlation), traditionally represented by the variogram, to model spatial phenomena"--
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http://onlinelibrary.wiley.com/book/10.1002/9781118662953
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