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Multiple-point geostatistics DUP_1 = stochastic modeling with training images /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Multiple-point geostatistics DUP_1/ Gregoire Mariethoz, Jef Caers.
其他題名:	stochastic modeling with training images /
作者:	Mariethoz, Gregoire.
其他作者:	Caers, Jef.
出版者:	Chichester, West Sussex ;John Wiley & Sons, Ltd, : 2015.,
面頁冊數:	1 online resource (xi, 364 p.) :ill. (some col.) :
標題:	Geology - Statistical methods. -
電子資源:	http://onlinelibrary.wiley.com/book/10.1002/9781118662953
ISBN:	9781118662946 (electronic bk.)

Multiple-point geostatistics DUP_1 = stochastic modeling with training images /
Mariethoz, Gregoire.

Multiple-point geostatistics DUP_1stochastic 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:

676684
Geology
--Statistical methods.

LC Class. No.: QE33.2.S82 / M37 2015

Dewey Class. No.: 551.01/5195

Multiple-point geostatistics DUP_1 = stochastic modeling with training images /
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245 1 0 $a Multiple-point geostatistics DUP_1 $h [electronic resource] : $b stochastic modeling with training images / $c Gregoire Mariethoz, Jef Caers.
260 $a Chichester, West Sussex ; $a Hoboken, NJ : $b John Wiley & Sons, Ltd, $c 2015.
300 $a 1 online resource (xi, 364 p.) : $b ill. (some col.)
504 $a Includes bibliographical references and index.
520 $a "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"-- $c Provided by publisher.
520 $a "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"-- $c Provided by publisher.
588 0 $a Online resource; title from digital title page (viewed on November 12, 2014).
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