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Book synopsis

This book deals with the estimation of natural resources using the Monte Carlo methodology. It includes a set of tools to describe the morphological, statistical and stereological properties of spatial random models. Furthermore, the author presents a wide range of spatial models, including random sets and functions, point processes and object populations applicable to the geosciences. The text is based on a series of courses given in the USA and Latin America to civil, mining and petroleum engineers as well as graduate students in statistics. It is the first book to discuss the geostatistical simulation techniques in such a specific way.Within the geoscience community the estimation of natural resources is a challenging topic. The difficulties are threefold: Intitially, the design of appropriate models to take account of the complexity of the variables of interest and their interactions. This book discusses a wide range of spatial models, including random sets and functions, point processes and object populations. Secondly,the construction of algorithms which reproduce the variability inherent in the models. Finally, the conditioning of the simulations for the data, which can considerably reduce their variability. Besides the classical algorithm for gaussian random functions, specific algorithms based on markovian iterations are presented for conditioning a wide range of spatial models (boolean model, Voronoi tesselation, substitution random function etc.) This volume is the result of a series of courses given in the USA and Latin America to civil, mining and petroleum engineers, as well as to gradute students is statistics. It is the first book to discuss geostatistical simulation techniques in such a systematic way.

Book details

Book category Books in English Mathematics & science Physics Applied physics

• Full title: Geostatistical Simulation
• Subtitle: Models and Algorithms
• Author: Christian Lantuejoul
• Language: English
• Binding: Paperback
• Number of pages: 256
• EAN: 9783642075827
• ISBN: 3642075827
• ID: 01652701
• Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
• Weight: 486 g
• Dimensions: 235 × 155 × 19 mm
• Date of publishing: 30. November 2010

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