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Titlebook: Geostatistics Oslo 2012; Petter Abrahamsen,Ragnar Hauge,Odd Kolbjørnsen Book 2012 Springer Science+Business Media Dordrecht 2012 Geostatis

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书目名称Geostatistics Oslo 2012
编辑Petter Abrahamsen,Ragnar Hauge,Odd Kolbjørnsen
视频video
概述Collection of state-of-the-art scientific work within Geostatistics.Contains new and innovative ideas in theoretical developments of Geostatistics.A broad selection of novel geostatistical methods app
丛书名称Quantitative Geology and Geostatistics
图书封面Titlebook: Geostatistics Oslo 2012;  Petter Abrahamsen,Ragnar Hauge,Odd Kolbjørnsen Book 2012 Springer Science+Business Media Dordrecht 2012 Geostatis
描述.This book consists of 44 technical papers presented at the Ninth International Geostatistics Congress held in Oslo, Norway in June 2012. The papers have been reviewed by a panel of specialists in Geostatistics. The book is divided into four main sections: Theory; Petroleum; Mining; and Environment, Climate and Hydrology. The first section focuses on new ideas of general interest to many fields of applications. The next sections are more focused on the particular needs of the particular industry or activity.   .Geostatistics is vital to any industry dependent on natural resources. Methods from geostatistics are used for estimating reserves, quantifying economical risk and planning of future industrial operations. Geostatistics is also an important tool for mapping environmental hazard and integrating climate data..
出版日期Book 2012
关键词Geostatistics; Geostatistics 2012; Kriging; Oslo 2012; Random Fields; Spatial Statistics
版次1
doihttps://doi.org/10.1007/978-94-007-4153-9
isbn_softcover978-94-007-9596-9
isbn_ebook978-94-007-4153-9Series ISSN 0924-1973 Series E-ISSN 2215-1834
issn_series 0924-1973
copyrightSpringer Science+Business Media Dordrecht 2012
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Event-Based Geostatistical Modeling: Description and Applicationsa continuum of rule complexity from very simple geometric models to complicated dynamics. Even the application of simple rules, including few conceptual interactions based on an understanding of stratigraphic relationships and parametric geometries for event scale depositional and erosion features,
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Revisiting the Linear Model of Coregionalizationriables as linear combinations of sets of independent (or at least uncorrelated) underlying variables. The popularity of the LCM stems mostly from the ease of modeling and verification of the admissibility of the model. However, LCM has strong limitations as it implies symmetrical cross-covariances
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Modeling Nonlinear Beta Probability Fields are not classic p-fields. Instead, the shape of the local probability density function (pdf) for the proportion .(.) random variable at each location . changes with the Beta distribution parameters, . and . which are in turn functions of the local proportions themselves. In addition, Beta random va
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Multiple-Point Geostatistical Simulation Based on Genetic Algorithms Implemented in a Shared-Memory a training image. The most widely used algorithm is based on solving a single normal equation at each location using the conditional probabilities inferred during the training process. Simulated annealing offers an alternative implementation that, in addition, allows to incorporate additional stati
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The Edge Effect in Geostatistical Simulationsave significant effects on simulations, especially for situations in which the variogram range is relatively large compared to the size of the simulation area (volume). Failure to account properly for the issue can bias simulations by generating values with ranges of correlation and statistical char
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