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Geostatistics Oslo 2012 [Paperback]

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  • Category: Books (Science)
  • ISBN-10:  9400795963
  • ISBN-10:  9400795963
  • ISBN-13:  9789400795969
  • ISBN-13:  9789400795969
  • Publisher:  Springer
  • Publisher:  Springer
  • Pages:  562
  • Pages:  562
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Feb-2014
  • Pub Date:  01-Feb-2014
  • SKU:  9400795963-11-SPRI
  • SKU:  9400795963-11-SPRI
  • Item ID: 100966910
  • List Price: $169.99
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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.

This volume consists of 44 technical papers presented at the Ninth International Geostatistics Congress held in Oslo, Norway in June 2012. It covers theory, petroleum, mining, and environmental, climate and hydrology.

Foreword

Preface

Acknowledgements

Part I Theory

Sequential Simulation with Iterative Methods ??????????

Applications of Randomized Methods for Decomposing and Simulating from Large Covariance Matrices ???????????????

Event-based Geostatistical Modeling: Description and Applications

A Plurigaussian Model for Simulating Regionalized Compositions

New Flexible Non-parametric Data Transformation for Trans-Gaussian Kriging

Revisiting the Linear Model of Coregionalisation

Modeling Nonlinear Beta Probability Fields

Approximations of High-Order Spatial Statistics through Decomposition

Multiple-Point Geostatistical Simulation BasedlS_