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Book Chapter

Modeling the Semivariogram: New Approach, Methods Comparison, and Simulation Study

By
A. Gribov
A. Gribov
Environmental Systems Research Institute Redlands, California, U.S.A.
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K. Krivoruchko
K. Krivoruchko
Environmental Systems Research Institute Redlands, California, U.S.A.
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J. M. Ver Hoef
J. M. Ver Hoef
Alaska Department of Fish and Game Fairbanks, Alaska, U.S.A.
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Published:
January 01, 2006

Abstract

This chapter proposes some new methods for computing empirical semivariograms and covariances and for fitting semivariogram and covariance models to empirical data. Grid-based empirical semivariograms and covariances are described, in which the grid values are smoothed using triangular kernels. A model-fitting procedure using modified iterative weighted least squares is presented. This algorithm is shown to be reliable for a wide range of data types and conditions, and its implementation in commercial software is discussed. Comparisons to restricted maximum likelihood estimation are also discussed.

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Contents

AAPG Computer Applications in Geology

Stochastic Modeling and Geostatistics: Principles, Methods, and Case Studies, Volume II

T. C. Coburn
T. C. Coburn
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J. M. Yarus
J. M. Yarus
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R. L. Chambers
R. L. Chambers
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American Association of Petroleum Geologists
Volume
5
ISBN electronic:
9781629810362
Publication date:
January 01, 2006

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