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Computational Geosciences

, Volume 12, Issue 4, pp 573–591 | Cite as

Estimation or simulation? That is the question

  • Jorge Kazuo Yamamoto
Original paper

Abstract

The issue of smoothing in kriging has been addressed either by estimation or simulation. The solution via estimation calls for postprocessing kriging estimates in order to correct the smoothing effect. Stochastic simulation provides equiprobable images presenting no smoothing and reproducing the covariance model. Consequently, these images reproduce both the sample histogram and the sample semivariogram. However, there is still a problem, which is the lack of local accuracy of simulated images. In this paper, a postprocessing algorithm for correcting the smoothing effect of ordinary kriging estimates is compared with sequential Gaussian simulation realizations. Based on samples drawn from exhaustive data sets, the postprocessing algorithm is shown to be superior to any individual simulation realization yet, at the expense of providing one deterministic estimate of the random function.

Keywords

Ordinary kriging Smoothing effect Stochastic simulation Sequential Gaussian simulation 

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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.Department of Environmental and Sedimentary Geology, Institute of GeosciencesUniversity of Sao PauloSao PauloBrazil

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