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Localised kriging parameter optimisation based on absolute error minimisation

Localised kriging parameter optimisation based on absolute error minimisation The definition of the search neighbourhood in kriging can have a significant impact on the resulting estimates. Stationary domains are usually estimated using a unique search strategy for the entire domain. However, the use of a global search neighbourhood ignores the local variations within each domain, i.e. all blocks are interpolated using a unique search strategy. In this paper, localised kriging parameter optimisation (LKPO) is proposed as an alternative methodology that considers the best ‘local estimation parameter settings’ block by block. The optimisation process is based on absolute error minimisation obtained in cross-validation. Two datasets are presented, the first is a synthetic mineral deposit (2D) and the second is a gold deposit (3D). A wide variety of validation checks show that the use of local kriging parameters significantly improves the grade estimation, obtaining more precise and accurate results than the methodologies currently available in the geostatistical literature. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Earth Science Taylor & Francis

Localised kriging parameter optimisation based on absolute error minimisation

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Localised kriging parameter optimisation based on absolute error minimisation

Abstract

The definition of the search neighbourhood in kriging can have a significant impact on the resulting estimates. Stationary domains are usually estimated using a unique search strategy for the entire domain. However, the use of a global search neighbourhood ignores the local variations within each domain, i.e. all blocks are interpolated using a unique search strategy. In this paper, localised kriging parameter optimisation (LKPO) is proposed as an alternative methodology that considers the...
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Publisher
Taylor & Francis
Copyright
© 2018 Institute of Materials, Minerals and Mining and The AusIMM
ISSN
2572-6838
eISSN
2572-6846
DOI
10.1080/25726838.2018.1539536
Publisher site
See Article on Publisher Site

Abstract

The definition of the search neighbourhood in kriging can have a significant impact on the resulting estimates. Stationary domains are usually estimated using a unique search strategy for the entire domain. However, the use of a global search neighbourhood ignores the local variations within each domain, i.e. all blocks are interpolated using a unique search strategy. In this paper, localised kriging parameter optimisation (LKPO) is proposed as an alternative methodology that considers the best ‘local estimation parameter settings’ block by block. The optimisation process is based on absolute error minimisation obtained in cross-validation. Two datasets are presented, the first is a synthetic mineral deposit (2D) and the second is a gold deposit (3D). A wide variety of validation checks show that the use of local kriging parameters significantly improves the grade estimation, obtaining more precise and accurate results than the methodologies currently available in the geostatistical literature.

Journal

Applied Earth Science – Taylor & Francis

Published: Oct 2, 2018

Keywords: Kriging parameters; local optimisation; search neighbourhood

References

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