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New variogram modeling method using MGGP and SVR

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Abstract

A critical step for kriging in geostatistics is estimation of the variogram. Traditional variogram modeling comprise of the experimental variogram calculation, appropriate variogram model selection and model parameter determination. Selecting of the variogram model and fitting of model parameters is the most controversial aspect of geostatistics. Shapes of valid variogram models are finite, and sometimes, the optimal shape of the model can not be fitted, leading to reduced estimation accuracy. In this paper, a new method is presented to automatically construct a model shape and fit model parameters to experimental variograms using Support Vector Regression (SVR) and Multi-Gene Genetic Programming (MGGP). The proposed method does not require the selection of a variogram model and can directly provide the model shape and parameters of the optimal variogram. The validity of the proposed method is demonstrated in a number of cases.

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Acknowledgments

This study was jointly supported by the Research of High-grade Iron Ore Formation Mechanism and Prediction of China (2012CB416800) and the Fundamental Research Funds for the Graduate Innovation State Education Ministry (N110601002). We are very grateful to Dr Isobel Clark and Dr Pierrre Goovaerts who made geostatistical data available on the internet. We are thankful to three of anonymous reviewers for their constructive comments. We are also very grateful to Earth Science Informatics editor, Dr. Hassan A. Babaie. Their careful review and editorial comments were very useful for the preparation of a revised version.

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Authors and Affiliations

  1. College of Resources & Civil, Northeastern University, Shenyang, China

    Changik Han, Ende Wang & Jianming Xia

  2. College of Geoexploration Engineering, Kimchaek University of Technology, Pyongyang, Democratic People’s Republic of Korea

    Changik Han, GwangSu Li & Sunchol Choe

  3. College of Information Science & Engineering, Northeastern University, Shenyang, China

    Jiyang Wang & Mingguo Zheng

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  1. Changik Han
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Communicated by: H. A. Babaie

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Han, C., Wang, J., Zheng, M. et al. New variogram modeling method using MGGP and SVR. Earth Sci Inform 9, 197–213 (2016). https://doi.org/10.1007/s12145-016-0251-9

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