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Arabian Journal of Geosciences

, 12:580 | Cite as

Lithological identification with probabilistic distribution by the modified compositional Kriging

  • Feilong Han
  • Hongbing Zhang
  • Qiang Guo
  • Jianwen Rui
  • Qiuyan Ji
Original Paper
  • 17 Downloads

Abstract

Lithological distribution, as a direct geological reflection, has been widely used in petroleum and geological projects. It is a challenging task to obtain a probabilistic map of lithology by compositional Kriging (CK) with limited logging core data. The predictions are usually affected by local high or low values, resulting in discontinuous boundaries and abnormal data fluctuation. To address the problem of local instability, we proposed the modified compositional Kriging (MCK) with a regulating factor, for adjusting the influence of core data to increase the accuracy and continuity of lithological probabilistic map. To obtain a reasonable result, we determined the hyper-parameter in the regulating factor’s function and a kind of seismic attribute highly correlated with logging data. The examples and the cross validation showed the effectiveness of Kriging method, and then proved the outstanding achievement of MCK through the comparison of field data’s predictions. After direct demonstration, we extracted the correlation coefficients and the regulating factor in our method to reveal more details inside the calculation. The correlation coefficients showed the variation of logging’s influence and illustrated the phenomenon that lacking of loggings can lead to deviations in the probability map. The regulating factor’s distribution showed the extra effect of MCK to increase the stability by its controlling effect. Hence, the proposed MCK method can provide a stable distribution of lithology when a suitable regulating factor has been chosen. This method is an effective tool for estimating lithological probabilistic map with limited wells.

Keywords

Lithology Identification Compositional Kriging Geostatistical modelling Classification 

Notes

Acknowledgements

The authors gratefully appreciate the two anonymous revivers for offering valuable comments that led to great improvements in this paper

Funding information

The authors would like to acknowledge the considerable support by the Fundamental Research Funds for the Central Universities (2018B696X14), Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX18_0623), and the general projects of the National Natural Science Foundation of China (Nos. 41374116 and 41674113).

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Copyright information

© Saudi Society for Geosciences 2019

Authors and Affiliations

  1. 1.College of Earth Science and EngineeringHohai UniversityNanjingPeople’s Republic of China
  2. 2.NanjingPeople’s Republic of China

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