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Research on calibrating rock mechanical parameters with a statistical method

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Listed:
  • Zhen Liu
  • Ye Guo
  • Shuheng Du
  • Gengyu Wu
  • Mao Pan

Abstract

Research on the modeling of rock mechanics parameters is of great significance to the exploration of oil and gas. The use of logging data with the Kriging interpolation to study rock mechanics parameters has been proven to be effective in reservoir prediction and other oilfield applications and can provide additional data. However, there will sometimes be a great deviation due to the limited samples and the strong heterogeneity of a layer. To solve this problem, a new approach was proposed to calibrate rock mechanical models through the statistical analysis of logging data. A module was developed to calibrate rock mechanics parameters automatically, which was then applied to the Wangyao area of the Ansai oilfield. This method significantly improved the accuracy of rock mechanics modeling.

Suggested Citation

  • Zhen Liu & Ye Guo & Shuheng Du & Gengyu Wu & Mao Pan, 2017. "Research on calibrating rock mechanical parameters with a statistical method," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-16, May.
    • Handle: RePEc:plo:pone00:0176215
    DOI: 10.1371/journal.pone.0176215
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    References listed on IDEAS

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    1. Roustant, Olivier & Ginsbourger, David & Deville, Yves, 2012. "DiceKriging, DiceOptim: Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 51(i01).
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