The paper presents the results of in-situ stress inversion for a certain hydrocarbon field. Data on natural fractures conductivity are used to evaluate directions of principal stresses, their relative magnitudes, and friction properties of studied rock. In-situ stresses are estimated using Monte-Carlo simulations method. Stress inversion results are in agreement with independent estimations of stress for the studied object. Mathematical statistics is applied to quantitatively evaluate uncertainties in stress inversion results. Pearson frequency distributions and metalog quantile distributions are applied to stress inversion results in order to deal with in-situ stresses in terms of probability functions. Specific questions of dealing with Monte-Carlo simulations for stress inversion from natural fractures analysis are discussed. The proposed approach can be consequently implemented in other stress inversion techniques to provide a solid basis for quantitative uncertainty analysis for various problems of oil and gas reservoir geomechanics.

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Some Statistical Issues of Inverse Problem for Stress Inversion from Data on Natural Shear Fractures Conductivity

  • N. V. Dubinya,
  • E. R. Ziganshin,
  • E. V. Novikova

摘要

The paper presents the results of in-situ stress inversion for a certain hydrocarbon field. Data on natural fractures conductivity are used to evaluate directions of principal stresses, their relative magnitudes, and friction properties of studied rock. In-situ stresses are estimated using Monte-Carlo simulations method. Stress inversion results are in agreement with independent estimations of stress for the studied object. Mathematical statistics is applied to quantitatively evaluate uncertainties in stress inversion results. Pearson frequency distributions and metalog quantile distributions are applied to stress inversion results in order to deal with in-situ stresses in terms of probability functions. Specific questions of dealing with Monte-Carlo simulations for stress inversion from natural fractures analysis are discussed. The proposed approach can be consequently implemented in other stress inversion techniques to provide a solid basis for quantitative uncertainty analysis for various problems of oil and gas reservoir geomechanics.