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Prestack Porosity Direct Inversion Based on Logging Constraints

  • Hai-tao Yan,
  • Huai-lai Zhou,
  • Nan-ke Wu,
  • Yuan-jun Wang,
  • Wei Zhou

摘要

The accurate calculation of formation porosity parameters is a key technology for reservoir prediction, reservoir description, reserve estimation and comprehensive study of oil and gas reservoirs in oil and gas exploration. Based on the basic theory of rock physics and rock physics test data, and under reasonable assumptions, based on Gassmann equation and Eshelby-Walsh equation, a mathematical model for directly calculating the porosity of formation rock using high signal-to-noise ratio seismic data and pre-stack high-precision elastic parameter inversion is derived and established. Through the generalized linear inversion theory, the reservoir porosity is directly inverted based on the accurate Zoeppritz equation and combined with the logging data constraint. Compared with the traditional porosity calculation method, this algorithm can directly invert the porosity by directly inputting the seismic trace collection and logging data, optimize the flow of calculating the porosity by the velocity and density of P-wave and S-wave, reduce the cumulative error in the calculation process, and at the same time, due to the accuracy of the accurate Zoeppritz equation, The results obtained by direct inversion of accurate Zoeppritz equation have higher resolution and accuracy than the porosity results obtained by three-parameter transformation. The application of actual data shows that the porosity results obtained by direct inversion of prestack elastic parameters based on logging constraints are more accurate, with higher resolution, and consistent with logging curves. The prestack elastic parameter inversion theory of the accurate Zoeppritz equation and the rock physics theory are combined to derive and establish the objective function of the direct inversion of porosity. The high-precision porosity results obtained by this algorithm have certain guiding significance for reservoir prediction, well location deployment and fracturing production.