Seismic inversion method for tight sandstone reservoir properties based on a variable critical porosity model

Chinese Journal of Geophysics(2023)

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摘要
Petrophysical seismic inversion is an important approach to quantitatively evaluate reservoir properties from seismic observation data. Tight sandstone oil/gas reservoirs are widely distributed in West China, which exhibit a great potential for the exploration and production. The prediction of tight sandstone reservoir properties is quite difficult due to the complex pore structures. This work presents a novel seismic inversion method for reservoir properties based on the variable critical porosity model. To effectively describe the complex pore structures in tight sandstone reservoirs, the critical porosity is considered as a variable, which varies spatially to characterize the complex pore structures, by which the accuracy of rock physics modeling of tight sandstones is improved. In addition, for the purpose of directly extracting reservoir properties from the observed seismic data, the forward operator is established by combining rock physics model and seismic reflectivity equation. The relevant inverse problem is proposed based on a Bayesian framework and the Gaussian mixture model is adopted to formulate the prior constraint on the reservoir properties to characterize the lithological/facies variations. According to the statistical relations between critical porosity, clay volume, and total porosity, the critical porosity is alternatively updated along with the reservoir properties during the fast simulated annealing optimization process, to improve the stability of the inversion results. The developed method is tested in a working area of the Sichuan Basin, west China, of which the results demonstrate that the method can be a good indicator for the gas-bearing zones. Compared with the method with the conventional fixed critical porosity model, the new method effectively improves the precision of inversion results.
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关键词
Tight sandstone,Complex pore reservoir,Petrophysical seismic inversion,Critical porosity,Gaussian mixture model,Nonlinear optimization,Bayesian framework
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