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• W4294860135 abstract "For tight sandstone reservoirs, permeability is an important parameter to evaluate the physical property and seepage characteristics of the reservoir, and it is also the key to tapping the potential of reservoir productivity and improving oil recovery. Tight sandstone reservoirs have diverse pore types, complex pore structure, strong heterogeneity, and complex changes in the porosity-permeability relationship, which is not a simple linear relationship. The prediction of permeability of tight sandstone reservoir has become an important and arduous task because of the low prediction accuracy of statistical regression of porosity and permeability and logging interpretation methods. Based on the pore structure as the main control factors of the permeability of tight sandstone reservoir, and combining with capillary pressure (MICP), nuclear magnetic resonance (NMR), core physical experiments and logging data, permeability prediction methods on the basis of the theory of statistical regression, the reservoir classification theory of FZI, the theory of fractal geometry theory and the theory of artificial intelligence are reviewed. Finally, it is pointed out that based on MICP, NMR and conventional logging, the combination of fluid flow unit division (FZI) reservoir classification technology, fractal geometry digital core technology and machine learning technology can form an effective method for the evaluation and prediction of the permeability of tight sandstone reservoir with petrophysical significance." @default.
• W4294860135 created "2022-09-07" @default.
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• W4294860135 date "2022-01-01" @default.
• W4294860135 modified "2023-09-27" @default.
• W4294860135 title "A Review of Permeability Prediction Techniques for Tight Sandstone Reservoirs" @default.
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• W4294860135 doi "https://doi.org/10.1007/978-981-19-2149-0_258" @default.
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