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A Method for Improving Permeability Accuracy of Tight Sandstone Gas Reservoirs Based on Core Data and NMR Logs

Author

Listed:
  • Liang Liu

    (Hubei Subsurface Multi-Scale Imaging Key Lab, Institute of Geophysics & Geomatics, China University of Geosciences, Wuhan 430074, China)

  • Heping Pan

    (Hubei Subsurface Multi-Scale Imaging Key Lab, Institute of Geophysics & Geomatics, China University of Geosciences, Wuhan 430074, China)

  • Chengxiang Deng

    (Hubei Subsurface Multi-Scale Imaging Key Lab, Institute of Geophysics & Geomatics, China University of Geosciences, Wuhan 430074, China)

  • Guoshu Huang

    (Hubei Subsurface Multi-Scale Imaging Key Lab, Institute of Geophysics & Geomatics, China University of Geosciences, Wuhan 430074, China)

Abstract

Accurate calculation of the permeability of tight sandstone gas reservoirs has been a challenge, due to the enhanced effect of pore structure. Reservoir permeability with the same porosity and different pore structure often varies greatly. The permeability estimated by the traditional core sample regression analysis method has low accuracy, and the nuclear magnetic resonance (NMR) logging method is affected by the hydrocarbon of the reservoir. In this paper, the defined parameter can effectively quantify the difference of pore structure. Based on regression analysis of core measurement data, the model with optimal factor parameters of permeability calculation is established. This method combines the advantages of empirical models and pore structure models in calculating permeability. The results show that the method can effectively improve the accuracy of permeability. It has been successfully applied to the tight sandstone gas reservoir of He3 member in Hangjinqi area, Ordos Basin, China. Compared with other permeability theoretical models, it provides a more accurate and practical method for calculating permeability.

Suggested Citation

  • Liang Liu & Heping Pan & Chengxiang Deng & Guoshu Huang, 2019. "A Method for Improving Permeability Accuracy of Tight Sandstone Gas Reservoirs Based on Core Data and NMR Logs," Energies, MDPI, vol. 12(15), pages 1-14, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:15:p:2859-:d:251496
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