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

Liang Liu, Heping Pan, Chengxiang Deng and Guoshu Huang
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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

Energies, 2019, vol. 12, issue 15, 1-14

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.

Keywords: permeability; pore structure; optimal parameter; tight sandstone gas reservoirs (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
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