首页|Concise extraction and characterization of the pore-throat network in unconventional hydrocarbon reservoirs:A new perspective

Concise extraction and characterization of the pore-throat network in unconventional hydrocarbon reservoirs:A new perspective

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In this study,a new image-based method for the extraction and characterization of pore-throat network for unconventional hydrocarbon storage and exploitation is proposed."Pore-throat solidity",which is analogous to particle solidity,and a new method for automatic identification of pores and throats in tight sandstone oil reservoirs are introduced.Additionally,the"pore-throat combination"and"pure pore"are defined and distinguished by drawing the cumulative probability curve of the pore-throat solidity and by selecting an appropriate cutoff point.When the discrete grid set is recognized as a pore-throat combi-nation,Legendre ellipse fitting and minimum Feret diameter are used.When the pore and throat grid sets are identified as pure pores,the pore diameter can be directly calculated.Using the new method,the analytical results for the physical parameters and pore radius agree well with most prior studies.The results comparing the maximum ball and the new model could also prove the accuracy of the latter's in micro and nano scales.The new model provides a more practical theoretical basis and a new calculation method for the rapid and accurate evaluation of the complex processes of oil migration.

Hydrocarbon exploitationPoreThroatPorous mediaIdentification

Shu-Heng Du、Yong-Min Shi

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State Key Laboratory of Nonlinear Mechanics,Institute of Mechanics,Chinese Academy of Sciences,Beijing,100190,China

School of Engineering Science,University of Chinese Academy of Sciences,Beijing,100049,China

School of Earth and Space Sciences,Peking University,Beijing,100871,China

School of Earth and Space Sciences,Peking University,Beijing 100871,China

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Beijing Natural Science FoundationYoung Elite Scientists Sponsorship Program by CASTYoung Elite Scientists Sponsorship Program by BASTYouth Innovation Promotion Association CASNational Natural Science Foundation of China

8232054YESS20220094BYESS2023182202302141902132

2024

10.1016/j.petsci.2023.12.009

石油科学(英文版)
中国石油大学（北京）

石油科学(英文版)

EI
影响因子：0.88
ISSN：1672-5107
年,卷(期)：2024.21(3)