A New Method for Full‐Size Pore Characterisation of Shale Based on <scp>NMR</scp> and <scp>HPMI</scp> : A Case Study From the Zhanhua Sag in the Jiyang Depression, Bohai Bay Basin

ABSTRACT Full‐size pore characterisation is critical for evaluating strongly heterogeneous shale reservoirs. In this study, the lacustrine shale of the Shahejie Formation in the Zhanhua Sag was analysed using high‐pressure mercury intrusion (HPMI) and nuclear magnetic resonance (NMR) combined with fractal theory to characterise full‐size pore structures. Three reservoir types are identified based on HPMI parameters such as displacement pressure and mercury saturation. Traditional T 2 –pore‐size conversion methods perform well for Type I reservoirs but systematically underestimate pore sizes in heterogeneous Type II and III reservoirs due to limited fitting points, strong heterogeneity, and exclusion of macropores. To overcome these limitations, we introduce a segmented conversion method that independently calibrates the D 1H and D 2H fractal segments and integrates the results into a unified pore‐size distribution. This method substantially improves the agreement between NMR‐ and HPMI‐derived pore‐size distributions across all reservoir types. Furthermore, theoretical analysis, supporting literature, and internal consistency of our data demonstrate that diffusion relaxation does not significantly affect T 2 under our experimental conditions. Overall, the new method provides a more accurate and physically consistent framework for full‐size pore characterisation in shale reservoirs.

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Publication Details

Journal
Geological Journal
Published
2025-12-25
DOI
https://doi.org/10.1002/gj.70181
Primary Topic
Hydrocarbon exploration and reservoir analysis
Type
article
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article

A New Method for Full‐Size Pore Characterisation of Shale Based on NMR and HPMI : A Case Study From the Zhanhua Sag in the Jiyang Depression, Bohai Bay Basin

Yousif M. Makeen, Siyuan Su, Zhenxue Jiang, Cheng Cheng et al.
Geological Journal
Hydrocarbon exploration and reservoir analysis
article

A New Method for Full‐Size Pore Characterisation of Shale Based on NMR and HPMI : A Case Study From the Zhanhua Sag in the Jiyang Depression, Bohai Bay Basin

Yousif M. Makeen, Siyuan Su, Zhenxue Jiang, Cheng Cheng, Xuanlong Shan, Rifang Zhu
article en

Abstract

ABSTRACT Full‐size pore characterisation is critical for evaluating strongly heterogeneous shale reservoirs. In this study, the lacustrine shale of the Shahejie Formation in the Zhanhua Sag was analysed using high‐pressure mercury intrusion (HPMI) and nuclear magnetic resonance (NMR) combined with fractal theory to characterise full‐size pore structures. Three reservoir types are identified based on HPMI parameters such as displacement pressure and mercury saturation. Traditional T 2 –pore‐size conversion methods perform well for Type I reservoirs but systematically underestimate pore sizes in heterogeneous Type II and III reservoirs due to limited fitting points, strong heterogeneity, and exclusion of macropores. To overcome these limitations, we introduce a segmented conversion method that independently calibrates the D 1H and D 2H fractal segments and integrates the results into a unified pore‐size distribution. This method substantially improves the agreement between NMR‐ and HPMI‐derived pore‐size distributions across all reservoir types. Furthermore, theoretical analysis, supporting literature, and internal consistency of our data demonstrate that diffusion relaxation does not significantly affect T 2 under our experimental conditions. Overall, the new method provides a more accurate and physically consistent framework for full‐size pore characterisation in shale reservoirs.

Geological Journal
Sinopec (China) (CN), Jilin University (CN), China University of Petroleum, Beijing (CN), Yibin University (CN), Jilin Agricultural University (CN)
National Natural Science Foundation of China, People's Government of Jilin Province, Jilin University, Natural Science Foundation of Sichuan Province
Life below water
Openalex Percentile: Top 42%
Hydrocarbon exploration and reservoir analysis
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