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Original Paper | Open Access

Diagenetic origins of low resistivity pays in low-permeability sandstone reservoirs: Insights from petrology, hydrochemistry, and machine learning

Yu-Xi Suna,b, Liang Chenc( ), Yuan Qia,b, Han-Cheng Jia,b( ), Yi-Ping Hed, Yan-Qing Shia,b, Si-Cong Wanga,b, Shuang-Qi Fenga,b, Bo-Yuan Zhaoa,b, Ru-Feng Denge
State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum (Beijing), Beijing, 102249, China
College of Geosciences, China University of Petroleum (Beijing), Beijing, 102249, China
College of Science, China University of Petroleum (Beijing), Beijing, 102249, China
No. 5 Oil Production Plant, Changqing Oilfield Company, PetroChina, Xi’an, 710200, Shaanxi, China
Kunlun Digital Technology Co., Ltd., Beijing, 102206, China

Edited by Xiu-Fang Hu

Peer review under the responsibility of China University of Petroleum (Beijing).

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Abstract

Low-permeability sandstone reservoirs containing low resistivity pays (LRPs) are widely encountered within the Triassic Yanchang Formation in the Jiyuan area, Ordos Basin, China. The resistivity of these reservoirs can be as low as 2·Ω m, leading to misinterpretation by conventional logging methods. Previous studies have primarily focused on resultant factors such as conductive minerals and clay minerals. However, how different diagenetic processes couple and control low resistivity remains unclear. This study focuses on the Chang 2 interval of the Yanchang Formation, integrating petrology, hydrochemistry, and machine learning (ML) to address these challenges. Results reveal that compaction-induced concentration of formation water and feldspar dissolution are critical controls on LRP formation. Dissolution processes not only release ions such as Na+ and Cl−, increasing formation water salinity, but also produce authigenic clay minerals like kaolinite, which obstruct pore throats and trap highly saline irreducible water, significantly reducing reservoir resistivity. Additionally, dissolution generates larger pores (diameter >10 μm), enabling more stable conductive networks and further lowering resistivity. In terms of fluid identification, the two newly constructed fluid-sensitive parameters exhibit strong explanatory capability, and the RF-PFN model outperforms other ML methods in distinguishing fluid properties. Prediction case studies show that LRPs preferentially develop in areas characterized by higher sandstone content, high porosity, and intensive dissolution effects. These findings provide critical insights and practical frameworks for evaluating and predicting similar low-permeability sandstone reservoirs worldwide.

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Petroleum Science
Pages 6092-6107

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Cite this article:
Sun Y-X, Chen L, Qi Y, et al. Diagenetic origins of low resistivity pays in low-permeability sandstone reservoirs: Insights from petrology, hydrochemistry, and machine learning. Petroleum Science, 2026, 23(10): 6092-6107. https://doi.org/10.1016/j.petsci.2026.07.048

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Received: 09 June 2025
Revised: 06 February 2026
Accepted: 24 July 2026
Published: 29 July 2026
© 2026 The Authors.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).