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Article

Control of Discrete Fracture Networks on Gas Accumulation and Reservoir Performance: An Integrated Characterization and Modeling Study in the Shahezi Formation

1
College of Resources and Environment, Yangtze University, Wuhan 430100, China
2
Cooperative Innovation Center of Unconventional Oil and Gas, Yangtze University, Wuhan 430100, China
3
State Key Laboratory of Geological Processes and Mineral Resources, School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2026, 16(1), 164; https://doi.org/10.3390/app16010164
Submission received: 19 November 2025 / Revised: 13 December 2025 / Accepted: 17 December 2025 / Published: 23 December 2025
(This article belongs to the Section Energy Science and Technology)

Abstract

A central challenge in tight fault-depression reservoirs is understanding how three-dimensional fracture structures control gas storage and flow. This study introduces a data-driven, geologically informed framework that integrates structural-mechanical coupling to decipher fracture networks within the Shahezi Formation. Our model, based on rock failure criteria, achieves quantitative fracture prediction across one-dimensional to three-dimensional scales. This capability overcomes the limitations inherent in single-method approaches for tight, fracture-dominated reservoirs. By synthesizing sedimentary facies-controlled reservoir modeling, sweet-spot inversion, and geo-engineering integration, we establish a predictive system for accurate reservoir assessment. The continental clastic Shahezi Formation is typified by secondary fractures. This study utilizes leverage small-scale data (core, thin section, log) to quantify key parameters (fracture density, aperture), enabling a systematic analysis of fracture typology, heterogeneity, and controls. Building on this foundation, and spatially constrained by large-scale datasets (seismic interpretation, stress-field simulations), we developed a robust fracture development model for deep tight reservoirs. Stress-field modeling delineated fracture-prone zones, where a discrete fracture network (DFN) model was built to characterize 3D fracture geometry and connectivity. Integrating simulated fracture size and aperture-derived permeability allowed us to quantify fracture contribution to total permeability, ultimately mapping favorable targets. The results identify favorable zones primarily in the western sector of the study area, forming an NS-trending, belt-like distribution. They are mainly concentrated around the wells Changshen-4, Changshen-40, and Changshen-41. This distribution is clearly controlled by the Qianshenzijing Fault.
Keywords: fracture development model; numerical simulation of tectonic stress field; discrete fracture network (DFN); Changling Fault Depression; Shahezi Formation fracture development model; numerical simulation of tectonic stress field; discrete fracture network (DFN); Changling Fault Depression; Shahezi Formation

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MDPI and ACS Style

Zhang, Y.; Tang, Y.; Song, H.; Qiu, L. Control of Discrete Fracture Networks on Gas Accumulation and Reservoir Performance: An Integrated Characterization and Modeling Study in the Shahezi Formation. Appl. Sci. 2026, 16, 164. https://doi.org/10.3390/app16010164

AMA Style

Zhang Y, Tang Y, Song H, Qiu L. Control of Discrete Fracture Networks on Gas Accumulation and Reservoir Performance: An Integrated Characterization and Modeling Study in the Shahezi Formation. Applied Sciences. 2026; 16(1):164. https://doi.org/10.3390/app16010164

Chicago/Turabian Style

Zhang, Yuan, Yong Tang, Huanxin Song, and Liang Qiu. 2026. "Control of Discrete Fracture Networks on Gas Accumulation and Reservoir Performance: An Integrated Characterization and Modeling Study in the Shahezi Formation" Applied Sciences 16, no. 1: 164. https://doi.org/10.3390/app16010164

APA Style

Zhang, Y., Tang, Y., Song, H., & Qiu, L. (2026). Control of Discrete Fracture Networks on Gas Accumulation and Reservoir Performance: An Integrated Characterization and Modeling Study in the Shahezi Formation. Applied Sciences, 16(1), 164. https://doi.org/10.3390/app16010164

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