Simulation of coal resistivity dynamics during methane adsorption and desorption using an electrical rock physics model

J Jiaqi Zou (State Key Laboratory of Cellular Stress Biology, Department of Neonatology, Xiang‘an Hospital of Xiamen University, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University) S Shuangquan Chen Y Yuanji Li T Tingting Yu (Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University)

Abstract

Abstract Understanding the correlation between coal resistivity and methane content is critical for optimizing coalbed methane (CBM) recovery and ensuring mining safety. Existing studies mainly rely on empirical trend fitting, leaving a gap in model-driven analyses of resistivity dynamics during methane adsorption and desorption. This study develops a dual-coefficient electrical rock physics model integrating inorganic mineral composition, organic resistivity, methane adsorption–desorption behavior, and pore inclusion structures. Correction coefficients (0.2 for methane and 0.4 for organic resistivity) were introduced to address adsorption heterogeneity and structural complexity. Experimental validation on coal samples (density: 1.45 g/cm3, porosity: 5.5%) showed strong agreement between simulated and measured resistivity during adsorption (0.8882–3.6973 m3/t) and desorption (3.3974–2.1773 m3/t), with high correlation (R2 = 0.9815 adsorption, 0.9956 desorption; P-values = 0.9861, 0.9763). Sensitivity analysis revealed that mineral composition (e.g., quartz, clay) and inclusion aspect ratios (0–1) notably affect resistivity. Flattened inclusions (low aspect ratios) reduce resistivity more than spherical ones, especially at methane volumes lower than 0.15 m3/t. Organic content inversely correlates with resistivity; when the volume fraction exceeds 0.92, pore structure effects diminish. This work links microscopic adsorption mechanisms to macroscopic electrical properties, providing a predictive framework for CBM resource evaluation, CO2 storage monitoring, and coal mine hazard mitigation. The model adapts to diverse coal types and structural conditions, demonstrating broad applicability in research and industry.

Article Details

Volume / Issue Vol. 15, Issue 1
Published July 18, 2025
ISSN 2045-2322
Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (4)

J

Jiaqi Zou

State Key Laboratory of Cellular Stress Biology, Department of Neonatology, Xiang‘an Hospital of Xiamen University, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University

S

Shuangquan Chen

Y

Yuanji Li

T

Tingting Yu

Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University