AUTHOR=Liu Haomin , Zhang Ran , Cui Ruikang 

TITLE=Gas content prediction model considering multi-factor coupling on shale by simplified local density model

JOURNAL=Frontiers in Earth Science

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2025.1519040

DOI=10.3389/feart.2025.1519040

ISSN=2296-6463

ABSTRACT=The quantity of gas adsorbed by shale, typically quantified using the Langmuir equation in isothermal adsorption experiments, is a critical metric for evaluating the gas content and resource potential of shale formations. However, the Langmuir equation frequently underestimates the actual adsorption capacity of shale gas reservoirs because it does not differentiate between excess and absolute adsorption capacities. To address this limitation, the simplified local density (SLD) model effectively characterizes excess adsorption in porous materials. Consequently, the SLD model was employed alongside isothermal adsorption experiments conducted under diverse conditions. The Levenberg-Marquardt (LM) algorithm was utilized to develop a shale adsorption model that integrates the effects of pressure, temperature, and moisture. To achieve this, several isothermal adsorption experiments with methane were conducted at various temperatures and water saturation levels, facilitating a detailed analysis of adsorption mechanisms influenced by temperature and moisture individually. Additionally, the combined effects of these factors on the adsorption mechanism were examined, resulting in a predictive adsorption model that incorporates both temperature and moisture variables, based on the SLD model and LM algorithm. The findings demonstrate that the SLD model effectively fits shale gas adsorption data under varied conditions, with average absolute deviations remaining below 10%. When both temperature and moisture simultaneously impact the adsorption capacity of shale gas, their effects tend to counteract each other, as they primarily influence methane adsorption within the same shale pores. The temperature- and moisture-responsive model derived from the SLD framework can predict the quantity of gas adsorbed in shale under varying temperatures and water saturation conditions. Experimental data from isothermal adsorption studies of Longmaxi shale, along with corroborating literature, confirm the model’s validity and applicability.