Gas adsorption-desorption highly affect gas storage and production behaviour in shale nanopores. The study of methane adsorption isotherm in shale has been extensively conducted experimentally. The shale compositions and reservoir conditions prominently control the adsorption capacity of methane. However, to date, there is a lack of discussion on the effect of heterogeneous TOC towards the adsorption isotherm and comparison with adsorption isotherm modelling. This study used the gravimetric method for supercritical methane adsorptions - desorption isotherms measurements. Isotherms measurements were conducted with three shale samples with various TOC values (9.67, 13.9, and 15.4 wt.%) from the Eagle Ford formation at pressure up to 10 MPa and temperature at 120 °C. The isotherms gathered were fitted with standard adsorption-desorption isotherm models, Langmuir, Freundlich and extended Sips to test the applicability of these models depicted the adsorption of supercritical methane. The results show that EF C with the highest TOC content (15.4 wt.%) has the highest adsorption-desorption methane capacity, more than 0.7 mmol/g, compared to other samples. The composition differences between these samples indicate that the organic contents were likely a major controlling factor of the adsorption capacities obtained. The TOC provides a higher surface area for adsorption to occur. Thus, a higher adsorption-desorption capacity was observed through this study. On the other hand, the adsorption and desorption curves did not intercept due to the hysteresis caused by the capillary condensation. The significant binding capacity of the shale surface for methane gas molecules leads to the hysteresis observed during methane desorption. It was observed that the Freundlich model was the most accurate adsorption model in describing the adsorption-desorption behaviour with tested shales with average R2 more than 0.90 and ARE (%) less than 10 % compared to other models with 15.8 % (Langmuir) and 18.9 % (Sips). This study also proved the influence of organic matter on predicting the adsorption-desorption capacity with adsorption isotherms highlighting the importance of modelling the TOC of shale with adsorption isotherm to determine the adsorption-desorption properties.
Adsorption isotherm can be used to depict the adsorption in shale.
Gas adsorption in the porous shale matrix is critical for gas-in-place (GIP) evaluation and exploration. Adsorption investigations benefit significantly from the use of molecular simulation. However, modelling adsorption in a realistic shale topology remains a constraint, and there is a need to study the adsorption behaviour using molecular models containing both organic and inorganic nanopores. Most simulations use a single component, either kerogen (organic composition) and quartz or clay (inorganic composition), to represent the shale surface. In this work, the molecular dynamic (MD) and grand conical Monte Carlo (GCMC) simulations were utilised to provide insight into methane adsorption behaviour. Amorphous shale structures composed of kerogen and quartz were constructed. The kerogen content was varied to replicate the shale with 2 wt.% and 5 wt.% Total Organic Carbon (TOC) content with 5 nm pore size. The simulated densities of the shale structures showed consistent values with actual shale from the Montney, Antrim, and Eagle Ford formations, with 2.52 g/cm3 and 2.44 g/cm3, respectively. The Average Error Analysis (ARE) was used to assess the applicability of the proposed amorphous shale model to replicate the laboratory adsorption isotherm measurements of actual shale. The ARE function showed that the amorphous shale shows good agreement with experimental measurements of all Barnett shale samples with an average of 5.0% error and slightly higher for the Haynesville samples with 8.0% error. The differences between the experimental adsorption measurement and simulation resulted from the amorphous packing, and actual shales have more minerals than the simulated model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.