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• W3210365506 abstract "Shale gas is an important unconventional gas resource because of its rich storage ability. The quantitative measurement of adsorption capacity is essential to shale gas exploration. However, traditional measurements, such as gravimetric and volumetric method, are influenced by excess adsorption effect and need to be corrected at high pressures. In this work, methane adsorption curves without excess adsorption effect were obtained through two ways: a low-field nuclear magnetic resonance (NMR) experimental measurement and the adsorption curves modification using density correction method by molecular simulation. Shale powder samples from the Longmaxi Formation, China, are used as representative sample in this work. In NMR experiments, the gas in packed beds, free spaces and nanopores is identified based on the multi-peaks in the NMR transverse relaxation spectrum, which guarantees the inexistence of excess adsorption effect. In simulations, considering the complex composition of the shale matrix and complicated pore shapes, the average density of methane in organic and inorganic nanopores with various size and shape was obtained using Grand Canonical Monte Carlo (GCMC) simulation, and the excess adsorption curve measured by gravimetric and volumetric method is corrected based on such density. Through comparing the NMR measured adsorption curve and corrected excess adsorption curve, it indicates that the adsorption curve measured via NMR was in good agreement with the modified adsorption curves by density correction, which validates the NMR experiment for measuring adsorption capacity of nanoporous media with complex structure, which is suitable for shale gas and hydrogen storage, as well as other adsorption processes." @default.
• W3210365506 created "2021-11-08" @default.
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• W3210365506 date "2022-02-01" @default.
• W3210365506 modified "2023-09-23" @default.
• W3210365506 title "Methane adsorption capacity measurement in shale matrix nanopores at high pressure by low-field NMR and molecular simulation" @default.
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• W3210365506 doi "https://doi.org/10.1016/j.cej.2021.133151" @default.
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