Molecular dynamics simulation of hydrogen diffusion in water-saturated clay minerals; implications for Underground Hydrogen Storage (UHS)

Ghasemi, Mehdi; Omrani, Sina; Mahmoodpour, Saeed; Zhou, Tianhang

doi:10.1016/j.ijhydene.2022.05.246

Cited by 54 publications

(23 citation statements)

References 67 publications

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“…Based on their analysis, the South East and Valence regions were favorable sites due to their geological suitability, available wind energy, and existing infrastructures. Various studies investigated the effect of H 2 diffusion , and wettability on H 2 storage. In addition to conventional storage sites, the depleted shale gas reservoir may also be a favorable option for H 2 storage.…”

Section: Introductionmentioning

confidence: 99%

Molecular Simulation of Hydrogen-Shale Gas System Phase Behavior under Multiscale Conditions: A Molecular-Level Analysis of Hydrogen Storage in Shale Gas Reservoirs

2023

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To reduce carbon emissions, hydrogen (H2) has been considered an important energy carrier, since its combustion only generates water. With the development of shale gas, depleted shale gas reservoirs might be good candidates for H2 storage. However, the mechanism of H2 storage in depleted shale gas reservoirs is not clearly understood. Therefore, in this work, we apply Monte Carlo simulation to analyze the compositional distribution and phase behavior of the H2–shale gas (H2–SG) system under multiscale (bulk + nanoscale) conditions. Our molecular simulation results show that compositional heterogeneity exists between the bulk region and the nanopores. The bulk fluid has a higher percentage of H2 while more hydrocarbons are present in nanopores. For the fluids in nanopores, hydrocarbons are adsorbed near the boundary while H2 molecules are freely distributed, which makes H2 molecules more likely to be released to the bulk region. The compositional heterogeneity and hydrocarbon adsorption collectively lead to a high percentage of H2 in the bulk fluid. Since the bulk fluid is produced during the extraction process, the high percentage of H2 in the bulk fluid means a high purity of H2 in the extracted fluid, which can be a positive factor for H2 storage in shale gas reservoirs. An increase in the volume percentage of nanopores can increase the H2 purity in the extracted fluid.

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Section: Introductionmentioning

confidence: 99%

Molecular Simulation of Hydrogen-Shale Gas System Phase Behavior under Multiscale Conditions: A Molecular-Level Analysis of Hydrogen Storage in Shale Gas Reservoirs

2023

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“…21−25 As in the case of experimental work, molecular simulation (MS) targeting hydrogen transport characteristics in the subsurface are limited. Notably, Ghasemi et al 35 estimated the diffusivity coefficient for hydrogen in clay saturated with water by employing molecular simulation (MS). 41 which are representative of real kerogen macromolecules before the optimization of structures.…”

Section: Molecular Simulation For Gas Diffusionmentioning

confidence: 99%

“…The Bosanquet equation of motion, describing transport as a result of surface tension only, was subsequently extended for flow in porous media. − With advances in computational power, molecular simulation (MS) was adopted to quantify the transport mechanism of CO 2 and CH 4 as an alternative to experimental approaches. − As in the case of experimental work, molecular simulation (MS) targeting hydrogen transport characteristics in the subsurface are limited. Notably, Ghasemi et al estimated the diffusivity coefficient for hydrogen in clay saturated with water by employing molecular simulation (MS). Results obtained suggest that there is no notable change in diffusion for pore sizes larger than 2 nm but diffusivity is proportionally correlated with the smaller pore sizes, i.e., less than 2 nm.…”

Section: Molecular Simulation For Gas Diffusionmentioning

confidence: 99%

“…21−25 As in the case of experimental work, molecular simulation (MS) targeting hydrogen transport characteristics in the subsurface are limited. Notably, Ghasemi et al 35 estimated the diffusivity coefficient for hydrogen in clay saturated with water by employing molecular simulation (MS). Results obtained suggest that there is no notable change in diffusion for pore sizes larger than 2 nm but diffusivity is proportionally correlated with the smaller pore sizes, i.e., less than 2 nm.…”

Section: Molecular Simulation For Gas Diffusionmentioning

confidence: 99%

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Hydrogen Diffusion in Organic-Rich Porous Media: Implications for Hydrogen Geo-storage

et al. 2022

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Subsurface hydrogen storage for large-scale energy supply to decarbonize a variety of greenhouse gas-emitting activities is gaining momentum worldwide to combat climate change. Hydrogen’s extensive range of flammable concentrations and low minimum ignition energy in air combined with its highly diffusive nature mandate implementation of comprehensive risk management protocols to maintain storage safety. In particular, the role of hydrogen diffusion process (self-diffusion) needs further investigation to understand H2 transport behavior and elude the associated risk of leakage for the long-term safety of the underground hydrogen storage process. Recent molecular simulation studies suggest that, compared to other subsurface storage options, depleted shale reservoirs may offer preferential storage characteristics due to excellent sealing and adsorption capabilities of shale. Data on hydrogen diffusion in organic (kerogen)-rich shale is scarce. Here, we applied molecular dynamics to compute hydrogen self-diffusivity in kerogen systems with different structures at various pressures, ranging from 3 to 41 MPa, and under an isothermal condition of 360 K. Two kerogen types of varying maturity (II-A and II-C) were utilized to create slit nanopores of 0.5 and 2 nm in size. The Knudsen number was calculated based on the mean free path and determined by the density values obtained from simulation to improve diffusion coefficient estimates. Results obtained indicate the K n data in the range from 0.64 to 9.72, demonstrating that the main transport mechanism was transitional in nature. With increasing pressure, diffusivity declined regardless of the slit pore size or kerogen type. H2 diffusion was greater for the 2 nm pore system compared to both the 0.5 nm in II-A (0.004–0.02 cm2/s) and II-C (0.0037 to 0.019 cm2/s). In addition, for a fixed nanopore size, thermal maturity does not seem to impact diffusivity. Finally, simulation results were regressed to delineate a continuous description for diffusivity as a function of pressure. For curve fitting, R2 values were found to be 98 and 92% for 2 nm pore size of II-A and II-C, respectively, while 97 and 79% for 0.5 nm pore size of II-A and II-C, respectively. The results obtained are not only of interest for storage of hydrogen in shale but also for any subsurface hydrogen storage approach where a shale layer acts as a seal to form a trap.

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“…[ 38 ] Most of the previous studies centred on asphaltene adsorption onto kaolinite, illite, montmorillonite, and, to a somewhat lesser extent, mica and chlorite. [ 39 ] According to the literature, apart from the previously mentioned clay characteristics, both cation exchange capacity (CEC) and specific surface area (SSA) are critical in asphaltene adsorption onto clay minerals. The former is defined as the capability of a clay mineral in retaining cations close to surfaces, [ 40 ] and the latter is the total amount of reactive surface available in a clay mineral.…”

Section: Introductionmentioning

confidence: 99%

Prediction of asphaltene adsorption capacity of clay minerals using machine learning

et al. 2022

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A thorough understanding of asphaltene adsorption on clay minerals is particularly important in oil production and contaminated soil remediation using claybased adsorbents. In this paper, we introduced a machine learning approach as a reliable alternative for commonly used adsorption isotherms that suffer from inherent limitations in the prediction of asphaltene adsorption onto clay minerals. Machine learning (ML) models, namely multilayer perceptron (MLP), support vector machine (SVM), decision tree (DT), random forest (RF), and committee machine intelligent system (CMIS) combined with two optimizers were used. Experimental data (142 data points for six different clay minerals) was used for the modelling. To improve the accuracy of the smart models, a comprehensive data preparation such as outlier removal and feature selection was carried out. The results showed that relatively all the proposed models predict asphaltene adsorption on clay minerals with acceptable precision. Nevertheless, the MLP model showed superior performance compared with other models in which the overall root mean square error (RMSE) and coefficient of determination (R 2 ) values of 6.72 and 0.93 were obtained, respectively. Finally, the developed MLP model was compared with the well-known adsorption isotherms of Langmuir and Freundlich and exhibited superior performance.

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Molecular dynamics simulation of hydrogen diffusion in water-saturated clay minerals; implications for Underground Hydrogen Storage (UHS)

Cited by 54 publications

References 67 publications

Molecular Simulation of Hydrogen-Shale Gas System Phase Behavior under Multiscale Conditions: A Molecular-Level Analysis of Hydrogen Storage in Shale Gas Reservoirs

Molecular Simulation of Hydrogen-Shale Gas System Phase Behavior under Multiscale Conditions: A Molecular-Level Analysis of Hydrogen Storage in Shale Gas Reservoirs

Hydrogen Diffusion in Organic-Rich Porous Media: Implications for Hydrogen Geo-storage

Prediction of asphaltene adsorption capacity of clay minerals using machine learning

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