Hydrogen (H₂) underground storage has attracted considerable attention as a potentially efficient strategy for the large-scale storage of H₂. Nevertheless, successful execution and long-term storage and withdrawal of H₂ necessitate a thorough understanding of the physical and chemical properties of H₂ in contact with the resident fluids. As capillary forces control H₂ migration and trapping in a subsurface environment, quantifying the interfacial tension (IFT) between H₂ and the resident fluids in the subsurface is important. In this study, molecular dynamics (MD) simulation was employed to develop a data set for the IFT of H₂-brine systems under a wide range of thermodynamic conditions (298-373 K temperatures and 1-30 MPa pressures) and NaCl salinities (0-5.02 mol·kg^-1). For the first time to our knowledge, a comprehensive assessment was carried out to introduce the most accurate force field combination for H₂-brine systems in predicting interfacial properties with an absolute relative deviation (ARD) of less than 3% compared with the experimental data. In addition, the effect of the cation type was investigated for brines containing NaCl, KCl, CaCl₂, and MgCl₂. Our results show that H₂-brine IFT decreases with increasing temperature under any pressure condition, while higher NaCl salinity increases the IFT. A slight decrease in IFT occurs when the pressure increases. Under the impact of cation type, Ca²⁺ can increase IFT values more than others, i.e., up to 12% with respect to KCl. In the last step, the predicted IFT data set was used to provide a reliable correlation using machine learning (ML). Three white-box ML approaches of the group method of data handling (GMDH), gene expression programming (GEP), and genetic programming (GP) were applied. GP demonstrates the most accurate correlation with a coefficient of determination (R²) and absolute average relative deviation (AARD) of 0.9783 and 0.9767%, respectively.

The possibility of impure carbon dioxide (CO₂) sequestration can reduce the cost of these projects and facilitate their widespread adoption. Despite this, there are a limited number of studies that address impure CO₂ sequestration aspects. In this study, we examine the convection–diffusion process of the CO₂–nitrogen (N₂) mixture dissolution in water-saturated porous media through numerical simulations. Cross-diffusion values, as the missing parameters in previous studies, are considered here to see the impact of N₂ impurity on dissolution trapping in more realistic conditions. Homogeneous porous media are used to examine this impact without side effects from the heterogeneity, and then simulations are extended to heterogeneous porous media, which are a good representative of the real fields. Heterogeneity in the permeability field is generated with sequential Gaussian simulation. Using the averaged dissolved CO₂ and dissolution fluxes for each case, we could determine the onset of different dissolution regimes and behaviors of dissolution fluxes in CO₂–N₂ mixture dissolution processes. The results show that there is a notable difference between the pure cases and impure cases. Additionally, a failure to recognize the changes in the diffusion matrix and cross-diffusion effects can result in significant errors in the dissolution process. At lower temperatures, the N₂ impurity decreases the amount and flux of CO₂ dissolution; however, at higher temperatures, sequestrating the CO₂–N₂ mixture would be a more reasonable choice due to enhancing the dissolution behavior and lowering the project costs. The results of the heterogeneous cases indicate that heterogeneity, in most cases, reduces the averaged dissolved CO₂, and dissolution flux and impedes the onset of convection. We believe that the results of this study set a basis for future studies regarding the CO₂–N₂ mixture sequestration in saline aquifers.

Solute transport and mixing in heterogeneous porous media are important to many processes of practical applications. Most of the previous studies focused on solute transport in flow of Newtonian fluids, whereas there are many processes in which the phenomenon takes place in flow of a non-Newtonian fluid. In this paper, we develop a computational approach to evaluate and upscale dispersion of a solute in flow of a shear-thinning (ST) fluid in a heterogeneous porous medium. Our results indicate that the dispersivity is a non-monotonic function of the Péclet number and the shear rate, and this behavior is accentuated by the heterogeneity of the pore space and spatial correlations between the local permeabilities. As a result, solute transport in ST fluids deviates significantly from the same phenomenon in Newtonian fluids. Moreover, the shear-dependence of the dispersivity strongly influences the fate of solute transport in porous media at large length scales, including larger effluent concentration at the breakthrough point, which also occurs much faster than Newtonian fluids. To provide further evidence for the numerical findings, we compare dispersion in flow of a power-law fluid in a single tube with the same in a bundle of such tubes. Our results emphasize the shortcomings of the current theories of dispersion to account for the role of fluid rheology in solute mixing and spreading.