Underground Hydrogen Storage (UHS) provides a large-scale and safe solution to balance the fluctuations in energy production from renewable sources and energy consumption but requires a proper and detailed characterization of the candidate reservoirs. The scope of this study was to estimate the hydrogen diffusion coefficient for real caprock samples from two natural gas storage reservoirs that are candidates for underground hydrogen storage. A significant number of adsorption/desorption tests were carried out using a Dynamic Gravimetric Vapor/Gas Sorption System. A total of 15 samples were tested at the reservoir temperature of 45 °C and using both hydrogen and methane. For each sample, two tests were performed with the same gas. Each test included four partial pressure steps of sorption alternated with desorption. After applying overshooting and buoyancy corrections, the data were then interpreted using the early time approximation of the solution to the diffusion equation. Each interpretable partial pressure step provided a value of the diffusion coefficient. In total, more than 90 estimations of the diffusion coefficient out of 120 partial pressure steps were available, allowing a thorough comparison between the diffusion of hydrogen and methane: hydrogen in the range of 1 × 10⁻¹⁰ m²/s to 6 × 10⁻⁸ m²/s and methane in the range of 9 × 10⁻¹⁰ m²/s to 2 × 10⁻⁸ m²/s. The diffusion coefficients measured on wet samples are 2 times lower compared to those measured on dry samples. Hysteresis in hydrogen adsorption/desorption was also observed.

Underground porous media are complex multiphase systems, where the behavior at the macro-scale is affected by physical phenomena occurring at the pore(micro)-scale. The understanding of pore-scale fluid flow, transport properties, and chemical reactions is fundamental to reducing the uncertainties associated with the dynamic behavior, volume capacity, and injection/withdrawal efficiency of reservoirs and groundwater systems. Lately, laboratory technologies were found to be growing along with new computational tools, for the analysis and characterization of porous media. In this context, a significant contribution is given by microfluidics, which provides synthetic tools, often referred to as micromodels or microfluidic devices, able to mimic porous media networks and offer direct visualization of fluid dynamics. This work aimed to provide a review of the design, materials, and fabrication techniques of 2D micromodels applied to the investigation of multiphase flow in underground porous media. The first part of the article describes the main aspects related to the geometrical characterization of the porous media that lead to the design of micromodels. Materials and fabrication processes to manufacture microfluidic devices are then described, and relevant applications in the field are presented. In conclusion, the strengths and limitations of this approach are discussed, and future perspectives are suggested.

The understanding of multiphase flow phenomena occurring in porous media at the pore scale is fundamental in a significant number of fields, from life science to geo and environmental engineering. However, because of the optical opacity and the geometrical complexity of natural porous media, detailed visual characterization is not possible or is limited and requires powerful and expensive imaging techniques. As a consequence, the understanding of micro-scale behavior is based on the interpretation of macro-scale parameters and indirect measurements. Microfluidic devices are transparent and synthetic tools that reproduce the porous network on a 2D plane, enabling the direct visualization of the fluid dynamics. Moreover, microfluidic patterns (also called micromodels) can be specifically designed according to research interests by tuning their geometrical features and surface properties. In this work we design, fabricate and test two different micromodels for the visualization and analysis of the gas-brine fluid flow, occurring during gas injection and withdrawal in underground storage systems. In particular, we compare two different designs: a regular grid and a real rock-like pattern reconstructed from a thin section of a sample of Hostun rock. We characterize the two media in terms of porosity, tortuosity and pore size distribution using the A* algorithm and CFD simulation. We fabricate PDMS-glass devices via soft lithography, and we perform preliminary air-water displacement tests at different capillary numbers to observe the impact of the design on the fluid dynamics. This preliminary work serves as a validation of design and fabrication procedures and opens the way to further investigations.

Some years ago, a new methodology called automatic history matching was approached by the scientific community. The idea consisted in treating history matching as an optimization process, i.e. defining a cost function representative of the discrepancy between measured (real) and simulated data, and in minimizing the cost function. The minimization of the cost function can be obtained by applying a suitable optimization algorithm. Optimization and non-linear programming were not new methodologies in the field of applied mathematics. However, the selection of the most adequate optimization algorithm among those available in the technical literature is not trivial, and the number of independent variables involved in complex reservoir simulation does not make the solution of the optimization problem a standard procedure. In fact, the main criticalities of a history matching process change for each analyzed reservoir. As a consequence, the identification of an optimization methodology appropriate for a wide variety of reservoirs is quite impossible. Therefore, automatic history matching remains a dream and, more realistically, assisted history matching can be the target. The concept of assisted history matching is that reservoir engineers are still in charge of reservoir model calibration, but they can rely on reliable optimization tools to better explore the parameter space and to speed up the convergence to one or more solutions. The aim of this paper consists in discussing benefits, limitations and drawbacks of assisted history matching by applying new techniques, based on multi objective optimization and heuristic strategies. Attention is focused on the possibility offered by these methodologies of obtaining a number of calibrated reservoir models. Each of these models can then be used for field performance prediction so as to obtain a representative evaluation of the risks associated to any reservoir development scenario.