Hypothesis: Underground hydrogen storage in depleted hydrocarbon reservoirs and aquifers has been proposed as a potential long-term solution to storing intermittently produced renewable electricity, as the subsurface formations provide secure and large storage space. Various phenomena can lead to hydrogen loss in subsurface systems with the key cause being the trapping especially during the withdrawal cycle. Capillary trapping, in particular, is strongly related to the hysteresis phenomena observed in the capillary pressure/saturation and relative-permeability/saturation curves. This paper address two key points: (1) the sole impact of hysteresis in capillary pressure on hydrogen trapping during withdrawal cycles and (2) the dependency of optimal operational parameters (injection/withdrawal flow rate) and the reservoir characteristics, such as permeability, thickness and wettability of the porous medium, on the remaining hydrogen saturation. Model: To study the capillary hysteresis during underground hydrogen storage, Killough [1] model was implemented in the MRST toolbox [2]. A comparative study was performed to quantify the impact of changes in capillary pressure behaviour by including and excluding the hysteresis and scanning curves. Additionally, this study investigates the impact of injection/withdrawal rates and the aquifer permeability for various capillary and Bond numbers in a homogeneous system. Findings: It was found that although the hydrogen storage efficiency is not considerably impacted by the inclusion of the capillary-pressure scanning curves, the impact of capillary pressure on the well properties (withdrawal rate and pressure) can become significant. Higher injection and withdrawal rates does not necessarily lead to a better performance in terms of productivity. The productivity enhancement depends on the competition between gravitational, capillary and viscous forces. The observed water upconing at relatively high capillary numbers resulted in low hydrogen productivity. highlighting the importance of well design and placement.

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Pore-network models have been used to derive relative-permeability and capillary-pressure relations, which are important for oil-recovery predictions and processes. Here, we show that relative-permeability and capillary-pressure relations on large scales can be obtained much faster with the effective-medium approximation. Our approach differs from previous work in that we use various shapes of non-circular pores and combinations of different shapes. We use a finite-element approach to compute the hydraulic conductivity of arbitrarily shaped prisms, which are partly filled with oil and water. Our present interest is confined to water-wet media. Striking features of the obtained constitutive relations are that the water relative permeabilities show a marked reduction below a critical water saturation—at which there is no infinite cluster of completely filled water pores—but the water relative permeabilities continue to be finite even at very low water saturations because of corner flow. The capillary pressure remains finite even at low water saturations. Primary-drainage oil relative permeabilities are non-zero at low oil saturations, which is in line with early gas breakthrough for the solution-gas drive oil-recovery mechanism. We compare the results obtained with the effective-medium approximation to the results obtained with a pore-network model consisting of a simple-cubic lattice of prisms. The comparison shows that the pore-network generated relative-permeability curves are completely dissimilar to the effective-medium approximation derived relative-permeability curves. Furthermore, below and near the percolation threshold, the pore-network results differ significantly from one realization to another and/or from one network size to another network size. The network-model results show discontinuous behavior at the percolation threshold. This implies that pore-network results are scale dependent and the pore-network sizes up to 301 × 301 × 301 (the limitation determined by the available computer power) studied here are still far from a representative elementary volume (REV).

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Reaction rates for different minerals are usually measured in ideal conditions in batch experiments, where the impact of pore morphology and hydrodynamics have been fully neglected. Such reaction rates are used at continuum-scale (Darcy-scale) models without the impact of pore structure on upscaled reaction rates under flow conditions. Therefore, to address the gap from batch experiments to upscaled reaction rates in continuum-scale models, a pore-network model coupled with geochemical modeling has been developed. As a case study, we simulate the geochemical reactions of geothermal energy storage/recovery in sandstone rocks by coupling PhreeqcRM (a geochemistry model) with a pore-network model. The main purpose is to delineate the impact of pore morphology and dynamic conditions on upscaling of reaction rates using the surface-weighted and volume-weighted averaging. The results show that the kaolinite reaction rate in porous media highly depends on both the flow rate and spatial distribution of reactive pores. We evaluate the impact of correlation between the reactive pores and pore size distribution on upscaled reaction rates. Results indicate that if reactive pores do not belong to the main flow path, then upscaling the geochemical reactions based on the continuum-scale or batch experiments would be erroneous. In such a scenario, the discrepancy between volume-averaged and surface-weighted average reaction rates are highlighted. Moreover, increasing the injection flow rate results in lower average concentration of different species in the effluent, while it results in higher reaction rates in porous media. This research provides insights into the complex aspects of flow-based reaction rates versus the batch reaction rates. That has a significant impact on continuum-scale modeling of reactive transport for applications such as geothermal energy and enhanced oil recovery.@en