Hydrogen storage in depleted gas fields is a promising option for the large-scale storage of excess renewable energy. In the framework of the hydrogen storage assessment for the "Underground Sun Storage" project, we conduct a multi-step geochemical modelling approach to study fluid-rock interactions by means of equilibrium and kinetic batch simulations. With the equilibrium approach, we estimate the long-term consequences of hydrogen storage, whereas kinetic models are used to investigate the interactions between hydrogen and the formation on the time scales of typical storage cycles. The kinetic approach suggests that reactions of hydrogen with minerals become only relevant over timescales much longer than the considered storage cycles. The final kinetic model considers both mineral reactions and hydrogen dissolution to be kinetically controlled. Interactions among hydrogen and aqueous-phase components seem to be dominant within the storage-relevant time span. Additionally, sensitivity analyses of hydrogen dissolution kinetics, which we consider to be the controlling parameter of the overall reaction system, were performed. Reliable data on the kinetic rates of mineral dissolution and precipitation reactions, specifically in the presence of hydrogen, are scarce and often not representative of the studied conditions. These uncertainties in the kinetic rates for minerals such as pyrite and pyrrhotite were investigated and are discussed in the present work. The proposed geochemical workflow provides valuable insight into controlling mechanisms and risk evaluation of hydrogen storage projects and may serve as a guideline for future investigations.

The equivalent permeability, keq of stratified fractured porous rocks and its anisotropy is important for hydrocarbon reservoir engineering, groundwater hydrology, and subsurface contaminant transport. However, it is difficult to constrain this tensor property as it is strongly influenced by infrequent large fractures. Boreholes miss them and their directional sampling bias affects the collected geostatistical data. Samples taken at any scale smaller than that of interest truncate distributions and this bias leads to an incorrect characterization and property upscaling. To better understand this sampling problem, we have investigated a collection of outcrop‐data‐based Discrete Fracture and Matrix (DFM) models with mechanically constrained fracture aperture distributions, trying to establish a useful Representative Elementary Volume (REV). Finite‐element analysis and flow‐based upscaling have been used to determine keq eigenvalues and anisotropy. While our results indicate a convergence toward a scale‐invariant keq REV with increasing sample size, keq magnitude can have multi‐modal distributions. REV size relates to the length of dilated fracture segments as opposed to overall fracture length. Tensor orientation and degree of anisotropy also converge with sample size. However, the REV for keq anisotropy is larger than that for keq magnitude. Across scales, tensor orientation varies spatially, reflecting inhomogeneity of the fracture patterns. Inhomogeneity is particularly pronounced where the ambient stress selectively activates late‐ as opposed to early (through‐going) fractures. While we cannot detect any increase of keq with sample size as postulated in some earlier studies, our results highlight a strong keq anisotropy that influences scale dependence.

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Since more than half of the crude oil is deposited in naturally fractured reservoirs, more research has been focused on characterizing and understanding the fracture impact on their production performance. Naturally open fractures are interpreted from Fullbore Formation Micro-Imaging (FMI) logs. According to the fracture aperture, they are classified as major, medium, minor and hairy fractures in decreasing order of their respective aperture size. Different fracture types were set up in this work as a Discrete Fracture Network (DFN) in synthetic models and a sector model from a highly naturally fractured carbonate reservoir. The field sector model includes four wells containing image logs from two wells and production data from two other wells. Numerous simulations were conducted to capture the contribution of fracture type on production performance. Primary recovery was used for synthetic and field sector models, while waterflooding and gas injection scenarios were considered just for the synthetic models. The results showed that the fracture type and its extent play an essential role in production for all studied models. The reservoir production capabilities might be underestimated by ignoring any fracture types present in the reservoir, especially the major ones. In the secondary recovery, fractures had different impacts. Better displacement and higher recovery were promoted for waterflooding, whereas faster breakthrough times were observed for the gas injection. The performance during gas injection was more dependent on fracture permeability changes than waterflooding. This study’s findings can help in better understanding the impact of the different types of fracture networks on oil recovery at the various production stages. Additionally, the history matching process can be improved by including all types of fractures in the dynamic model. Any simplification of the fracture types might end in overestimating or underestimating the oil recovery.