Geochemistry of Geologic Thermal Energy Storage (GeoTES) Systems: Assessment of the Weber Sandstone, Western Wyoming, USA

The geological thermal energy storage (GeoTES) technology envisions injection of surface-heated water into a geologic unit at depth to store excess heat and extract that stored heat for consumption when energy demand is high. However, both initial heating of formation brine on the surface facility and injection of heated brine back into the deep reservoir are likely to produce potentially adverse geochemical consequences such as scaling in the piping and dissolution and precipitation in the reservoir, respectively. To assess these processes, we are conducting hydrothermal experiments and supporting geochemical modeling using the Weber Sandstone formation in western Wyoming as a model GeoTES system. The Weber Sandstone is a fine-grained quartz arenite with bimodal grainsize distribution. This formation in Rock Springs area, Wyoming is known to have 92° C, circum-neutral pH brines with sodium and chloride as dominant ions. Geochemical simulations show that the brine can precipitate over a half cubic centimeter of carbonates and sulfate minerals per kilogram of brine when heated to 160° C. In an operational setting, these precipitated minerals would be separated from the brine prior to injection back into the deep reservoir. It is likely that injection of this heated and minerals-depleted brine will results in new geochemical interactions in the reservoir. To better understand these geochemical consequences, we conducted a series of long-term (over 2 months), high temperature, batch-type water-rock interaction experiments at 160º C and 200º C and 5, 16, 50 bars of partial CO2 pressure. Throughout the course of the experiments, a small volume of time-series fluid sample is collected for chemical analysis. The post-experimental mineralogical and textural characteristics of the rock along with temporal evolution of brine compositions, will be compared with their pre-experimental counterparts to constrain our team’s concurrent THMC modeling effort.