QUANTITATIVE CHARACTERIZATION OF NAVAJO SANDSTONE WELL CUTTINGS FOR CARBON STORAGE ASSESSMENT IN A DATA-POOR SUBSURFACE ENVIRONMENT, IRON COUNTY, UTAH (Invited Presentation)

In the Iron Springs District of southwest Utah, operators of an active iron mine have proposed building a direct reduced iron plant to optimize their operations and increase the domestic supply of steel. Ideally, CO₂ produced from this plant will be stored within local subsurface reservoirs at suitable depths, but considerable reservoir quality uncertainty exists due to geologically complex and poorly constrained subsurface conditions. Primary injection targets lie within eolian sequences of the ~1500’-thick Jurassic Navajo Sandstone, which lies entirely in the subsurface at a mean depth of 7,000’ below ground. The sole well penetration in the area, the 1984 ARCO Three Peaks #1 (ATP-1), yielded only cutting samples of the target reservoir. The Navajo Sandstone is largely documented as an eolian facies set with dune and inter-dune deposits that may exhibit widely divergent petrophysical properties. Our primary objectives were to quantify the inherent petrological and petrophysical properties of the Navajo Sandstone to determine its suitability as a CO₂ reservoir, derive an accurate diagenetic history using petrographic clues contained within well cuttings, and develop a robust paleo-depositional environment interpretation to predict reservoir heterogeneity away from well control. Petrographic thin sections were created from ATP-1 well cuttings to document rock properties and diagenetic features like framework grain mineralogy, cement geochemistry, fracture sets, quartz pressure solution, and iron-oxide grain coats. Photomicrographs were analyzed with automated detection software and python-based ML techniques to quantify stratigraphic changes in grain size distributions and pore space dimensions. We complemented our observations with pXRF data and interpreted our results with context from outcrop and core at well-characterized analog sites in the region. Preliminary calculations indicate that current reservoir targets may store industrial volumes of CO₂ despite a range of complex reservoir conditions where diagenetic events impacted highly favorable native rock properties. This study highlights how practical reservoir characterization can improve CO₂ storage potential models that require a detailed understanding of the extent, architecture, and rock properties of subsurface reservoirs, even in data-poor environments.