"Hidden" hydrothermal technical potential & technoeconomics: Revealing permeability & fluids with more data

• Hydrothermal technical potential estimates are improved by using name plate capacities as evidence that permeability and fluids are naturally present , whereas previous estimates as used temperature with an exponential relationship to arrive at capacity ( Pinchuk et al., 2023 ). • The versatile XGBoost algorithm is used to train a model to predict hydrothermal capacity with 37 geothermal namplate capacities as labels and 48 geologic and geophysical layers as features and proxy information on permeability and fluids. • Geologic domains are used to help balance the 248 0MW sites with the 37 geothermal power plant data ( nameplate capacities). • Distributions of technical capacity and levelized cost of electricity are provided that significantly narrow the ranges from the temperature-alone estimates. Historical hydrothermal estimates have largely relied on temperature or heat flow estimates ignoring the need for natural flowing fluids. More accurate hydrothermal estimates require some indication of permeability and fluids that naturally exist in the subsurface. This paper describes a novel approach that includes proxies of permeability and fluids in hydrothermal estimates by leveraging the relatively data-rich Great Basin. Specifically, nameplate capacities (megawatts) of operating geothermal plants, negative (0 megawatt) locations and 48 geophysical and geologic features are used to used in eXtreme Gradient Boosting (XGBoost) regression to make hydrothermal capacity predictions. Additionally, this work inputs the XGBoost-based hydrothermal predictions into the Renewable Energy Potential (reV) model to quantify technical capacity, its uncertainty and techno-economics. Compared to historical hydrothermal estimates, these predictions adhere to the 37 operating geothermal plants and negative locations. We present a method for subsampling the negative sites to bring the labels into balance that uses the geologic domain knowledge to proportionally represent negatives. Overall, the distributions of the hydrothermal technical capacity and the site levelized cost of energy are respectively much tighter, lower and more accurate than the previous estimates for the Great Basin, as they include geological and geophysical surrogates for permeability and fluids. Percentile (50th and 90th, median and high estimate, respectively) models provide bookends for these metrics.