Play fairway analysis (PFA) is an exploration tool developed in the petroleum industry that has recently been adapted to assess geothermal resource potential and reduce geothermal resource exploration risk. Geothermal exploration risk is particularly high when searching for hidden (or blind) geothermal systems (i.e., systems without surface expressions such as hot springs). Many hidden systems exist in the Great Basin region (GBR) of the western United States, a world-class geothermal province with over 1 GWe installed nameplate capacity. Since 2014, there have been four major Department of Energy funded PFA studies within or adjacent to the GBR, each focused on different parts of the region (the Great Basin interior in Nevada, the Modoc Plateau area of NE California and NW Nevada, the eastern Great Basin in Utah, and Snake River Plain in Idaho). The INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems (INGENIOUS) project aims to build on previous PFAs, as well as recent machine learning-based work to improve methodologies/workflows for discovering new, economically viable, hidden systems in the GBR. The INGENIOUS GBR study area encompasses most of Nevada, western Utah, southern Idaho, southeastern Oregon, and easternmost California. A key objective of INGENIOUS is to reduce geothermal exploration risk for hidden geothermal systems by developing a comprehensive play fairway workflow applicable to the entire GBR. Here, we present a preliminary GBR play fairway workflow built from the assessment of 14 newly updated regional geological, geophysical, and geochemical datasets compiled over the GBR study area in Phase I of the INGENIOUS project. The datasets have been analyzed with weights of evidence, logistic regression, and other tools to identify statistically significant relationships between data layers and known geothermal systems. Additionally, feature engineering has been utilized to extract maximum value from the data by developing hybrid predictive features consistent with previously identified physiographic relationships. The identified key predictive feature layers were then statistically integrated using PFA architecture into a preliminary GBR play fairway model. The resulting preliminary geothermal fairway maps improve our understanding of GBR geothermal resources and facilitate identification of potential hidden systems.

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