Machine learning and a process model to better characterize hidden geothermal resources
M. Ahmmed, V.V. Vesselinov
Geothermal Rising Conference (transactions)2022
Summary
The Tularosa Basin in New Mexico has significant geothermal potential. This paper curated data from the Department of Energy's Geothermal Data Repository and analyzed them with a machine learning based framework, GeoThermalCloud (GTC), to find prospective geothermal locations. GTC discovers prospective geothermal locations and finds key parameters defining these prospectivities. Also, we found that these prospectivities are consistent with an existing comprehensive play fairway analysis. Finally, we discussed a coupling strategy between a process model (Burns equation) and GTC to obtain a better understanding about the geothermal conditions in the study area.