Machine learning and shallow groundwater chemistry to identify geothermal prospects in the Great Basin
B. Ahmmed, V.V. Vesselinov
Renewable Energy2022DOI 10.1016/j.renene.2022.08.024
Summary
This study identifies geothermal prospects in the Great Basin using shallow groundwater geochemistry as a proxy for geothermal prospectivity. By processing sparse geochemical measurements from more than 14,000 locations, the work shows how machine learning can uncover hidden information in regional chemistry datasets and help prioritize promising areas for geothermal exploration.