Play fairway analysis for geothermal exploration in north-western Argentina

Abstract

Play fairway analysis (PFA) is a statistically based data integration and exploration tool originating in the oil and gas industry that has recently been applied to geothermal exploration. Here, we apply geothermal PFA to a ~40,000 km2 area in the Argentine Puna of the South American Andes (average elevation >4,000 m aMSL) that has geothermal potential but no geothermal resource development to date. We develop a PF workflow customized to the local geological setting and availability of regional geoscience datasets. Evidence layers were grouped to model the spatial distribution of three primary geological attributes of a geothermal system: heat, permeability, and fluid. These layers included hot springs, geothermometry, age and distribution of volcanism, hydrothermal alteration, regional faults along with their kinematics and approximate age of most recent rupture, structural settings, and earthquakes. Spatial statistical methods were used to model and weight the distribution of these evidence layers, including distance buffers, point statistics, and weighted sum functions. Resulting favorability models were created using the veto (product) and voter (sum) methods, and both models indicate highest geothermal potential in Cerro Tuzgle/Aguas Calientes/Tocomar and west Coranzulí. Additional locations in the Puna study area may be prospective but are not resolved given the current data availability. Thus, further data collection to reduce the geological uncertainty is recommended, including acquisition of relatively low-cost datasets such as spring temperatures, fluid chemistry, detailed geological mapping, and structural characterization.