Machine learning enhancement of thermal response tests for geothermal potential evaluations at site and regional scales

Paul Bourhis, Benoît Cousin, Alessandro F. Rotta Loria, Lyesse Laloui
2021 Geothermics  
A B S T R A C T This study explores and validates a machine learning approach for the practical, effective, and precise prediction of the thermo-physical characteristics that are essential for the analysis and design of shallow geothermal systems, including borehole heat exchangers: (i) undisturbed ground temperature, (ii) ground effective thermal conductivity, and (iii) borehole thermal resistance. Benefiting from 174 thermal response tests from central and western Switzerland, the algorithm
more » ... nd, the algorithm is used to provide accurate site-specific as well as regional-scale predictions of the investigated thermo-physical characteristics, which in turn can serve preliminary yet representative evaluations of the geothermal potential of even very broad areas.
doi:10.1016/j.geothermics.2021.102132 fatcat:yjdgghz3afbhfg6mope34pfkty