Master of Science (MS), Ohio University, 2021, Geological Sciences (Arts and Sciences)

Past geological, geochemical and geophysical studies by LaGeo have shown the presence of a 12 km2 geothermal reservoir at San Vicente Geothermal Field (SVGF) . This reservoir has an estimated thickness of 600 to 1200 m underneath a 600 to 800 m thick capping rock. All this located under the northern flank of San Vicente volcano. Potential drilling targets for geothermal exploitation are determined through visual geographical correlation of geological, geochemical and geophysical variables. However there are statistical methods such as geographical weighted regression and cluster analysis that allow us to establish statistical correlation between the geochemical and geophysical variables that are related to fluid storage and flow. Carbon dioxide (CO2) diffuse degassing and other gases, and geophysical variables such as resistivity and gravity, are related to high permeability areas, such as faults, and underground fluid movement within a geothermal field. In order to establish more accurate drilling targets for geothermal exploitation, a better and more objective data interpretation can be achieved by establishing the statistical correlation of CO2 diffuse degassing to other geochemical or geophysical variables. We have used Geographically Weighted Regression (GWR) models via computer program GWR4 to determine the statistical correlation between the space dependent geophysical and geochemical variables. Data from San Vicente Geothermal Field in El Salvador was used to determine the spatial correlations between CO2 soil concentration and the concentrations of He, 222Rn, 220Rn, Hg, resistivity and gravity measurements. Bivariate GWR showed statistically significant correlations between CO2 diffuse degassing, He concentration, Hg concentration, 222Rn concentration, 220Rn concentration and Magneto-telluric measurements. He concentration had the greatest statistical weight (푅푝 2 = 0.55, F = 7.21, p < 0.001). Stepwise multivariate GWR was applied and the most stati (open full item for complete abstract)

Committee: Dina Lopez Dr (Advisor); Katherine Fornash Dr (Committee Member); Schenk Xizhen Dr (Committee Member) Subjects: Earth; Energy; Environmental Geology; Geochemistry; Geographic Information Science; Geology; Natural Resource Management; Statistics