APPLYING GEOGRAPHICAL WEIGHTED REGRESSION TO GEOCHEMICAL AND GEOPHYSICAL VARIABLES IN GEOTHERMAL FIELDS: SAN VICENTE GEOTHERMAL FIELD, EL SALVADOR

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, soil temperature, resistivity and gravity measurements. Bivariate GWR showed statistically significant correlations between CO₂ diffuse degassing, He concentration, ²²⁰Rn concentration and Soil temperature. He concentration had the greatest statistical weight (). Stepwise multivariate GWR was applied and the most statistically significant multivariate regression model for CO₂ soil concentration included He concentration, ²²⁰Rn concentration, Hg concentration, Soil Temperatures, Resistivity measurements and Gravimetry measurements (). Geophysical and geochemical variables appear to be strongly correlated. This behavior is the result of the influence of the geological properties and fluid storage and movement on the released gases from the reservoir and the variations in the geophysical properties. This methodology can provide a new insight into the analysis of multiple geochemical and geophysical variables and their application to understand the geothermal reservoir structure.