A multivariate statistical analysis with artificial neural networks for geothermometric studies of geothermal systems has been carried out.

Na, K, Mg, Ca y Li compositions of geothermal fluids were evaluated for determining their contributions in the estimation of deep equilibrium temperatures of geothermal wells.

log(Na/K) showed the highest contribution ranging from 69% to 75%.

The results obtained in this geochemometrical study will enable in the future to develop a multicomponent geothermometer for the exploration and exploitation of geothermal systems.