For successful geothermal reservoir exploration, accurate temperature estimation is essential. Since reservoir temperature estimation frequently involves high uncertainties when using conventional solute geothermometers, a new statistical approach is proposed. The focus of this study is on the development of a new multicomponent geothermometer tool which requires a significantly reduced data set compared to existing approaches. The method is validated against reservoir temperature measurements in the Krafla and the Reykjanes geothermal systems. A site-specific basaltic mineral set was selected as the basis to compute the equilibrium temperatures. These high-enthalpy geothermal reservoirs are located in the neo-volcanic zone of Iceland where the fluid temperatures are known to reach up to 350 °C at a depth of 2000 m. During ascent, the fluid composition is prone to changes as well as possible phase segregation due to depressurization and boiling. Therefore, to reduce the uncertainty of temperature estimations, reservoir temperature conditions are numerically reconstructed with sensitivity analyses considering pH, aluminium concentration, and steam loss. The evaluation of the geochemical data and the sensitivity analyses were calculated via a numerical in-house tool called MulT_predict. In all cases, the temperature estimations match with the in situ temperatures measured at Krafla and Reykjanes. The development of this method tends to be a promising and precise tool for reservoir temperature estimation. The developed methodology is a fast and easy-to-handle exploration tool that can be applied to standard geochemical data without the need for a sophisticated gas analysis yet obtaining very accurate results.
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