Hydrochemical characteristics and evolution of geothermal waters in western Yunnan, China based on self-organizing map and hydrogeochemical simulation

Abstract

Ascertaining the hydrochemical features of geothermal waters and their spatial distribution and the associated hydrogeochemical regimes in complex geothermal areas with intense tectonic and hydrothermal activities is important for hydrothermal resource management, but still remains difficult. Western Yunnan, located in the Mediterranean–Himalayan geothermal zone and collision zone between the Indian and Eurasian plates with diverse hydrothermal activities and temperatures, is an ideal area for such study, which was realized by utilizing self-organizing map method (SOM), hydrogeochemical simulations and solute geothermometers in this study. The combined results show that four geothermal water groups with different hydrogeochemical features were discerned. The Group 1 geothermal waters are HCO₃–Na type, and they have relatively high reservoir temperatures ranging from 170 to 200 °C and moderate d-excess (d-excess = δ²H-8∗δ¹⁸O), whose major components originate from alkaline feldspar dissolution during the deep circulation. The hydrogeochemical type of Group 2 is HCO₃–Ca–Mg with the largest d-excess and the lowest reservoir temperatures ranging from 50 to 100 °C, and carbonate mineral dissolutions are the source of their major components. Group 3 is characterized by high acidity and abundant SO₄, which is from shallow groundwaters heated by high-temperature steam comprising H₂S, with the smallest d-excess due to strong hydrothermal alteration. Group 4 (Cl–HCO₃–Na/HCO₃–Cl–Na type) possesses a smaller d-excess and the highest reservoir temperatures ranging from 160 to 240 °C, resulting from deep NaCl-type parent fluid replenishment under the influence of magmatic input. During the upward migration, alkaline feldspar dissolution followed by extensive steam loss induces elevated concentrations. Furthermore, CO₂ degassing is another vital process that affects geothermal waters evolution at high temperatures. In this study, coupling SOM network clustering and hydrogeochemical simulation sheds new light on the extraction of hydrogeochemical characteristics and evolution information.