Geothermal Reservoir Parameter Identification by Wellbore–Reservoir Integrated Fluid and Heat Transport Modeling

Efficient development of karst geothermal resources relies on the accurate identification of thermophysical and hydrogeological parameters. In this paper, the integrated wellbore–reservoir model of fluid and heat transport is applied to identify hydrothermal parameters of the karst geothermal system in Tianjin, China, based on multi-type field test data. A natural state model is conducted by fitting steady-state borehole temperature measurement results to identify formation thermal conductivity, while reservoir permeability is determined via the Gauss–Marquardt–Levenberg optimization algorithm based on dynamic temperature and pressure data from pumping tests. The parameter identification results indicate a reservoir permeability of 5.25 × 10⁻¹⁴ m² and a corrected bottom-hole temperature of 109 °C. Subsequently, productivity optimization for actual heating demands (1.33 × 10⁵ m²) yields an optimal heat extraction efficiency of 6.17 MW, with a flow rate of 80 m³/h, an injection well perforated length of 388 m, and an injection temperature of 30 °C. Additionally, addressing reservoir heterogeneity, the study finds that high-permeability zones between wells significantly shorten the safe operation duration of geothermal doublets, and reducing flow rate can mitigate thermal breakthrough risk to a certain extent.