Abstract
Based on tracer tests and the equivalent flow channel model, this study proposes a theoretical modelling framework to back-calculate the unknown parameters of geothermal reservoirs and predict the thermal breakthrough in production wells. The inverse modelling module combines the analytical solution of the tracer transport equation with the method of moving asymptotes, and then an analytical model that considers heat advection and transfer was used to predict the thermal breakthrough in a production well. Based on the results of tracer tests in the double geothermal wells, Xianxian geothermal field, China, two equivalent flow channels were determined, and their average flow velocity, dispersion coefficient, section area, and channel length were estimated using this theoretical framework. The possible thermal breakthrough in the production well and its main influencing factors are also discussed. The theoretical model was applied to the engineering case, and the tracer test data were used to carry out the parameter back analysis and obtain the goodness of fit ( R2)=0.7907 > 0.6, indicating that the optimization result strongly correlated with the measured value and the fit was good. The values of the thermal reservoir parameters from the tracer test’s back analysis were used to predict the thermal breakthrough for the geothermal well system. The results indicated that due to the lower tracer recovery rate, the hydraulic connection between the production well and the recharge well was poor. During the 100-year service life of a geothermal well system, the production water temperature will not obviously change, and no thermal breakthrough will occur.
Highlights
Deep geothermal resources are a kind of clean and environmentally friendly renewable energy, and geothermal tail water reinjection is the key link for the sustainable exploration and utilization of deep geothermals
Based on the on-site tracer test, this paper proposes a complete theoretical framework for thermal reservoir parameter inversion and the thermal breakthrough prediction of exploitation wells based on a seepage channel model
This paper used the seepage channel model as the theoretical basis and applied the solute transport theory to modify the analytical solution describing the change in solute concentration in the production well and proposed the theoretical framework of the inverse analysis of the thermal reservoir parameters based on the method of moving asymptotes (MMA) algorithm
Summary
Deep geothermal resources are a kind of clean and environmentally friendly renewable energy, and geothermal tail water reinjection is the key link for the sustainable exploration and utilization of deep geothermals. Rich experience has been accumulated in geothermal field tracer testing, but research on both the migration law of tracers in thermal reservoir seepage channels and theoretical models to predict the thermal breakthrough of the exploitation wells is not sufficient.
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