Stochastic Inversion of Hydrothermal Properties in Heterogeneous Porous Media

Permeability, thermal conductivity, and porosity distribution are key factors to control groundwater flow and heat transport in porous media. The parameter estimation procedure is widely used to understand flow and transport behavior in geothermal systems. As recognized in most studies, this parameter estimation relies on the quality and quantity of spatiotemporal measurements. With the typically limited resources for conducting field investigations, understanding suitable sampling strategies is crucial before applying a model to site-specific conditions. This study aims to quantify uncertainties in hydro-thermal properties using Monte Carlo Simulation (MCS) and Ensemble Kalman Filter (EnKF). A synthetic two-dimensional aquifer profile is used to evaluate the accuracy of the estimated hydrothermal properties in accounting for variations in groundwater temperature resulting from cross-hole pumping and injection events. Based on the calculations of the mean absolute and squared errors for estimated hydrothermal properties, EnKF generally leads to more accurate estimates of hydrothermal properties than MCS. Furthermore, EnKF strikes a balance between accuracy and efficiency, making it the most effective method. This study highlights the strengths and limitations of each method, providing valuable insights for selecting appropriate inversion techniques to quantify uncertainties in geothermal systems. Additionally, well spacing and open screen locations are recommended to obtain optimal thermal energy in the geothermal system