Efficient Optimization and Uncertainty Quantification Method Applied to Time-Continuous Geothermal Energy Extraction

Abstract

Various uncertainties in subsurface static and dynamic parameters are often connected with geothermal field modeling. Simulated uncertainty quantification is a valuable technique for designing optimal field-development options and guiding decision-making. The optimization procedure comprises evaluations of numerous time-dependent flow mechanisms, which are functions of operational parameters that are susceptible to subsurface uncertainties. This paper describes a new method for evaluating time-dependent estimates of thermal recovery and produced-enthalpy rates, including uncertainty quantification and optimization. For geothermal recovery via a water re-injection system, we apply time-continuous and multi-objective uncertainty quantification. The operating and uncertainty parameter ranges are defined by a thorough database compiled for 135 geothermal fields throughout the globe. Following that, the expected thermal recovery and produced-enthalpy rates are assessed as functions of the significant uncertainty parameters based on dimensionless groups. The method is performed to 25 geothermal fields to determine optimal well spacing, indicating possible efficiency gains. This method provides a fast and reliable procedure for time-continuous uncertainty quantification and global sensitivity analysis in geothermal field modeling and optimization.