Uncertainty quantification and optimization method applied to time-continuous geothermal energy extraction

Uncertainties in static and dynamic subsurface parameters are involved in geothermal field modeling. The quantification of such uncertainties is important to guide field-development alternatives and decision-making. This work presents a novel method for estimating thermal recovery and produced-enthalpy rates, combined with uncertainty quantification and optimization. We use time-continuous, multi-objective uncertainty quantification for geothermal recovery by water re-injection. The uncertainty ranges were determined using a database of 135 geothermal fields. Thermal recovery and produced-enthalpy rates are then evaluated as functions of dimensionless uncertainty parameters. Using the proposed method, a set of 25 geothermal fields are analyzed to determine optimal well spacing. This method quantifies time-continuous uncertainty and global sensitivity for geothermal field modeling undergoing re-injection when detailed subsurface data are not available. •New workflow to perform time-continuous multi-objectives uncertainty quantification.•Data-driven parameter selection based on 135 geothermal fields worldwide.•Applied ANCOVA sensitivity indices for time-continuous nested functions.•Workflow applied to optimize well spacing for 25 geothermal fields.