Data-worth analysis using ensemble smoother with multiple data assimilation to constrain uncertainty in geothermal energy production from clastic fluvial reservoirs

Geothermal energy is a key option for decarbonizing heating and cooling in the energy transition. Forecasting geothermal production has inherent uncertainty due to the heterogeneity of geological formations that host the geothermal resource and the limited data available to characterize and quantify these heterogeneities. This uncertainty leads to operational risks such as early thermal breakthrough. Identifying the most valuable monitoring data and data acquisition strategies for operators is key to constraining uncertainties and ultimately de-risking operations in a reliable and cost-effective way. Data-worth analysis quantifies the value of data provided by existing observations or proposed data collection strategies. This study combines Ensemble Smoother with Multiple Data Assimilation and data-worth analysis to constrain uncertainty in production forecasts and reservoir response for a geothermal doublet system located in a clastic, channelized fluvial reservoir. The main monitoring data includes production temperature, injection pressure, and temperature and pressure profiles along the well paths. We show that production temperature and injection pressure alone only can constrain uncertainties in production forecasts. Using observations of well temperature and pressure profiles demonstrates a threefold increase in data worth, which improves both the quantification of production forecasts and reservoir dynamics. At constant injection rates in doublet system, temperature profiles monitored along the wells provide higher data worth compared to pressure profiles. Data from a deviated monitoring borehole is advantageous. Early-time (first year) observations of temperature and pressure profiles along the injector, producer, and monitoring borehole already constrain production uncertainty prior to thermal breakthrough. Data-worth analysis is shown to be most beneficial when conducted across multiple plausible geological scenarios to ensure a more reliable assessment of collection strategies. The findings of this study yield insight into designing informative data-acquisition strategies for direct-use geothermal systems.