Machine Learning to Characterize the State of Stress and its Influence on Geothermal Production

Summary

This presentation explores how machine learning can be used to characterize subsurface stress states and their impact on geothermal production, using field data and predictive modeling. It highlights the integration of geological, geophysical, and production data to extract features related to stress conditions and their influence on reservoir performance, with implications for optimizing geothermal energy extraction.