Technical Session: Machine Learning (1)

Session Topic: Machine Learning in Geothermal Development

Improving the Accessibility and Usability of Geothermal Information with Data Lakes and Data Pipelines on the Geothermal Data Repository - Jon Weers

Machine Learning to Characterize State of Stress Influence on Geothermal Production - Velimir Vesselinov

Machine Learning Methods for Estimating Down-hole Depth of Cut - Jacob Sacks

Prospectivity Analyses of the Utah FORGE Site using Unsupervised Machine Learning - Bulbul Ahmmed

Machine Learning Approach to Generate Synthetic Sonic Logs in Geothermal Wells - Cesar Vivas