Machine Learning Optimization of Geothermal Potential Prediction with Key Control Quantification: A Case Study from Alberta's Basal Cambrian Sandstone Unit
Accurately predicting geothermal potential in sedimentary basins is critical for de-risking exploration. This study develops a robust machine learning (ML) framework that prioritizes predictive integrity through rigorous model benchmarking and interpretability analysis. Using the Lower Cambrian sandstone in the Alber...