Novel machine learning methods and tools for geothermal and geochemical problems
V.V. Vesselinov, T. Kliphuis
AGU Fall Meeting2022
Summary
This presentation surveys machine-learning methods and tools for geothermal and geochemical problems, including supervised, unsupervised, and physics-informed approaches. It emphasizes hidden-feature extraction, categorization, and science-informed prediction as practical tools for analyzing complex geoscience datasets and supporting geothermal and environmental applications.