Machine Learning Approaches for Predicting Total Organic Carbon From Petrophysical Well Logs in the Wufeng–Longmaxi Shale, Southeast Sichuan Basin, China
AI summaryPretrains on diverse geophysical data and adapts to forecasting weather, ocean waves, air quality and tropical cyclone tracks, exploring a foundation model for multiple Earth-system tasks.
AI summaryReviews how differentiable computation can jointly train physical components and neural networks to support process understanding, parameter estimation and geoscientific prediction.
AI summaryProposes 11 features of an ideal Earth foundation model, including multisensor integration, awareness of location and scale, and physical consistency, and discusses evaluation and research directions.
AI summaryProposes a workflow that embeds geological domain knowledge in input data, model design and output interpretation to address interpretability, generalisation and physical consistency in AI-based mineral prospectivity mapping.