Geological Map

Geological maps visually represent the subsurface distribution of rock types and other geological features, crucial for applications ranging from mineral exploration to hazard assessment. Current research emphasizes improving map accuracy and efficiency through advanced computational methods, focusing on machine learning techniques like deep neural networks (including autoencoders, Bayesian networks, and GANs), and large language models to process diverse data sources (e.g., borehole descriptions, remote sensing imagery, and core scans). These advancements enable more accurate and detailed geological mapping, improving our understanding of Earth's structure and facilitating better resource management and risk mitigation.