Mineral Prospectivity

Mineral prospectivity mapping aims to predict the location and extent of valuable mineral deposits, guiding efficient and cost-effective exploration. Current research heavily utilizes machine learning, particularly deep learning models like convolutional neural networks and graph neural networks, to integrate diverse geospatial data (e.g., geophysical surveys, geological maps) and improve prediction accuracy. These advanced techniques, often incorporating multimodal data fusion and self-supervised learning, are enhancing the interpretation of complex geological datasets and improving decision-making in mineral exploration. Ultimately, these advancements contribute to a more sustainable and efficient supply of critical minerals for various industries.