Large areas of prospective mineral regions are buried by regolith cover and have been overlooked owing to the difficulty of identifying and verifying deeper targets below. This presents a huge opportunity for mineral exploration as new technologies emerge to address this challenge. New techniques must be able to image buried geological structures in adequate detail for geologists to make informed decisions about the presence of suitable structures to host a mineral deposit. Potential field methods provide a broad scale exploration picture but lack the resolution provided by active source seismic surveys. A significant impediment to the uptake of seismic techniques in minerals exploration has been the complexity of the outputs. We address this in two ways. Firstly, we use new seismic processing and velocity model building workflows specifically tailored for hard rock environments. These provide considerable uplift over legacy seismic data sets as well as high quality new subsurface imaging results. Secondly, using these high-fidelity results, we use new automated, data-driven workflows to provide more geological outputs which can be used to inform key aspects of minerals systems at multiple scales. New automated interpretation techniques adapted from the oil and gas industry using machine learning and artificial intelligence are now being applied to mineral 3D data sets for automatic fault detection. Along with this, seismic inversion is now being successfully employed to generate robust 3D rock and rock property volumes incorporating all available drillhole control. The combination of these two approaches results in a comprehensive 3D geologic model of structure and stratigraphy at a resolution rarely seen in the minerals industry. Our paper will present multiple case histories of how these approaches are transforming the way seismic is being used to advance geological understanding and accelerate mineral exploration under cover.

Open-Access Online Publication: May 29, 2023