Unveiling deep-seated metallic ore deposits using mining blast data: A case study of the Ashele copper polymetallic deposit

ABSTRACT Currently, the demand for metal mineral resources is high, while deep mineral exploration remains challenging. Reflection seismic methods have been playing an important role in metal mineral exploration due to their high exploration accuracy. However, reflection seismic methods are more effective for exploring layered or nearly layered media and less effective for inclined mineral deposits. In addition, reflection seismic exploration requires artificial sources of excitation, which are costly, complex to operate, and hazardous. Therefore, we develop a methodology to detect deep metal minerals using mining blasts as seismic sources within the mining area. Because no additional blasting is required, the cost is significantly reduced. At the Ashele copper mine in Xinjiang, China, we deploy 109 nodal seismometers on the earth’s surface to record mining blasts for 26 days. We use a deep-neural-network-based algorithm — PhaseNet— and a sequential earthquake association and location workflow to locate the positions of the mining blasts during the observation period. A total of 1163 blast events are located, and we use the double-difference seismic tomography method to obtain a 3D P-wave velocity structure of the study area (the S-wave picks are less reliable). The tomographic results confirm the presence of a deep ore-bearing rock mass extending from 0.7 to 1.7 km. In mining blasting, the source is located underground, allowing seismic waves to propagate deeper than those from surface sources, thereby improving detection depth. This cutting-edge method is convenient, safe, efficient, and cost-effective, offering guidance for deep metal mineral resource exploration, especially in mining areas where the ore-bearing rock mass has a higher density than the host rock.