Longwall automation depends on the development of automatic coal seam (horizon) tracking and lateral guidance systems to keep mining the target coal seam while steering to the desired target. While inertial sensing has provided some success for lateral control of mining machinery, horizon control, i.e. establishing a 'flight plan' for the longwall shearer, is a critical component of longwall automation that requires spatial accuracy for changes in a horizon's depth of the order of 10 cm, and positions of structures (faults and rolls) within fractions of a metre tens of metres ahead of the longwall machine. However, securing this is still largely unachieved. Much depends on our precise prior knowledge of the coal seam's location. Coal is electrically resistive compared with its surrounding rocks. Therefore, we can use electromagnetic waves to image coal seam boundaries (roof and/or floor) and its relevant structures. Here we propose to use borehole radar profiles of in-seam drill holes to map the seam roof or floor accurately. This will help to fill the gap between coarse scale and relatively inaccurate exploration data (drilling, borehole logging and seismic) available and the detailed seam knowledge (ground penetrating radar, thermal and optical data) at the longwall face and gate roads. Integrating these datasets should provide a more accurate horizon model that can be used for longwall machine automation and guidance. In this paper, numerical modelling is used to investigate the feasibility of and factors affecting in-seam borehole radar imaging. We show that in-seam borehole radar imaging can be used to map the coal seam roof and floor position accurately with an estimated error of less than 10cm. Such accuracy requires the central frequency of the borehole radar to be no less than 100MHz and the offset of the transmitter and receiver no more than 1m.

Open-Access Online Publication: Feb 27, 2023