Bumps in underground coal mines are violent events that result from a buildup of stress, usually in mines underlain and overlain by massive strata. Seismic velocity tomography can be implemented to infer stress distribution at mines and determine when a dangerous situation is developing. Three different methods were employed to compare time-lapse passive seismic tomograms at a longwall coal mine. The dataset is well sampled with a dense receiver array. Parameterization and results were compared using GeoTom, TomoDD, and SIMULPS. TomoDD and SIMULPS both allow for variable gridding and relocation of microseismic events while GeoTOM does not. All three methods produced consistent results for the data set showing clear high velocity zones in areas where abutment stress is expected and low velocity zones corresponding with gob. TomoDD proved to be the most suitable method for generating tomograms from mining-induced microseismic events because it resulted in the most consistent images and the calculated velocity distribution matched prior stress distribution measurements at the site.
Seismic velocity tomography has been utilized previously in underground mines to produce velocity images that are used to infer stress redistribution. However, long-term passive seismic tomography is still a relatively immature, though promising, technology for the remote and continuous monitoring of a mine on a global scale using mining-induced microseismic events as sources. A high ratio of fatalities occurring in coal mines are the result of fall of roof, rib, or highwall. The use of passive seismic tomography may be able to detect areas of relatively high stress in a mine so that precautionary measures can be taken, improving safety for miners working underground and positively impacting productivity. In order to implement passive seismic velocity tomography three methods of tomographic inversion are explored to determine which method provides the most consistent and meaningful results.