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Recent research has developed a seismic event clustering method that groups seismic events spatially while preserving the event sequence. The main benefit of this method is that it can be done proactively at any point in time as seismicity progresses. Since caving is a progressive non-blasting mining method, this clustering method could potentially detect changes in the progression of the rock mass as they occur and without retroactive analysis. This paper demonstrates the use of the new method using data from a caving mine. In particular, the fractal dimension of the seismic source parameters of time, distance and intensity are used to characterise the seismic events during three periods: development of the undercut, cave initiation, and cave propagation. The data will become a benchmark case study characterising a caving rock mass.

Application of sequential spatial clustering and fractal dimension to caving seismic event parameters of time, distance, and intensity