Refining microseismic event classification through hypocentre location

Monitoring of unstable rock slopes is a promising application of passive microseismics. Hypocentre localization might be a powerful tool to distinguish events generated by internal stress from rockfalls. However, its application is still a challenging task due to the heterogeneity of fractured rock slopes and the weakness of acoustic emissions generated by stress releases. In this study, we tried to validate a classification procedure based on hypocentre location by testing the approach on a selected subset of high quality data recorded by a five-sensor network installed on a steep rock slope. To properly manage the complexity and heterogeneity of the rock mass, we used a 3D velocity model that was derived from a tomographic experiment. We performed the localization by using the equal differential time method. The location results fairly fit our expectations: suspected rockfall events were mostly located on the rock surface or near the rock surface and suspected fracture events were mostly located inside the rock mass. However, we also observed examples of microseismic events for which our assumptions were wrong and that thanks to location results were correctly classified. This test demonstrates that hypocentre location is a promising method to improve the final classification of microseismic events.