Olivier, G 2017, 'Inferring subtle stress changes related to blasting and large seismic events in mines using ambient noise', in J Wesseloo (ed.), Proceedings of the Eighth International Conference on Deep and High Stress Mining
, Australian Centre for Geomechanics, Perth, pp. 233-246.
Over the last decade, using ambient seismic noise correlations has been widely adopted in crustal seismology to image and monitor the subsurface. The method relies on the reconstruction of the seismic Green’s function between sensors, effectively turning one station in to a virtual active source. Since this process is repeatable, subtle changes in seismic velocity, attenuation and anisotropy can be measured over time. In some settings, these measurements can be made on an hourly (or even shorter) basis. To use this method routinely in underground mines, it is important to determine the cause of velocity variations in the absence of large dynamic stress perturbations (such as blasts). It also is important to calibrate the seismic velocity changes in terms of known stress changes so the effect of mining activities can be quantified in units that can be used by geotechnical engineers. The results presented here indicate that atmospheric air pressure changes can have a measurable influence on the long term seismic velocity variations at depth in the absence of large dynamic stress perturbations. This influence enabled me to determine the sensitivity of the relative velocity changes to stress, where a value of 3.2 × 10−6 %∕Pa was found. This calibration essentially enables me to turn each sensor pair in an underground mine into a stress meter, which in turn enabled me to infer the subtle change in static stress after a blast. The static stress change was only visible after the non-linear behaviour (damage and relaxation) had subsided five days after the blast. This new method can be used by geotechnical engineers to monitor the evolution of stress and to assess seismic hazard in conjunction with conventional microseismic methods.
Keywords: passive seismic, ambient noise, seismic monitoring
Keywords: passive seismic, ambient noise, seismic monitoring
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