2022 – New insights for tailings dam monitoring using ambient noise interferometry

Susanne Ouellet1 – Department of Geoscience, University of Calgary, Canada, Jan Dettmer – Department of Geoscience, University of Calgary, Canada, Gerrit Olivier – Centre for Ore Deposit and Earth Sciences, University of Tasmania, Australia, Tjaart de WitInstitute of Mine Seismology, Australia, Matthew Lato – BGC Engineering Inc., Canada

We apply a novel method to monitor tailings dams by harnessing the ambient noise wavefield to monitor changes in seismic velocities. This method is applied on a seismic dataset collected from a geophone array at a tailings dam in northern Canada and combined with a quantitative stress model, to demonstrate monitoring of shear wave velocity (Vs) changes over time. The stress model is calibrated using pond level recordings and Vs profiles obtained from seismic cone penetration tests. We demonstrate that the seismic velocity changes are inversely correlated to changes in water levels at the nearby tailings pond and are highly sensitive to changes in Vs. This paper presents advanced research on a tailings dam monitoring technology with high potential to reduce the risk of tailings dam failures worldwide. Keywords:

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