High-resolution temporal variations in rock elasticity at kiruna mine (block #30 to #34) using full 4D passive seismic tomography

Abstract We investigate seismic velocity changes in the rock mass related to mining induced seismic events and ore exploitation by computing a one-month long 4D elastic model of Kiirunavaara mine (Sweden). We focus on a specific mine sector, where a single $$\varvec{M_W}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>M</mml:mi> <mml:mi>W</mml:mi> </mml:msub> </mml:mrow> </mml:math> =2.0 event occurred on May 22 (02:31 local time), damaging the infrastructure. We make use of P- and S-first-arrival times obtained from the permanent seismic system for computing the full 4D (continuous 3D volume in time) seismic velocity model of Kiruna mine using a trans-dimensional Monte Carlo sampling. The trans-dimensional approach guarantees that the resolution, both in space and in time, is strictly data-driven. Our results give the following insights into the velocity differences at the mining levels and at different time-length scales. (a) We observe a striking correlation between spatial variations of $$\varvec{V_P}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>V</mml:mi> <mml:mi>P</mml:mi> </mml:msub> </mml:mrow> </mml:math> and ore-body geometry, confirming the robustness of the velocity model. Clay zones appear as a low $$\varvec{V_P/V_S}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>V</mml:mi> <mml:mi>P</mml:mi> </mml:msub> <mml:mo>/</mml:mo> <mml:msub> <mml:mi>V</mml:mi> <mml:mi>S</mml:mi> </mml:msub> </mml:mrow> </mml:math> ratio zones, as seen in previous tomographic studies. (b) High-frequency (hourly) fluctuations of the rock mass $$\varvec{V_P}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>V</mml:mi> <mml:mi>P</mml:mi> </mml:msub> </mml:mrow> </mml:math> around the ore-passes are highly correlated with seismic sequences in the same rock volumes. In particular, $$\varvec{V_P}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>V</mml:mi> <mml:mi>P</mml:mi> </mml:msub> </mml:mrow> </mml:math> increases rapidly when ore-passes are seismically active and $$\varvec{V_P}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>V</mml:mi> <mml:mi>P</mml:mi> </mml:msub> </mml:mrow> </mml:math> values keep a high value for few (1-4) hours after the end of the seismic sequence. (c) The smoothed velocity model, computed as averaged model over a 2-days moving window, suggests that low-frequency $$\varvec{V_P}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>V</mml:mi> <mml:mi>P</mml:mi> </mml:msub> </mml:mrow> </mml:math> fluctuations can be compared to stress cell measurements located closely.