Imaging of temporal stress redistribution due to triggered seismicity at a deep nickel mine

Ma, Xu; Westman, Erik; Fahrman, Ben; Thibodeau, Denis

doi:10.1016/j.gete.2016.01.001

Cited by 19 publications

(11 citation statements)

References 17 publications

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“…The iterative results of relocation are not shown in this study due to the emphasis of this study on the velocity change in tomograms, but the relocating function contributed to the improved the velocity structure for seismic tomograms. The process of relocating seismic events in Creighton Mine was introduced in a previous study (Ma et al 2016). Other studies applied collaborative localization methods using analytical and iterative solutions for microseismic sources in underground mining.…”

Section: Methodsmentioning

confidence: 99%

“…Passive seismic tomography, a seismic imaging method using mininginduced seismicity to infer the velocity of structures through which waves propagate, plays an increasingly important role in stress distribution and mitigating seismic hazards as mines increase their use of seismic monitoring systems (Young and Maxwell 1992;Meglis et al 2005;Baig et al 2017). Studies in seismic imaging have validated that a passive seismic tomography is a useful tool for examining stress distribution and perturbation around mining (Luxbacher et al 2008;Ma et al 2016;Westman et al 2017;Vatcher et al 2018).…”

Section: Introductionmentioning

confidence: 99%

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Passive Seismic Imaging of Stress Evolution with Mining-Induced Seismicity at Hard-Rock Deep Mines

Westman

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et al. 2020

Rock Mech Rock Eng

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This work aims to examine the stress redistribution with evolving seismicity rates using a passive seismic tomographic tool. We compiled a total of 26,000 events from two underground mines and partitioned them into multiple clusters in a temporal sequence, each of which contains 1000 events. To image stress redistribution associated with seismicity rates, we then run the tomographic studies using each cluster to yield seismic tomograms and computed the corresponding seismicity rate. We found that high velocity anomalies grew with the increase of seismicity rates, and they switched to a shrinking tendency under low seismicity rates. Results of this study imply that seismicity rates increase with increasing stress concentration and decrease with decreasing stress concentration. This study highlights the value of utilizing passive seismic tomography for estimating stress evolution associated with the change of seismicity rates at underground mines. Our findings illuminate the applications of using mining-induced seismicity to assess stress redistribution associated with seismicity rates at hard-rock mines, providing insights into seismic hazards for deep mining.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Passive Seismic Imaging of Stress Evolution with Mining-Induced Seismicity at Hard-Rock Deep Mines

Westman

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et al. 2020

Rock Mech Rock Eng

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“…Recent advances in PST have enabled the monitoring of mining-induced stress redistribution in coal and hardrock mines [31,32,53]. The basic goal of microseismic tomography is to image subsurface properties by using the many low-magnitude seismic events (e.g., microearthquakes) that are recorded by a microseismic monitoring system in a deep mine.…”

Section: Passive Seismic Tomography (Pst)mentioning

confidence: 99%

Efficient generalized Golub–Kahan based methods for dynamic inverse problems

et al. 2018

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We consider efficient methods for computing solutions to and estimating uncertainties in dynamic inverse problems, where the parameters of interest may change during the measurement procedure. Compared to static inverse problems, incorporating prior information in both space and time in a Bayesian framework can become computationally intensive, in part, due to the large number of unknown parameters. In these problems, explicit computation of the square root and/or inverse of the prior covariance matrix is not possible. In this work, we develop efficient, iterative, matrix-free methods based on the generalized Golub-Kahan bidiagonalization that allow automatic regularization parameter and variance estimation. We demonstrate that these methods can be more flexible than standard methods and develop efficient implementations that can exploit structure in the prior, as well as possible structure in the forward model. Numerical examples from photoacoustic tomography, deblurring, and passive seismic tomography demonstrate the range of applicability and effectiveness of the described approaches. Specifically, in passive seismic tomography, we demonstrate our approach on both synthetic and real data. To demonstrate the scalability of our algorithm, we solve a dynamic inverse problem with approximately 43, 000 measurements and 7.8 million unknowns in under 40 seconds on a standard desktop.

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“…These techniques have been used extensively and successfully in the Earth Sciences to map characteristics of the Earth at great depths, for example, the identification of the Mohorovicic Discontinuity (Moho); see Rawlinson et al (2010) for a description of the history of tomographic techniques. To a lesser extent, these techniques have been applied in the mining environment, which is at a much smaller scale, where correlations between velocities and i) geomechanical characteristics of the rock mass (Cai et al 2014;Hemmati Nourani et al 2017;Watanabe and Sassa 1996), and ii) stress anomalies (Cao et al 2015;Friedel et al 1995Friedel et al , 1997He et al 2011;Hosseini et al 2013;Krauß et al 2014;Luxbacher et al 2008;Ma et al 2016;Young and Maxwell 1992) are evaluated. Much of this work was conducted in soft rock environments (coal mines).…”

Section: Introductionmentioning

confidence: 99%