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

Ma, Xu; Westman, Erik; Counter, Dave; Malek, Farid; Slaker, Brent

doi:10.1007/s00603-020-02076-5

Cited by 13 publications

(10 citation statements)

References 33 publications

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“…Usually, the low-velocity zones may indicate excavations or surrounding rock fracturing caused by mining-induced stress, whereas the high-velocity zones are likely caused by mining-induced stress concentration or anomalous geology structures. By using seismic tomography, Ma et al [105] found that high-velocity zones variation agree well with seismicity rates (Figure 14), which indicates that seismicity rates are positively correlated with the mininginduced stress concentration.…”

Section: 4mentioning

confidence: 89%

Review of the Evolution of Mining-Induced Stress and the Failure Characteristics of Surrounding Rock Based on Microseismic Tomography

Zhu

Xingdong

Westman

2021

Shock and Vibration

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With the gradual depletion of shallow resources, deep mining has become an inevitable trend and has become an important part of the world mining industry. The high stress concentration caused by redistribution of original stress field will lead to stress-driven failure of surrounding rock; conventional methods, such as point-location stress measurement, analytical analysis, numerical simulation, and physical modeling, are not able to completely reflect the distribution and evolution characteristics of the mining-induced stress field in real time and at mine scale, so it is difficult to fully understand, control, and prevent mining-induced injuries and fatalities. In the past decades, microseismic monitoring technology, velocity tomography, numerical simulation, and laboratory test technology have been successfully applied to better understand mining-induced stress and rock mass failures. The combination of these methods has led to innovative ways to investigate the mining-induced stress field, surrounding rock failure, and hazard prevention. This review focuses on the mining-induced stress and velocity tomography based on microseismic monitoring data. Research progress in analysis and measurement methods of mining-induced stress, rock mechanics for mining, and velocity tomography practices are presented.

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Section: 4mentioning

confidence: 89%

Review of the Evolution of Mining-Induced Stress and the Failure Characteristics of Surrounding Rock Based on Microseismic Tomography

Zhu

Xingdong

Westman

2021

Shock and Vibration

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“…In recent years, seismic monitoring of subsurface processes has also been realized through seismic tomography (e.g. Chiarabba et al, 2020) and in particular with the analysis of DD data: rock weakening due to mining activities (Qian et al, 2018;Ma et al, 2020;Luxbacher et al, 2008), granite fracturing during geothermal well stimulation (Caló et al, 2011;Caló and Dorbath, 2013) and oil&gas operations (Zhang et al, 2006). For monitoring purpose, an additional assumption is considered during DD data preparation: elastic properties of the media traversed by the seismic waves should not change between the occurrence of the selected pairs of events.…”

Section: Double Difference Data In Seismologymentioning

confidence: 99%

Exploration of the data space via trans-dimensional sampling: the case study of seismic double difference data

Agostinetti

Sgattoni

2021

Preprint

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Abstract. Double differences (DD) seismic data are widely used to define elasticity distribution in the Earth's interior, and its variation in time. DD data are often pre-processed from earthquakes recordings through expert-opinion, where couples of earthquakes are selected based on some user-defined criteria, and DD data are computed from the selected couples. We develop a novel methodology for preparing DD seismic data based on a trans-dimensional algorithm, without imposing pre-defined criteria on the selection of couples of events. We apply it to a seismic database recorded on the flank of Katla volcano (Iceland), where elasticity variations in time has been indicated. Our approach quantitatively defines the presence of changepoints that separate the seismic events in time-windows. Within each time-window, the DD data are consistent with the hypothesis of time-invariant elasticity in the subsurface, and DD data can be safely used in subsequent analysis. Due to the parsimonious behavior of the trans-dimensional algorithm, only changepoints supported by the data are retrieved. Our results indicate that: (a) retrieved changepoints are consistent with first-order variations in the data (i.e. most striking changes in the DD data are correctly reproduced in the changepoint distribution in time); (b) changepoint locations in time do correlate neither with changes in seismicity rate, nor with changes in waveforms similarity (measured through the cross-correlation coefficients); and (c) noteworthy, the changepoint distribution in time seems to be insensitive to variations in the seismic network geometry during the experiment. Our results proofs that trans-dimensional algorithms can be positively applied to pre-processing of geophysical data before the application of standard routines (i.e. before using them to solve standard geophysical inverse problems) in the so called exploration of the data space.

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“…In this study, seismicity analysis will be carried out in underground mines which require a high level of accuracy and precision in determining the location of the hypocenter. Determining the location of the hypocenter in underground mines is necessary to minimize the potential for seismic hazards in underground mines (Ma, et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

Earthquake Relocation Studies near Local Scale Sources using Double-Difference Technique

Giamboro

Hamdalah

2021

cset

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Determination of the location of the hypocenter is very necessary to monitor the potential for seismic hazard. Positioning and seismic energy can help safety workers determine which areas can be mined or temporarily halted. Earthquakes in underground mines are caused by seismic induction due to mining activities such as blasting processes, hydrofracturing, vehicle activities, etc. Earthquakes that occur are generally clustering. Earthquake events generally occur in mine openings, this is caused by mass compensation taken. The data used in this study are synthetic micro-earthquake data around the mining area. To obtain a high level of accuracy and precision, especially in determining the location and depth in determining the hypocenter using the Double-Difference (DD) method. The results of the microseismic relocation in the study area are well covered, as evidenced by the residual histogram and shift distribution. The shift of the microseismic before and after being relocated spread in all directions with the dominant direction in the NE – SW direction. The value of the microseismic shift before and after being relocated ranged from 0.5 meters to 150 meters.

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

Cited by 13 publications

References 33 publications

Review of the Evolution of Mining-Induced Stress and the Failure Characteristics of Surrounding Rock Based on Microseismic Tomography

Review of the Evolution of Mining-Induced Stress and the Failure Characteristics of Surrounding Rock Based on Microseismic Tomography

Exploration of the data space via trans-dimensional sampling: the case study of seismic double difference data

Earthquake Relocation Studies near Local Scale Sources using Double-Difference Technique

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