Correlations between mining and seismicity for re-entry protocol development

Vallejos, Javier; McKinnon, Stephen D.

doi:10.1016/j.ijrmms.2011.02.014

Cited by 42 publications

(24 citation statements)

References 27 publications

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“…The exponential link-function in (2) means that the dependency on depth in h 3j will have a positive exponential effect on the average seismicity (2) and follows the results obtained by Vallejos and McKinnon (2011).…”

Section: Level 2: the Mine Wide Modelsupporting

confidence: 74%

“…The blue curves are the estimated prior distributions for the parameters the green curves represent group-level regression curves. The size s j is for visualisation proposes shown here in kilotonne (kt/week) rather than megatonne (Mt/week) any group-level dependence of the decay times with respect to depth (nor size) for the studied data, as was found in Vallejos and McKinnon (2011). The second parameter h 2j is the effect of the weekly accumulative rock mass retrieved by the production blasts in (2) on the activity.…”

Section: Parameter Estimationmentioning

confidence: 85%

“…For the regression hyperparameters / 3 ; / 4 ; / 6 ; / 7 we consider weakly-informative Cauchy hyperprior distributions proposed in Gelman et al (2008), where the effect of depth / 7 is restricted to be positive (Vallejos and McKinnon 2011) using a half-Cauchy prior distribution (Kruschke 2014) and illustrated in Fig. 3.…”

Section: Level 2: the Mine Wide Modelmentioning

confidence: 99%

“…Depth dependencies can also be explored as in Vallejos and McKinnon (2011) by pooling the orebodies and consider a single model for the entire mine but at different mining levels. This will, however, eliminate the possibility to explore dissimilarities among the orebodies and our aim to customise the production for each one of them would be lost.…”

Section: Introductionmentioning

confidence: 99%

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Modelling the Dynamic Relationship Between Mining Induced Seismic Activity and Production Rates, Depth and Size: A Mine-Wide Hierarchical Model

Martinsson

Törnman

2019

Pure Appl. Geophys.

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The dynamic properties of mining induced seismic activity with respect to production rate, depth and size are studied in seven orebodies in the same underground iron ore mine. The objective is to understand the relationship between the measured seismic activity and the: seismic decay time, planned production rate, production size and mining depth. This relationship is the first step to individually customise the production rate for each orebody in the mine, make short-term predictions of future seismicity given planned productions, and to find out in what way the available predictors affect the seismicity. The seismic response with respect to the dependent variables is parametrised and the estimated decay times for each orebody, which are of particular interest here, are compared. An autoregressive model is proposed to capture the dynamic relationship between the induced seismic activity, the current production rate and the past seismic activity. Bayesian estimation of the parameters is considered and parameter constraints are incorporated in the prior distributions. The models for all orebodies are tied together and modelled hierarchically to capture the underlying joint structure of the problem, where the mine-wide parameters are learnt together with the individual orebody parameters from the observed data. Comparisons between the parameters from the hierarchical model and independent models are given. Group-level regressions reveal dependencies on size and mining depth. Model validation with posterior predictive checking using several discrepancy measures could not detect any model deficiencies or flaws. Posterior predictive intervals are evaluated and inference of model parameters are presented.

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Section: Level 2: the Mine Wide Modelsupporting

confidence: 74%

Section: Parameter Estimationmentioning

confidence: 85%

Section: Level 2: the Mine Wide Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Modelling the Dynamic Relationship Between Mining Induced Seismic Activity and Production Rates, Depth and Size: A Mine-Wide Hierarchical Model

Martinsson

Törnman

2019

Pure Appl. Geophys.

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“…Additionally, monitoring programs to mitigate risks during the active mining process are carried out by the operators of the mine (e.g., Gibowicz, 1989;Gibowicz and Kijko, 1994;Trifu, 2002;Trifu, 2010). The aim of this monitoring is to identify regions that may be susceptible to rockbursts or structural damage (e.g., Young et al, 1992;Ge, 2005) or to decide when a safe re-entry to the mine is possible after a rockburst or larger event (e.g., Vallejos and McKinnon, 2011).…”

Section: Introductionmentioning

confidence: 99%

Macroscopic Failure Processes at Mines Revealed by Acoustic Emission (AE) Monitoring

Cailleau¹,

Kaiser²,

Dahm³

2014

Bulletin of the Seismological Society of America

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Mining activity may cause different types of seismicity and rock failure.Typical events include (1) fully induced microearthquakes in close proximity to galleries and human activity due to high-stress concentrations (border fractures) and (2) triggered earthquakes within the rock mass at larger distance to the source of the stress perturbation (inner fractures). Type 1 is important to understand the development of rock bursts and evaluate the stability of the mine. Type 2 may be associated with larger events releasing pre-existing stress and being triggered by stress changes due to the mining operation. They are important to assess the seismic hazard related to mining activity.To analyze these different failure processes, we use a dataset of high-frequency acoustic emission (AE) events monitored in an abandoned salt mine. The process of fracture formation in the rock mass was enhanced by the backfilling of a cavity. Thermal stresses induced by the backfilling operation are modeled with a finite-element approach, and observed AE activity is used to quantify the mechanism of event triggering in terms of a Coulomb failure model.Two observations are outstanding. First, the instantaneous triggering of enhanced activity and the slow growth of an inner fracture in relatively far distance to the backfilled cavity is detected. The structure already showed AE activity before the refilling started and was triggered by traction-like stress transfer. Its AE activity correlates well with the calculated Coulomb stress changes at the beginning of backfilling. Second, the sudden occurrence of a macroscopic, induced border fracture at the backfilled gallery which is oriented in agreement with the acting stress field is observed. Although AE activity at the inner fracture was triggered by tiny Coulomb stress changes, indicating a structure already in critical state, formation of the border fracture required significantly larger stresses, hinting at a previously intact rock volume.Online Material: Figure depicting the variability of the static Coulomb stress changes on the inner fracture for different rake values.

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Temporal Delineation and Quantification of Short Term Clustered Mining Seismicity

Woodward

Wesseloo

Potvin

2017

Pure Appl. Geophys.

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Correlations between mining and seismicity for re-entry protocol development

Cited by 42 publications

References 27 publications

Modelling the Dynamic Relationship Between Mining Induced Seismic Activity and Production Rates, Depth and Size: A Mine-Wide Hierarchical Model

Modelling the Dynamic Relationship Between Mining Induced Seismic Activity and Production Rates, Depth and Size: A Mine-Wide Hierarchical Model

Macroscopic Failure Processes at Mines Revealed by Acoustic Emission (AE) Monitoring

Temporal Delineation and Quantification of Short Term Clustered Mining Seismicity

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