Back Analysis of Short-Term Seismic Hazard Indicators of Larger Seismic Events in Deep Underground Mines (LKAB, Kiirunavaara Mine, Sweden)

Abstract

Back analysis for evaluation of the merits of the short-term seismic hazard indicators (precursors) used in the mines and their potential application for early warning was carried out for fourteen seismic events that potentially caused damage in Kiirunavaara Mine, Sweden, selected according to our designed criteria. Five short-term hazard indicators: Seismic Activity Rate (SAR), Cumulative Seismic Moment (CSM), Energy Index (EI), Cumulative Apparent Volume (CAV) and Seismic Apparent Stress Frequency (ASF) were tested. The behaviour of the indicators was studied using the parameters of all seismic events within a sphere around the hypocenter location of the analyzed seismic source within one month before the main (damaging) event. The size of the sphere equals the estimated radius of the analyzed seismic source (area of inelastic deformation). mXrap software (Australian Centre for Geomechanics) was used for data visualization, manipulation, analysis and extraction. The results from the main analysis showed a good agreement between the expected and actual behaviour of the SAR, CSM and CAV indicators. In overall, CSM and CAV ranked the highest positive/expected behaviour followed by SAR (Table 3). The EI and ASF ranked lowest and showed to be sensitive to the number of events within the source sphere. The rate of false warnings and missed warnings was also investigated for the 25 days-long period before the damaging events. A similar trend was observed as for the main analysed event. The results from this study can be used for further improvement of the short-term hazard estimations and early warning system in deep underground mines.

Moving towards deep underground mineral resources: Drivers, challenges and potential solutions

“…This system can be viewed as a data generation source, which provides valuable seismic data that can be analysed to monitor and guide extraction. A combination of techniques, such as near realtime data analysis, e.g., tomographic imaging (Aminzadeh and Dasgupta, 2013;Rodvelt, 2014) and predictive analytics can be used to predictively achieve mine safety (Nordström et al, 2020;Törnman, 2021). For mitigating stress concentration and reducing rockburst hazards, mining-induced energy variations in the rock mass should be minimised.…”

Reliable automatic processing of seismic events: solving the Swiss cheese problem

“…Increased sensitivity will also increase the quality of existing events by incorporating more data, under the condition that we apply robust statistics to handle additional outliers and noise. This is particularly valuable in studying precursors (Nordström et al 2020), creating prediction models (Martinsson & Törnman 2019;Wettainen & Martinsson 2014), or generating tomographic images of the rock mass, all directly depending on the amount and quality of detectable events.…”

Seismic ground motion alerts for mines

“…Mendecki, 2016, section 4.2, described a method to estimate the probability that the seismicity rate in two different time intervals are different by a given factor. Nordstrom et al (2020) back analysed the utility of 14 different parameters as short term hazard indicators or as early warnings using data from Kiirunavaara mine in Sweden. They concluded that the most successful parameters are accelerated moment, accelerated apparent volume release and increased activity rate.…”