Aftershock series of even comparatively small seismic events can pose a risk to the mining operation or the personnel in deep underground mines as the main shocks and some of the aftershocks can cause damage in the rock mass. Stochastic modeling was applied in this study for the analysis of the temporal evolution of aftershock occurrence probability during a M1.85 aftershock sequence in Kiirunavaara Mine, Sweden. The Restricted Epidemic-Type Aftershock Sequence (RETAS) model was chosen for estimation of the aftershock occurrence probability. This model considers all events with magnitude above the magnitude of completeness M0 and has the advantage of including the Modified Omori Formula (MOF) model and Epidemic-Type Aftershock Sequence (ETAS) model as its end versions, considering also all intermediate models. The model was applied sequentially to data samples covering cumulative periods of time, starting from the first 2 h after the main event and increasing them by 2 h until the period covered the entire 72-h sequence. For each sample, the best-fit RETAS version was identified and the probability of a M ≥ 0.5 aftershock for every next 2 h was determined through Monte Carlo simulation. The feasibility of the resulting probability evolution for suspension and re-starting of the mining operations was discussed together with possible prospects for future development of the methodology.

We propose a new fully automatic and robust Bayesian method to estimate precise and reliable model parameters describing the observed S-wave spectra. All the spectra associated with each event are modelled jointly, using a t-distribution as likelihood function together with informative prior distributions for increased robustness against outliers and extreme values. The model includes the observed noise and a combined empirical Green’s function. It captures source-, receiver-, and path-dependent terms in the description of the observed spectra by combining a physical source and attenuation model with a spatially and event-size dependent empirical compensation. The proposed method propagates estimation uncertainties along the entire processing chain starting from the hypocentre location and delivers reliable uncertainty description of the estimands. The objective is to automatically provide robust and valid descriptions of the observed S-wave spectra generated from an earthquake source in a noisy and heterogeneous environment. The efficiency of the method is tested with synthetic seismograms, and the model is calibrated and cross-validated using 31 640 mining induced seismic events in a iron ore mine (in north of Sweden) with an comprehensive seismic network. The model is evaluated using both posterior predictive checks and residual analysis and we found no evidence that indicates any model deficiencies with respect to central tendency, dispersion, and residual trends.

Strong mining‐induced earthquakes are often followed by aftershocks, similar to natural earthquakes. Although the magnitudes of such in‐mine aftershocks are not high, they may pose a threat to mining infrastructure, production, and primarily, people working underground. The existing post‐earthquake mining procedures usually do not consider any aspects of the physics of the mainshock. This work aims to estimate the rate and distribution of aftershocks following mining‐induced seismic events by applying the rate‐and‐state model of fault friction, which is commonly used in natural earthquake studies. It was found that both the pre‐mainshock level of seismicity and the coseismic stress change following the mainshock rupture have strong effects on the aftershock sequence. For mining‐induced seismicity, however, we need to additionally account for the constantly changing stress state caused by the ongoing exploitation. Here, we attempt to model the aftershock sequence, its rate, and distribution of two M≈2 events in iron ore Kiruna mine, Sweden. We could appropriately estimate the aftershock sequence for one of the events because both the modeled rate and distribution of aftershocks matched the observed activity; however, the model underestimated the rate of aftershocks for the other event. The results of modeling showed that aftershocks following mining events occur in the areas of pre‐mainshock activity influenced by the positive coulomb stress changes, according to the model’s assumptions. However, we also noted that some additional process not incorporated in the rate‐and‐state model may influence the aftershock sequence. Nevertheless, this type of modeling is a good tool for evaluating the risk areas in mines following a strong seismic event.

Mining, water-reservoir impoundment, underground gas storage, geothermal energy exploitation and hydrocarbon extraction have the potential to cause rock deformation and earthquakes, which may be hazardous for people, infrastructure and the environment. Restricted access to data constitutes a barrier to assessing and mitigating the associated hazards. Thematic Core Service Anthropogenic Hazards (TCS AH) of the European Plate Observing System (EPOS) provides a novel e-research infrastructure. The core of this infrastructure, the IS-EPOS Platform (tcs.ah-epos.eu) connected to international data storage nodes offers open access to large grouped datasets (here termed episodes), comprising geoscientific and associated data from industrial activity along with a large set of embedded applications for their efficient data processing, analysis and visualization. The novel team-working features of the IS-EPOS Platform facilitate collaborative and interdisciplinary scientific research, public understanding of science, citizen science applications, knowledge dissemination, data-informed policy-making and the teaching of anthropogenic hazards related to georesource exploitation. TCS AH is one of 10 thematic core services forming EPOS, a solid earth science European Research Infrastructure Consortium (ERIC) (www.epos-ip.org).

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.

The Nakamura method, which utilizes the Horizontal to Vertical Spectral Ratio (HVSR) analysis, is widely used for seismic microzonation studies. The HVSR is an easy tool for estimation of site response resonances based on recorded ambient noise; however, it gives amplifications at resonant frequencies that are poorly correlated to the actual amplifications during strong ground motion.

Generally, the site response, including any resonant effects, depends on the amplitude, frequency and duration of ground motion. An approach was proposed previously by McGuire [1], in which the transfer function of the soil response was approximated as a Single Degree of Freedom (SDOF) oscillator with one resonant frequency, obtained from the maximum in HVSR. A new approach is developed here, in which the entire HVSR curve is approximated by a manageable set of parallel band-pass resonators. Each individual oscillator is defined by three parameters: center frequency, gain, and steepness (Q factor). This approximation allows for the development and use of an analytical model of the HVSR curve.

The application of the new approach is demonstrated on data recorded by the stations of the Southern Ontario Seismic Network (SOSN/Polaris), which have well studied characteristics and site response [2,3]. Data collected at each site consists of noise recordings to obtain the HVSR, as well as earthquake records. The analytical HVSR curves for each station are used to remove the site effect component from the recorded seismograms.

To assess the performance of underground excavations and ground support when subjected to mining-induced seismicity, a site has been instrumented at the Kiirunavaara mine. Geophones, multi-point extensometers and instrumented bolts were installed at the site. After the installation, several large seismic events (local magnitude>1.5) have occurred near the site and caused serious damages. The results from site monitoring indicate that the seismic waves are amplified near the excavation surface. The rock mass and rock bolts respond to mining-induced seismicity with step changes in displacement. The ejection velocity back-calculated from the energy absorbed in the rock bolts shows good agreement with the measured peak particle velocity (PPV). It is concluded that the scaling law used to evaluate the ground motion near excavation surface needs to be improved by considering velocity amplification. Repeated loading from multiple seismic events should be considered to assess rockburst damage.

The rockfall risk due to mining-induced seismicity reduces by installing appropriate rock support to absorb the kinetic energy from a seismic event, which is calculated by assuming the mass of ejected rock and its ejection velocity. Estimation of ejection velocity is normally based on scaling laws that do not consider the effect of the excavation free-surface and existing fractures near the excavation free-surface. Field monitoring studies have shown that the peak particle velocity on the free-surface can be much larger than the velocity in deep solid rock. The interaction between the fractures and the free-surface under incident S-wave is investigated by using a two-dimensional UDEC model with fractured zone characterized as one, two, three and four sets of parallel fractures with varied intersecting angles. The results show that wave amplification factor varies according to the incident wave angle, the number of fracture sets and fracture spacing.

Mining induced seismicity is an undesired consequence of mining operations, which poses significant hazard to miners and infrastructures and requires an accurate analysis of the rupture process. Seismic moment tensors of mining-induced events help to understand the nature of mining-induced seismicity by providing information about the relationship between the mining, stress redistribution and instabilities in the rock mass. In this work, we adapt and test a waveform-based inversion method on high frequency data recorded by a dense underground seismic system in one of the largest underground mines in the world (Kiruna mine, Sweden). A stable algorithm for moment tensor inversion for comparatively small mining induced earthquakes, resolving both the double-couple and full moment tensor with high frequency data, is very challenging. Moreover, the application to underground mining system requires accounting for the 3-D geometry of the monitoring system. We construct a Green's function database using a homogeneous velocity model, but assuming a 3-D distribution of potential sources and receivers. We first perform a set of moment tensor inversions using synthetic data to test the effects of different factors on moment tensor inversion stability and source parameters accuracy, including the network spatial coverage, the number of sensors and the signal-tonoise ratio. The influence of the accuracy of the input source parameters on the inversion results is also tested. Those tests show that an accurate selection of the inversion parameters allows resolving the moment tensor also in the presence of realistic seismic noise conditions. Finally, the moment tensor inversion methodology is applied to eight events chosen from mining block #33/34 at Kiruna mine. Source parameters including scalar moment, magnitude, double-couple, compensated linear vector dipole and isotropic contributions as well as the strike, dip and rake configurations of the double-couple term were obtained. The orientations of the nodal planes of the double-couple component in most cases vary from NNW to NNE with a dip along the ore body or in the opposite direction.

Kiirunavaara (Kiruna) iron ore mine owned by LKAB (Sweden) is one of the largest underground mines. Miningstarted in 1898 as an open pit mine. In mid-1950, the mine started a transition to underground mining andpassed to only underground mining in 1962. More substantial problems with seismicity started in 2007-2008when the deepest mining level was 907 m (ca. 670 m below surface). By 2016, the mining production is at1,022–1,079 m Level (ca. 785–845 m below surface). More than one billion tonnes of ore have been extractedsince the beginning of mining. The average yearly production in recent years is 28 million tonnes.By 2016 the mine has the largest underground seismic system in the world with 204 operational geophones.The number of the sensors (geophones with natural frequencies of 4.5, 14, and a few of 30 Hz) changed withthe increasing of production depth. The major stages with seismic system upgrades are: August 2008–June2009 with 112 installed geophones, and July 2012–September 2013 with 95 installed geophones. During2016–2017 it is planned to install some additional 45 geophones.The study was carried out to identify some trends in seismicity as the mining goes deeper and to find thecorrelation with some main controlling parameters – volume and depth of the production in order to obtaininformation for future seismic hazard and risk analysis. Custom made applications within mXrap were utilisedto carry out the spatial variations of seismicity.The analysis showed substantial difference between the seismicity in the three studied blocks – 15/16, 28/30,and 33-37/34, with the weakest seismic activity in Block 15/16 (Mmax 1.6, maximum observed magnitude),followed by Block 28/30 (Mmax 2.2), and then largest seismicity in Block 33-37/34 (Mmax 2.2). The dailyseismicity rate increased substantially through the years only for Block 33-37/34. The seismicity correlatesstrongly with the production depth. In general a straightforward correlation between the production volumeand number of larger events (M > 0) was not found for the three studied blocks, assuming there are otherfactors affecting the seismicity, e.g. geological structures, areas with contrast in geomechanical properties,etc. The spatial variations of some seismic source parameters were traced for varying periods of time,depending on the major production stages (opening of new levels, full production, closing) for the threeblocks. The distributions of the cumulative seismic energy showed a maximum around and below theproduction. The cumulative seismic moment and number of events in most cases showed a maximum aroundand above the production, indicating caving in these areas. The static stress drop shows the largest valuesaround and below the production on the footwall side, corresponding also to the areas with increased stress.The energy index showed increased stresses in the same areas (EI > 1).This study is only the first overview of the seismicity in Kiruna Mine. For seismic hazard assessment and riskanalysis further more detailed studies with smaller time intervals need to be carried out to obtain more precisecorrelations between the seismic parameters and the production volume and depth, and other possible factorsaffecting seismicity (geological structures, areas with contrast geomechanical properties, etc.).