As mining progresses to greater depths, the challenges of high stress become more pronounced, often resulting in rockbursts that significantly impact deep underground mining operations. To address these challenges, Zinkgruvan mine in Sweden is testing destress drilling as a proactive measure to reduce the propensity for rockbursts and enhance the long-term stability of the mining drift, particularly in the roof and shoulders. Destress drilling holes, in this study, were drilled at 20° inclination on the periphery of the exploration drift and strategically placed ahead of development blasts. Laser scans of the drift were conducted before and after scaling, and the point cloud data was analysed using Cloud Compare software, with the Cloud-to-Cloud (C2C) algorithm employed to detect profile changes. This allowed for a comparison between blast rounds with and without destress drilling to assess the technique’s effectiveness. Results demonstrated that destress drilling reduced stress concentrations in the surrounding rockmass, as evidenced by reduced profile change. Blast rounds with destress drilling had up to 2.5 m3 less volume added per metre. C2C analysis showed 20 % to 30 % lower standard deviation and consistently lower mean deviation, indicating improved profile uniformity. These findings highlight the technical and operational benefits of destress drilling. 

We investigate seismic velocity changes in the rock mass related to mining induced seismic events and ore exploitation by computing a one-month long 4D elastic model of Kiirunavaara mine (Sweden). We focus on a specific mine sector, where a single =2.0 event occurred on May 22 (02:31 local time), damaging the infrastructure. We make use of P- and S-first-arrival times obtained from the permanent seismic system for computing the full 4D (continuous 3D volume in time) seismic velocity model of Kiruna mine using a trans-dimensional Monte Carlo sampling. The trans-dimensional approach guarantees that the resolution, both in space and in time, is strictly data-driven. Our results give the following insights into the velocity differences at the mining levels and at different time-length scales. (a) We observe a striking correlation between spatial variations of  and ore-body geometry, confirming the robustness of the velocity model. Clay zones appear as a low  ratio zones, as seen in previous tomographic studies. (b) High-frequency (hourly) fluctuations of the rock mass  around the ore-passes are highly correlated with seismic sequences in the same rock volumes. In particular,  increases rapidly when ore-passes are seismically active and  values keep a high value for few (1-4) hours after the end of the seismic sequence. (c) The smoothed velocity model, computed as averaged model over a 2-days moving window, suggests that low-frequency  fluctuations can be compared to stress cell measurements located closely.

An unusually large event with moment magnitude MW 4.2 occurred on May 18, 2020 in Kiirunavaara Mine (Sweden), followed by very intense aftershock activity for about 2 weeks. A comprehensive interdisciplinary study found that the event was the result of a combination of stress, rock stiffness, strength, structural and mining factors.

In this paper, we concentrate on the observed patterns of seismic source parameters, inferred seismic velocity, and inferred stress and strain changes before and immediately after the large event, to appreciate potential warning signs for future similar events. The observations of the relation between investigated source parameters - apparent stress, energy index and seismic velocity changes - and calibrated stress and strain change from a calibrated mine scale numerical model, add to the understanding of system changes during the event and may assist in future to infer the stability state of parts of the mine, and potentially to identify some emerging instability hazards.

The Malmberget iron ore mine owned by LKAB (Sweden) is one of the largest iron underground mines in the world. At present 10 orebodies are being mined, with seismicity being a known issue for several of them. The seismic system consists of 143 geophones, of which 36% are triaxial. They are a mix of 4.5 and 14 Hz geophones installed underground and in crown pillars. On the ground surface five 1 Hz geophones have been installed to estimate seismic source parameters. The mine seismic system records on average 440 events monthly with ML > 0. The largest seismic event recorded until the end of 2023 is with ML 2.9. The study was carried out in order to identify some trends in seismicity as the mining goes deeper and to find a correlation with some main controlling parameters – volume and depth of the production in order to obtain information for future seismic hazard and risk analysis. Another purpose of the study was to identify trends and behaviors for different orebodies (mining areas). The seismicity correlates strongly with the production depth, but there are differences between the orebodies.

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).