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By Musa D. Manzi, Raymond J. Durrheim, Richard T. Masethe

Large mining-induced seismic events and their aftershocks cause hazardous working conditions, damage infrastructure, delay production and pose a risk to miners in the deep-level gold mines of South Africa. Stress changes affecting pre-existing zones of weakness are the main drivers of large mining-induced seismic events, which are often followed by aftershocks triggered by quasi-static stress transfer within the rockmass. A better understanding of seismic source mechanisms is important if the seismic data is to be used more effectively for mine planning and to reduce the rockburst risk. Four large seismic events (ML≥2.0) associated with the mining of the Ventersdorp Contact Reef (VCR) at Kloof Gold Mine occurred on 13 June 2017. The events and their fore- and aftershocks were studied in detail to establish the circumstances and the cause of the incidents. The local magnitudes ranged from ML 2.3 to ML 3.0, the seismic moment from 0.69 to 2.25 x 1013 Nm and the source radius from 92 – 150 m. The main shocks were preceded by foreshock sequences, which were especially vigorous in the four hours before the main shock. Seismicity was recorded by in-mine arrays of three-component 4.5Hz geophones (detection threshold approx. ML -2.9). Following all four main seismic events, ML 2.3, ML 2.3, ML 2.9 and ML 3.0, the network detected a total number of 300 aftershocks ranging from ML -2.9 to ML 1.6 spread within a 1300 m radius from the centre of the seismic network. The statistical properties of the aftershocks were analysed using three scaling relationships: (i) Gutenberg–Richter frequency magnitude relationship; (ii) modified Omori’s law; and (iii) Båth’s law for the magnitude of the largest aftershock. The geological or mining feature that controlled the failure (e.g., fault, dyke, pillar, abutment) was determined by calculating the orientation of the nodal planes of the large seismic events using moment tensor analysis and studying the aftershock distributions.

Apr 26, 2022

By Lourens Scheepers

Mining induced seismicity and rockbursts have been part of the deep level gold mining industry in South Africa for many years. One could be forgiven for thinking that we should know everything there is to know by now to have rockbursting under control to a level that it has minimal impact on safety and production. Well, we don’t… There are things we know that we know, and they are implemented, or should be. There are thigs we know that we don’t know, and they are researched, or should be. There are things we don’t know that we don’t know, and, well, we don’t know… We know that seismicity and the associated potential for rockbursts generally increase with an increase in stress (increase in mining depth and/or mining span and creation of remnants) and proximity to faults and dykes. We know there are a number of potential sources of events in a mine; that is: mining abutments, pillar abutments, mining faces and geological structures (faults and dykes). We know there are a number of event mechanisms associated with these sources; that is: slip on a geological structure, shear through intact rock and bursting of the rock near the edge of a mining excavation. One of the tools used more and more and with increased success to identify event source mechanisms is Moment-Tensor analysis (MT). This typically assist in differentiating between three event mechanism components: volumetric deformation component, axial deformation component and slip / shear component. The insight gained from MT assist greatly in identifying the most likely event source to assist in understanding the rockmass response to mining. We know that the seismic response in our mines are mining induced (not natural). This may seem trivial, but it is important to realise that we influence the seismic response with the way we mine, and by how much we mine (extraction ratio). Therefore we put design rules and strategies in place to reduce the seismic hazard and we install rockburst support in our mining excavations. We know the seismic response to mining is influenced by the properties of the rockmass, including strength, stiffness and brittleness, but quantifying its influence is typically more difficult than expected. We know numerical modelling can improve the engineer’s understanding of the potential rockmass response associated with designed mining layouts and strategies. For our environment (narrow, tabular large area) elastic boundary element modelling remains the most convenient and practical approach, but it overestimates the stress at mining abutments and underestimates the stress further away from these abutments. Adding a crushing (based in limit equilibrium) modelling approach vastly improves the boundary element modelling ability to simulate the deformed (interpret fractured) zones and associated redistribution of stress. We don’t know how to quantify what an acceptable seismic risk is. We don’t know if we can mine remnants at an acceptable seismic risk. Some remnants are extracted surprisingly easy, others serve us with devastating rockbursts. The limit equilibrium modelling shows potential to significantly improve our ability to quantify the rockburst risk. We don’t know if large-scale preconditioning is possible and will be effective to significantly reduce the seismic risk associated with remnant and pillar mining. Research is required (and has been initiated). Vast areas of ground have been extracted historically in the South African gold fields. Most gold reserves are now in deeper ground (4000 m) and historic remnants (areas left before due to mining difficulties) as well as pillars (regional stability pillars). If we cannot find ways to extract these reserves at acceptable risk levels, the future of the South African gold mining industry is very short.

Apr 26, 2022

By Rene Padilla, Siyanda B. Mngadi, Gerrie van Aswegen, Peter Stonestreet

While many mine tunnels are developed through ground that must be riddled with the sources of small (and larger) mining induced seismic events, recorded by the mine seismic monitoring systems, we do not see planar discontinuities classified as seismic sources in the geotechnical databases. Here we list criteria that may be useful to identify discontinuities in drill core which are dynamic slip surfaces, parts of mining induced seismic sources. Such shear rupture surfaces in core would generally be powdery, cohesionless, and rough on cm scale. Finely broken rock and rock flour may be found in the core boxes at the discontinuities. Slickensides would be soft (easily destroyed) and kinematically consistent with the local stress field. In some cases, a cross fabric would be present, orthogonal to the slickensides, being the intersections of en-echelon extension fractures, within the dynamic shear zones, with the shear zone walls.

Apr 26, 2022

By David Beck

In Australia, Safe Work legislation requires mines to have a documented ‘Safety Case’ explaining how a mine will safely manage all major hazards. A similar requirement is legislated or inferred by regulation in all jurisdictions. For small scale, instabilities leading to day-to-day seismic hazards, a ‘Stability Safety Case’ built around observational methods and measurement triggered responses can be effective because adverse situations are easily identified and the costs of lower control measures are not onerous. Also, if the influence of a volume of yield on the mine load system is small, the response of the system will be more predictable. However, for episodes of large scale mine instability, the hazard derives from the widespread, multi component influence of the event on the mine load system. As the system response depends on interactions between many parts, the resolution of predictions will be lower and situations can arise without local precedent. Further, as episodes of large scale instability change the stiffness and nature of the connectedness between parts of the mine load system, the behavior of the system before the event will be a poor empirical basis for forecasts of event related hazards. Most importantly, Triggered Action Response Plans (TARPs) and ‘traffic light’ warning systems cannot make design choices or identify new hazard phenomena. They are ‘lower’ control measures targeting explicit human-made instability hypotheses. As such, the Safety Cases related to management of hazard from potential large scale seismic events and mine instability cannot rely solely on TARPs. Mines that successfully manage meaningful dynamic instability always acknowledge the ultimate reliance on expert human intuition, knowledge and imagination to appreciate the range of possible hazard scenarios, to make stability hypotheses and propose solutions. Complex analysis, TARPs and measurements are critical steps in the human decision cycle, but only support the making and testing of ‘Stability Hypotheses’ made by expert engineers. Relying on expert skill and judgement as essential components of a Safety Case, however essential, introduces human vulnerabilities. Another challenge is that the expert decision making process is hard to document. Beck et al 2019 first described an organizational and procedural framework for maintenance of an ongoing large-scale ‘Stability Safety Case' where a degree of expert judgement and imagination is needed to manage a seismically active mine. The structured data appreciation process outlined sufficient measurements, analysis and appreciation to confirm the stability state of the mine and was applicable to all underground mines. After several years of implementation in various forms in stoping, caving and room and pillar mines, this update addresses lessons learned and describes some considerations for numerical forecasting to establish a base case, and some challenges for empirical hazard identification.

Apr 26, 2022

By Stanisław Lasocki

We present an algorithm to integrate the uncertainties of mean activity rate and magnitude cumulative distribution function in the interval estimation of the primary seismic hazard parameters: the exceedance probability and the mean return period. The algorithm is applicable for both the parametric and nonparametric modeling of magnitude distribution. When the Gutenberg-Richter relation-based parametric model of magnitude distribution is used, the interval estimation of its parameters is based on the asymptotic normality of the maximum likelihood estimators. When the nonparametric kernel estimation of magnitude distribution is used, we apply the iterated bias-corrected and accelerated method for the interval estimation, based on the smoothed bootstrap and second-order bootstrap samples. Previous studies indicated that the uncertainty of mean activity rate significantly affects the interval estimates of hazard functions only when the activity rate is low and the inference period is not long (Orlecka-Sikora & Lasocki 2017). With increasing mean activity rate, the uncertainty of magnitude distribution dominates over the uncertainty of mean activity rate in the aggregated uncertainty of the hazard functions. The provided algorithm is generic and can be applied to capture the uncertainty of any multiparameter function from the uncertainties of its parameters. Here we present a further development of the algorithm developed by Orlecka-Sikora & Lasocki (2017) by presenting its implementation in the Traffic Light System approach. As an example of use, we present the confidence intervals estimation of hazard parameters for the datasets related to induced seismicity accompanying underground exploitation of copper ore in the Legnica-Głogów Copper District (LGCD) in Poland. The algorithm is under implementation to the EPISODES platform (https://tcs.ah-epos.eu/) - an IT platform that provides access to integrated research infrastructures of the Thematic Core Service of Anthropogenic Hazards (TCS AH) of EPOS (European Plate Observing System). The algorithm is also a component of the pilot developed within the EPOS SP project (No 871121), which aims to strengthen the interaction with the private sector and the added value for society. The pilot demonstrates the potential of the IS-EPOS platform software applications for the technology-related probabilistic assessment of time-dependent seismic hazard. The pilot supports a Traffic Light System approach. The current seismic hazard is compared to threshold values based on the exceedance probability for a given magnitude.

Apr 26, 2022

By Evan Dressel, Mark S. Diederichs, Kathy Kalenchuk

As hard rock mining develops deeper over time, there is an increasing need to predict the spatial and temporal distribution of adverse seismogenic rockmass reaction to mining. Real-time monitoring and feedback of mine data are used to tactically manage risk associated with induced-seismicity; however, strategic risk management requires reliable tools for forward predictions of seismic hazard. The forward prediction of seismic hazard is strengthened by understanding of potential seismic intensity, which often relies on well calibrated mine-wide numerical models. This paper uses a case study to explore how future seismogenic potential and the nature of future seismicity can be domained according to numerically predicted stress-strain paths at past seismic event locations. Delineation of high confinement seismogenic volumes vs. lower-confinement, high-strain seismogenic volumes at the mine-scale can be achieved, based on a loading and unloading stress path analogue, to refine understanding of seismic intensity. Practical qualitative and quantitative methods to achieve this delineation will be demonstrated. Once seismogenic mode (high-stress vs. high-strain) is identified, detailed analyses of seismic source parameters demonstrates change in seismic hazard between the domained volumes.

Apr 26, 2022

By Dragomir Gospodinov, Savka Dineva

A surprisingly large mining-induced seismic event occurred in the LKAB Kiirunavaara Mine (Sweden) on 18 May, 2020 at 03:11 (local time). The estimated moment magnitude was 4.2. The event caused extensive damage in a large section of the mine. The production in the area is not yet resumed, even by the beginning of 2022 (~20 months after the event). The Kiirunavaara Mine has one of the world’s largest underground seismic systems with approximately 253 geophones. The in-mine records of the event showed a very complex character with a several sub-events. The event was also well recorded by seismic stations out to over 9,000 km distance. Data from the underground and regional seismic systems were analysed to define and compare basic source parameters such as hypocenter location, seismic moment, as well as the seismic moment tensor. The data from the in-mine seismic system was used to study the development of the seismic process and to define elementary seismic sub-sources together with the official hypocenter location.

Apr 26, 2022

By Wieda Azani, Alexander Tarigan, Willem de Beer

In block caving, the rates and sequencing of undercut production blasting, drawbell blasting, and mucking are the key levers for attempting to manage cave performance. Cave performance encompasses a range of factors, which include growth, shape and the effect of the cave on the abutments, excavations, geological structures and lithology. We compare production data in several panels in the Grasberg DMLZ and GBC block caves with the seismic response in work areas, around geological structures, and in geotechnical domains. These comparisons enable evidence-based conceptualising of the effect of production rates and mining layouts. By also considering the correlation of seismic release rates in different parts of the rock mass, the wider influence of a cave can be gauged through considering possible stress and / or deformation transfer. This concept is not novel, but it is rarely implemented in a routine fashion, principally because production data rarely are easily available. Previously, it has also been used to retrospectively compare seismic hazard between different mines. This paper discusses practical, day-to-day tools to manage seismic response to mining. Therefore, the paper presents a methodology for presenting seismic release and production rates on integrated plots at any time to facilitate quick identification of correlated spatial regions. This methodology explores the production data collection and geolocation at Grasberg, which will be described in some detail.

Apr 26, 2022

By Elżbieta Węglińska, Andrzej Leśniak

The earthquake locations are generally scattered mainly due to a simplified velocity model or seismic event picking errors. The aim of our research was to increase the resolution of the cloud of microseismic events recorded during mining activity in the Bobrek hard coal mine on the 3/503 coalface to delineate seismically active structures using unsupervised machine learning algorithms. We presented results of applying two completely different algorithms for reducing scatter in microseismic location to all events recorded during mining activity on the coalface - the collapsing (proposed by Jones and Stewart in 1997) and condensation (proposed by Kamer in 2015). The collapsing method simplifies the seismic cloud by shifting events inside their error ellipsoids towards local source densities. The error ellipsoids are determined by errors in the measured parameters and seismic network configuration. The advantage of the collapsing method is the partial elimination of blurring of the microseismic cloud. The condensation method reduces the size of the set of seismic events without changing the geometrical information. The reduction of the number of seismic events in the catalog takes place through the condensation of localized events with larger uncertainty into events with lower uncertainty. The spatio-temporal analysis of microseismic events was performed separately on two processed clouds – collapsed and condensed one. We examined how collapsing and condensation methods affect the automatic detection of clusters of microseismicity using density-based spatial clustering of application with noise algorithms. We compared structures detected by the machine learning algorithms in both seismic clouds first created by collapsing and second by the condensation. We identified structures created by mining activity and structures related to the local tectonics activated by mining. The presented results are essential for the prediction of future tremors induced by the mining operation and tectonics and thus ensuring safety in the mine.

Apr 26, 2022

By JA Vallejos

High stress underground mining poses a significant challenge to rock mechanics and rock engineering. To overcome theses challenges significative improvements in solutions and best practices of the design and operation of mines under high stress have been developed and implemented. This paper presents certain topics related to the management of high stress for sustainable underground mining. The topics include; the effect of preconditioning techniques (destress blasting and hydraulic fracturing) in the seismic rock mass response to underground mining and the dynamic behaviour of rock support systems. The opportunities associated with research in rock mechanics and practical rock engineering are discussed.

Apr 26, 2022

By Guangyao Si, Ismet Canbulat, Xun Luo, Yi Duan

Routine analyses of seismicity and event locations are essential for coal burst risk management, especially in the presence of unfavorable and complex geology. In an Australian longwall coal mine, a small-scale seismic monitoring network was installed to monitor a section of a major dyke intersected by the roadway, which was classified as a coal burst prone zone. The Deep Convolutional Neural Network (DCNN) technique was adopted for automatically discriminating seismic events to assess seismicity in this zone. The discriminated seismic events were located with the Shortest Path Method based on the Boundary Discretization Scheme (BDS-SPM) for temporal-spatial seismic event distribution analysis. The results demonstrate that the seismic events are discriminated with an average accuracy of 94%. Moreover, the seismic events are more accurately located using the BDS-SPM with a 3D heterogeneous velocity model compared with results obtained with a homogeneous velocity model. The temporal and spatial variances in seismic activities identify that the rock fractures in the dyke zone are closely related to the longwall mining process and a local dyke has a controlling influence on the stress concentration in its vicinity.

Apr 26, 2022

By Derrick Chambers, George Kevin Chapin, M. Shawn Boltz

Seismic monitoring is one of the few noninvasive technologies with the potential to provide sub-surface geomechanical information to operators of large open-pit mines. Although passive seismic data has been used to refine emerging failure geometries and provide advance indication of surface deformations in the literature, doing so reliably in an operational context is much more difficult. This is due in part to difficulties in estimating and interpreting source locations and parameters in complex, low-stress open-pit environments. Additionally, the high costs associated with implementing, operating, and maintaining deep borehole seismic networks, which are most commonly used to monitor large open pits, can be difficult to justify, especially if monitoring benefits are not readily apparent. In this study, we explore the use of a near-surface nodal seismic deployment, which is commonly used in oil and gas exploration, for monitoring open-pit mining-related seismicity on a short-term basis. A deployment of 18 geophones was conducted on the surface in and around the Bingham Canyon Mine, a large open-pit mine near Salt Lake City, Utah, USA, where we find the small seismic array can detect and locate a variety of mining-related seismic sources, even with an extremely simplified velocity model. We outline the process of creating an idealized velocity model, developing a local magnitude scale, and interpreting the observed seismicity. Of note, we analyze a sequence of mining-induced events associated with a known structure on the south pit wall. We conclude with discussion on how surface-based deployments may be used to augment, or in some cases supplant, borehole seismic networks at large open-pit mines depending on monitoring requirements and objectives.

Apr 26, 2022

By Michael Murphy, Mark Van Dyke, VASU GANGRADE, Brent Slaker

Room-and-pillar mining in multi-level underground stone mines come with unique pillar stability issues. The pillar stability in these mines primarily depends on the thickness of interburden between mining levels and the staggering of pillars. NIOSH has previously established pillar design guidelines for shallow, flat-lying mines and single-level operations, but there is little guidance for ground control design in multiple-level stone mines. Therefore, to improve the overall understanding of ground control in these mines, a microseismic monitoring system has been installed at a multi-level underground stone mine in Tennessee with up to a 243-m overburden and a 7-m interburden thickness between levels. The microseismic system is comprised of nine uniaxial accelerometers and one triaxial accelerometer installed in the interburden. The seismic array is locally focused with all sensors installed within a 625 m2 area and is setup to monitor the seismicity around the formation of the pillar in the lower mining level. Data is collected over 11 months and comprises of over 1,000 high-confidence events that have been located in the study area comprised of post-blast activity. The event locations were identified using a 3D-velocity model, with an average 4-m location accuracy for this array calculated using the system data. Most observed seismicity was on the excavation boundary, both in the interburden and in the roof of the top level. At this stage of analysis, there are no significant rock failures with which to correlate seismicity, but event locations correlate well with presumed damage in the vicinity of blasts.

Apr 26, 2022

By Dmitriy A. Malovichko

The general theory for the description of seismic sources is briefly discussed. The effect of excavations on seismic radiation is considered. Expressions for seismic source mechanisms in terms of the geometrical and mechanical parameters of source processes are provided for the following cases: fault slip and shear failure in a confined environment, dynamic stress fracturing around a tunnel, rock fall, landslide and sudden subsidence. A classification of seismic events in mines based on source mechanisms is introduced. The classification separates blast-, slip- and crush-type events. Various approaches of analysis of source mechanisms involving forward modelling and inversion are discussed. The following examples demonstrating the utility of source mechanisms in mining are presented: forensic analysis of damaging seismic events, assessment of the increase in the depth of failure for dynamic stress fracturing around tunnels and its duration, examination of the rockmass deformation regime, assessment of deformation around tunnels using crush-type events, identification and parameterisation of weak geological structures, stress inversion from slip-type events. Finally, the requirements for seismic data to ensure high quality source mechanism solutions are briefly reviewed and future challenges in the interpretation and utilisation of seismic source mechanisms in mines are speculated on.

Apr 26, 2022

By Musa D. Manzi, Raymond J. Durrheim, Richard T. Masethe

An investigation into the source mechanism of mining-induced seismic activity plays a vital role in understanding the various modes of failure observed in the underground deep-level South African mining environment. The seismic events data for this study was captured by the mine-wide seismic system operating at Kloof Gold Mine. This system comprises 40 4.5 Hz tri-axial geophones sampling at 6 kHz installed at locations that surround the stopes mining the Ventersdorp Contact Reef (VCR), Main Reef (MR) and Kloof Reef (KR). A set of 103,753 mining-related seismic events (-3.0≤ ML ≤2.7) that occurred during 2017 and 2018 was selected for this study. The mining depth of these seismic events ranges from 1600 – 4200 m; most located close to stopes mining the VCR ore body. The main criteria used to select a subset of events for detailed analysis were the number of stations that recorded the seismic event and the azimuthal distribution of the sensors.

Apr 26, 2022

By Peiwei Xiao, Xiang Li, Biao Li, Haoyu Mao, Nuwen Xu

As an advanced method of rock engineering construction safety monitoring, microseismic monitoring technology can monitor the micro-fracture of rock masses within an effective range, and then perform forecast analysis of rockburst, cracking, falling blocks and other disasters. Although the application of microseismic monitoring technology has become more mature, how to improve its application efficiency remains to be further studied. At present, artificial intelligence has been extensively developed, and the use of intelligent algorithms to improve the efficiency of rockburst forecast can provide a valuable reference for the safe construction of underground engineering. To this end, this paper proposes a microseismic multi-parameter rockburst early warning model based on dynamic Bayesian networks. First, the sensitivity of microseismic source parameters to rockburst forecast is analyzed based on microseismic monitoring data and actual rockburst information of a hydropower station. Second, the main seismic source parameters and their data are selected and imported into a dynamic Bayesian network for learning to obtain the rockburst forecast model. The model is confirmed in its self-validation and K times cross-validation, and the receiver operating characteristic curve of the model is also analyzed, it is found that the area under the curve is close to 1, indicating that the model has good accuracy. Finally, the analysis of the influence strength of the parent and child nodes in the model reveals that the moment magnitude and source scale are the most sensitive parameters, which can be used as an important reference for rockburst forecast.

Apr 26, 2022

By Michelle Pienaar, Musa S. D. Manzi, Thabang Kgarume, Glen T. Nwaila, Raymond J. Durrheim, Abrie Oberholster, Hennie Grobler

The South African Mining, Extraction, Research, Development and Innovation (SAMERDI) strategy was launched in 2019 with the goal of modernizing the mining industry. It comprises three major research initiatives: improvement in the efficiency of extraction and health and safety in current mining operations, development of fully mechanized systems to mine narrow tabular ore bodies in hard rock, and development of extraction systems to break rock without using explosives. The crosscutting Advanced Orebody Knowledge (AOK) program seeks to develop and implement drilling and geophysical technologies that can characterize the rock mass ahead of mining and identify potentially hazardous geological features. This knowledge will be integrated with information derived from seismic monitoring. Mining methods, layouts and rock support systems will be adjusted accordingly to mitigate the risk of rockbursts. Boreholes are routinely drilled ahead of mine workings using diamond-impregnated bits. The drill core is logged to identify lithology and geological structures (especially dykes and faults that may be seismogenic), sample the ore body for grade control, and detect areas that may contain water and/or flammable gas. Methods and technology to improve the efficiency of drilling and maximize the information obtained from the drilling process, borehole core, and the borehole itself are being investigated. A range of geophysical technologies are being developed to map the rock mass from the skin of the excavation to a distance of several tens of meters. Light Detection and Ranging (LiDAR) is used to map the geometry of the excavation, including prominent joint, vein and fracture sets and the presence and performance of rock support elements and systems. Ground Penetrating Radar (GPR) is used to penetrate deeper into the rock mass and image joints, fractures bedding planes that influence the stability of the hanging and side walls. Image processing techniques known as ‘seismic attributes’ are being applied to the radargrams to improve interpretation. Electrical Resistivity Tomography (ERT) and various active and passive seismic techniques (e.g. Tunnel Seismic Profiling (TSP), ambient noise tomography) achieve even greater penetration into the rock mass. Finally, machine learning is used to improve the processing and interpretation of seismic and radar data.

Apr 26, 2022

By Mirjana Boskovic

LKAB’s Kiirunavaara Mine is a sublevel caving iron-ore mine located above the polar circle in northern Sweden. The mine has been proclaimed seismically active since 2008 after a magnitude 3 seismic event, according to Swedish National Seismic Network (SNSN). At that time the Kiruna Mine did not have mine-wide seismic system. Since then, the Kiruna Mine experienced several damaging seismic events of which the largest one on the May 18, 2020. The magnitude, based on the moment tensor inversion results on data from the SNSN as well as seismic stations in Finland and Norway, is estimated to 4.2 ± 0.2 moment magnitude. The seismic event on the May 18, 2020 was located in the middle of the one of the productions areas and caused the major damage in the mine, damaging several kilometres of drifts on six mining levels, some of them beyond the practical repair. These damages affected four of ten production areas on several levels, some more some less. Luckily, no person got injured from the seismic event and the very long aftershock series. An important part in the whole process after the seismic event was information flow and decision-making process. It was very important to keep workers and community informed as that contributed transparency of decision-making and decreased the speculations. Resuming the production in the damaged areas in the safe manner, very soon become main focus for the mine management. It was obvious that not only rehabilitation of the areas is needed to resume the production. It was A MUST to understand the factors behind the seismic event and its mechanism to be able to avoid same situation and prevent seismic event of similar size. Mine engineers had to think outside the box to find the solutions to ‘rescue’ every drift that they could to be able to make good enough base for continued mining of the area. The paper describes actions taken in a very complex process of recovering the area that we from the beginning thought need to be abandon. Seismological analyses of the event on May 18, 2020 and past activity in the area, damage mapping, detailed studies of structures and geology, numerical modelling as well as engineering judgement were used as base for all our decisions how to proceed in attempt to restore mining of the area heavily damaged by 4.2 moment magnitude seismic event, in a safe way.

Apr 26, 2022

By B. Simser, T. Butler

Glencore’s Nickel Rim South Mine, located in Sudbury, Ontario, Canada, is a primary/secondary blasthole operation with ore zones lying between 1,100 and 1,700 m below surface. One of the main benefits of the primary/secondary mining method in high stress ground is that up to 50% of the mining will take place in secondary stopes that should be in a yielded rock mass state. Every future secondary mining stope begins as a primary stope abutment pillar. As with many mines, the stress loading history and rock mass conditions can vary considerably in space and time. Safe mining practices cannot allow for an assumption that the planned secondary stopes are indeed yielded. An incorrect assumption can result in mining development and stoping taking place in high stress ground rather than the expected yielded rock mass conditions. This can result in higher levels of seismicity than expected and incorrect ground support recommendations in areas where workers could be exposed. Seismic monitoring is the mines’ premier tool to track the actual rock mass response to mining. Yielded zones have a reasonably clear seismic signature/pattern over time that is visible in the collected data. The ability to accurately locate small magnitude seismic events can help define and delineate different stages of rock mass failure. The vast majority of the seismic data recorded by the microseismic monitoring system is below moment magnitude (Mw) 0.0. Examples are provided showing how small seismic events (Mw < -1.5) can help provide feedback from the rock mass deformation that allows the ground control engineer to gain a better understanding of how the rock mass is responding to mining processes.

Apr 26, 2022

By Xun Luo, Yi Duan

A field trial of by distributed optical fiber sensing (DOFS) technique was conducted at a longwall coal mine in Australia. This investigation was designed to assess the applicability of DOFS for microseismic monitoring in mining. The experiments used commercially available optic fiber cables, geophones and associated data acquisition instruments – a fiber interrogator and a seismic recorder. The fiber cable was deployed in a 300m deep hole and in trenches of approximately 3.5 km long on the ground surface around and across the longwall panel being mined. The results obtained from the experiments have shown that DOFS is able to acquire microseismic data with quality that is comparable to geophones. It has been proven that DOFS can achieve higher spatial resolution for seismicity sensing and higher accuracy for locating events than a geophone network. These characteristics are particularly useful for using DOFS to monitor ground vibrations associated with ground caving processes and rock fracturing events induced by mining and civil engineering. It was also found that far more additional seismic events were recorded by the fibers than by the geophones. Automated data discrimination and processing methods must be developed in order to utilize DOFS for real-time applications.

Apr 26, 2022