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By Kathy Kalenchuk

To develop strategic and tactical strategies to manage seismic hazard in a safe and economic manner, it is necessary to understand the spatial and temporal distribution of mine wide seismogenic behavior. Global mine-scale numerical stress modelling provides a means to forward predict seismic susceptibility thereby facilitating informed decision making for the development and implementation of strategic and tactical risk mitigation measures. To make forward predictions of hazard susceptibility using global stress models with reasonable confidence, it is necessary to rigorously calibrate numerical stress models to the observed history of ground reaction. This paper demonstrates quantifiable methods for calibrating numerical models and developing probabilistic prediction criterion using seismic data. The appropriate applications of model inputs (including boundary conditions, constitutive models and material parameterization) specific to global mine-scale modelling are also discussed. Lastly, this paper demonstrates how the calibration process adds value not only to informed decision making, but also to the improved understanding of site geomechanical conditions; including enhanced identification of geotechnical domains and mechanical indicators required for seismic mechanism domaining.

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 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 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 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 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 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

By Chris Groccia, Damodara R. Chinnasane

Vale is in the process of resuming mining in the lower 810 ore body (810 OB) below 4130L at Copper Cliff Mine – South Side. Production in the lower 810 OB had continued until it was temporarily ceased in 2017 to allow for the execution of activities associated with Copper Cliff Mine Phase 1 project. While mining the stopes in both the lower and mid part of the 810 OB, a seismic response was experienced that resulted in rockbursts and challenging mining conditions. The majority of the rockbursts experienced in the past were associated with stopes mined in a bottom-up mining sequence under a diminishing pillar situation between 3350L and 3540L. The current mining plan is comprised of both top-down and bottom-up mining fronts using a center-out chevron sequence of long hole open stopes to manage induced stresses. Numerical modeling assessments have been carried out to forecast the response of the rock mass due to the planned mining. Seismicity and stress induced damage surrounding excavations are anticipated, and areas requiring extra attention have been identified. A tactical approach is being used to prepare the area for production, including replacement of ground support elements that are damaged or have insufficient residual capacity, and installation of dynamic support in areas anticipated to experience bulking and/or dynamic loading that would exceed the current support system’s capacity. A series of monitoring programs are being put in place to confirm current conditions, and to monitor the response of the rock mass to proactively implement ground control tactics should the need arise. This paper provides a summary of the approach used to forecast, monitor, and manage the behavior of the 810 OB rock mass response to continued mining at depth.

Apr 26, 2022

By Eduardo Rojas, Pedro Landeros

El Teniente Mine expansion plans are currently under development and construction stages through an integrated project strategy that will allow the continuity of future mining. The deepest sector corresponds to Andes Norte Project that faced rockburst risks during tunneling in a completely different manner, implementing different actions for the mitigation of seismic hazard and seismic risk management, based on the following main aspects: rock mass preconditioning techniques such as destress blasting and hydraulic fracturing, improvement of rock support design with the inclusion of elements with higher energy dissipation capacities, use of mechanized equipment for the most critical activities in addition to re-entry protocols and improvements in geological, geomechanical and seismic data collection procedures to reduce the uncertainty of rock mass behavior. The current seismic risk management strategy integrates all of these elements and is the basis of construction methodologies in use, supporting the technical feasibility of tunneling in high-stress environments.

Apr 26, 2022

By Zhiyuan Shen, Dan Zhao

The abstract discusses the importance of reliable mine monitoring systems for preventing accidents. It focuses on diagnosing ventilation system failures caused by roadway faults that alter airflow resistance. The paper proposes using an improved Support Vector Machine (SVM) method to identify the fault location based on changes in air volume detected by wind speed sensors. The approach involves building a sensitivity 0-1 matrix and establishing a roadway fault scope library. The improved SVM method is tested on the Daming coal mine, demonstrating its effectiveness in diagnosing fault locations, reducing training time, and improving accuracy compared to traditional SVM.

Apr 5, 2022

By Nasser Madani, SULTAN ABULKHAIR

The abstract of the paper discusses the challenge of quantifying iron content in a coal deposit in Kazakhstan. The iron dataset is limited, coming from only three drill holes and some stope samples, while a large amount of geological information is available from legacy drill hole data. The paper proposes a workflow using multiple-point geostatistics to model geological domains and two-point geostatistics to model iron content within these domains. The results show that the direct sampling (DeeSse) algorithm effectively reproduces the complex seam layers, and sequential Gaussian simulation models the iron within each domain.

Mar 30, 2022

By Charlotte Abena Benyarku, Albert Buabeng, Eric Stemn

The abstract highlights the increasing use of mobile equipment in mining and its contribution to accidents. The research analyzes injury narratives from Ghanaian surface gold mines to understand the involvement of mobile mining equipment in injuries and explore the use of injury narrative data as a human factors tool. The study identified priority human factor issues, such as operating mobile mining equipment, part removal/installation, and the operator's cabin. The use of Sankey diagrams for multivariable analysis effectively identified specific operator-centered issues that warrant further investigation for improved safety interventions.

Mar 29, 2022

By Jürgen. F. Brune, CLAIRE STREBINGER, ADITYA JUGANDA, Gregory E. Bogin Jr

The abstract highlights the risk of methane gas explosions in underground coal mines and the potential of computational fluid dynamics (CFD) modeling to simulate such events and assess their impact on mine ventilation. The study focuses on developing CFD models for large-scale explosions in longwall mines, specifically simulating methane gas explosions resulting from face ignition during coal cutting. The research demonstrates the integration of a combustion model into a longwall mine ventilation model and shows how the availability of explosive gas mixtures significantly affects flame propagation and explosion pressure.

Mar 27, 2022

By O Otgonbayar, B Bayarmaa, D Batbyamba, S Amar-Amgalan, K H. Natsagdorj, J Nomin-Erdene, B Boldkhuu, T S. Sainzaya

The Argyle deposit in the Kimberley region of Western Australia was the world’s largest accumulation of natural diamonds. Following its discovery in 1979, the mining of associated alluvial diamonds commenced in 1983, followed by the pipe in late 1985. Over the life of the mine to its closure in November 2020, Argyle produced approximately 900 million carats of diamonds. Argyle diamonds are distinctive in having a predominance of brown colours and rare highly-prized pink diamonds, which are a signature of the deposit. The 3D geological model developed from mining and deep drilling shows that Argyle is a composite pipe formed by the coalescence of several steep-sided diatremes, each with their own feeder zones at depth, that were erupted along a NNE-trending fault. The ~1.2 Ga Argyle pipe is comprised of diamondiferous olivine lamproite volcaniclastic rocks and intruded by sparse olivine lamproite dykes. The volcaniclastic rocks are predominantly comprised of unconsolidated quartz-rich lapilli and coarse ash deposits formed by numerous phreatomagmatic eruptions of olivine lamproite magma through Mesoproterozoic water-rich sands and silts. Post-emplacement deformation has tilted the orebody 30° to the north and regional strike-slip faulting has offset, segmented, and elongated the orebody. Recent significant modifications of the geological model resulted from underground block cave operations, producing several critical lessons learnt. Diamond grade and quality reconciliation issues warranted a geological investigation which resulted in the recognition of new volcaniclastic olivine lamproite domains with a broad range of diamond grades, including some very high-grade units. The new lamproite domains had a significant effect on the block cave mining and resultant recovery of diamonds. The new findings enable a more coherent and detailed geological understanding of the volcanic emplacement and paragenetic sequence of the Argyle AK1 pipe. Structural modelling of the deposit also played a major role in the block cave mining tonnage recoveries and daily operations. The re-examination of the geology of the Argyle pipe and the results of this new information reinforces the need for ongoing robust geological work both in the early stages of mining a deposit and continued during the life of the mine.

Mar 22, 2022

By P J. Willems, B J. Junor

Blackwater Mine is in the central-southern Bowen Basin, immediately south of the township of Blackwater on the Capricorn Highway. The current open cut operation extracts coal from three main seams, designated Top, Middle and Lower, in the Late Permian Rangal Coal Measures cropping out on the eastern flank of the Comet Ridge. Complex geological structures, dominated by E-W normal faults and N-S reverse faults, have significant detrimental effects on coal mining operations. Historical exploration before 2010 involved several types of drilling only to understand structure, coal quality and washability. Hence, although drilling data was combined with limited pit mapping and observation, unknown structures were still often encountered during excavations and led to mining surprises. In 2010 BHP completed 200-line km of closely spaced 2D seismic survey to capture gross and detailed structures followed by fit for purpose structural drilling to confirm major structures in the northern part of the mine. In 2018 a high density 9.2 km2 3D seismic survey was completed in the southern part of the mine. Subsequently, a 17.2 km2 survey was completed in 2020 to cover the northern active mining area. It allowed geoscientists to successfully map previously unknown major faults and seam splits, which could potentially impact the mineability of the area. It is important to note, that faults interpreted using modern high-density 3D data can be interpreted with dramatically higher confidence in the fault dip and azimuth orientation in comparison to the legacy 2D data. Along with targeted drilling, pit mapping and structural interpretation, the outcome adds value to mine planning and operations. This paper outlines recent successful seismic 3D data acquisition and interpretation. In detail, the paper presents case studies on how the data can be incorporated into a structural model to improve geological knowledge, enable geotechnical assessment, and support safe and efficient coal mining in a large and structurally complex mine.

Mar 22, 2022