An approach to model seismicity induced by mining was proposed by MDG Salamon and developed further by AM Linkov. We suggest a variation of the Salamon-Linkov method that does not require a priori assumptions about sizes, orientations and locations of flaws, reducing the amount of input data. The algorithm places a 3D grid over the model domain and searches the entire grid space for possible planes of failure by identifying lobes of positive Coulomb Failure Stress (CFS). The largest CFS lobes are then utilised as flaws. Another change from the original formulation is that the flaws are discretised into smaller sub flaws. This accounts for the complexity of the shapes of the flaws and provides more accurate modelling of their effect on the stress field. Some elements of the original framework of Salamon and Linkov, e.g. tensile failure and creep effects are not included into our implementation. This is done intentionally to keep the method simple at the current stage. The implemented method requires limited input data: models of mining steps, information about virgin stress, rock mass elastic properties and strength. The strength may be anisotropic and inhomogeneous, where specific Mohr-Coulomb failure criteria can be assigned to particular orientations (describing joint sets) and 3D surfaces (describing faults or dykes). The output of the method represents two catalogues-one for seismic and another for aseismic events. The catalogues contain origin times (mining steps), coordinates, seismic potencies and source mechanisms of events. The method was applied to real case studies at two mines. The Boundary Element Method (BEM) models of the mines were of the order of 200,000 Fictitious Force (FF) elements. The first model included seven mining steps and the second model consisted of 33 steps. The computations took seven and 50 hours respectively on a multi-core machine. In the first case the resulting catalogue includes more than 900 seismic events, whereas in the second case the catalogues contained approximately 3,400 seismic and 100 aseismic events. The modelled seismicity may be used as a reference for the interpretation of the observed seismicity. Analysing the discrepancies between the modelled and observed seismicity can also help to assess the validity of input parameters-characteristics of in situ stress and failure criteria. Another possible application of the suggested method is the testing of future mining scenarios. Although the prediction of seismic response for individual scenarios may be not accurate, the difference between the modelled seismicity of the scenarios may help to choose the optimal one in regards to seismic or ground motion hazard.
Rapid assessment of areas that may experience damage during large seismic events is an important task of seismic monitoring in rockburst-prone mines, particularly in the seconds to hours following the event. Correctly installed sensors of the appropriate type allow instantaneous and accurate measurement at the location of the sensor. However, the ground motion at any point in the mine could be of interest. Traditionally, this assessment at locations away from sensors was estimated using ground motion prediction equations (GMPEs); specially calibrated equations describing the relationship between ground motion, event strength (radiated seismic energy or seismic potency) and distance. However, the uncertainty in these equations is often quite significant due to complexity of the problem, e.g. radiation pattern effects, extended seismic sources, variations in attenuation characteristics, and uncertainty in source parameters. We improve the accuracy of these estimations by combining the measurements at sensors with a GMPE in an approach known as ShakeMap, popular in crustal seismology. This allows for rapid and more accurate estimation of ground motions at any location following a large event. This knowledge can play an important role in planning of potential post-event evacuation operations and damage assessments. The method is demonstrated on examples from an Australian sublevel caving mine.
Seismic risk management at mining operations is predominately reliant on analysis and interpretation by ground control engineers, who must also manage all other mine site geotechnical hazards. Seismic systems run in real time collecting seismic parameters. However, the analysis, interpretation and resultant actions can be intermittent depending on available resources. Stress-induced seismicity during cave initiation and propagation is a constantly evolving hazard that requires a high level of continuous monitoring and examination. The authors have assisted in the development of integrated seismic monitoring and trigger response software applications within the Ticker3D seismic visualiser and analysis application, developed by the Institute of Mine Seismology (IMS). The benefits of the integrated applications include real-time monitoring of key seismic parameters and automatic trigger response, aiming to reduce workforce exposure to hazardous seismic conditions. Using measured ground motion as a monitoring input enables an almost immediate trigger response to a threshold breach via the Mine Control Trigger Response System. The continuity in seismic data interpretation and triggered mitigation controls are also recognised advantages to the applications.
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