Modelling the influence of heterogeneity on microseismic characteristics in longwall coal mining

Mining-induced microseismicity has been extensively used to evaluate the potential for rock bursts and coal and gas outbursts in underground coal mines. In a research project completed a few years ago, it was observed that characteristics of microseismicity around a longwall working panel were fairly consistent over the monitoring period until a heterogeneous zone with a relatively high coal strength was reached. The current research presented in this paper aims at achieving a better understanding of the effect of heterogeneity on microseismic activity in longwall coal mining. A microseismicity modelling approach which combines deterministic stress and failure analysis together with a stochastic fracture slip evaluation was used to simulate the evolution of microseismicity induced by the progressive face advance passing through a heterogeneous zone. The heterogeneous zone was taken into account by varying the material strength of the elements within the high strength zone and the fracture attributes within this zone. Results have shown that both the high rock strength of coal lithotype and low fracture intensity within this zone contribute to the decrease in seismic event counts, and that the increase in energy released results from the combined effects of increased stress drops and slipped fracture sizes when the high strength zone is approached. on gas emission and outburst tendency. The simulation results have shown that the presence of a low permeability area results in an increased gas pressure gradient with the approaching of the heading, and an increase in the outburst tendency shortly after the passage of the heading; meanwhile, the presence of an enhanced strength region leads to a significant suppression in gas emission when the heading approaches, and a rapid increase in gas emission with the passing of the development heading. The impact of material heterogeneity arisen from geological structures such as faults or shear zones has been investigated by a number of researchers. Lei et al. (2004) conducted triaxial loading experiments on rock samples containing pre-existing joints with various healing strength and asperities, and found that while the failure of homogeneous faults gives no clear early warning signals and is unpredictable, heterogeneous faults fracture after a crack nucleation phase with distinct statistical variation of AE activity parameters. Sainoki and Mitri (2014) used a transversely isotropic, linear elastic model to verify the increase in fault-slip potential as a result of heterogeneity of shear stiffness in the weak zone. Zhao et al. (2014) modelled the response of the rock mass containing a brittle fault zone in TBM excavations, in which the Mohr-Coulomb yield criterion was adopted to evaluate the failure of the fault zone, and interface elements were used to represent the interaction between the fault and the rock mass. Xu et al. (2015) used an equivalent continuum approach to model a cavern excavation near an interlayer shear weakness zone, where the thickness, strength and orientation of the zone were characterised. In a research project completed a few years ago, continuous microseismic monitoring was performed around a working longwall panel at Coal Mine Velenje in Slovenia. During a monitoring period of twelve weeks in 2011, a seismic anomaly characterised by a decrease in event counts and an increase in the average seismic energy released was observed from the eighth week onwards (Si et al., 2015a). This anomaly has been attributed to a xylite-rich zone with relatively high strength in an area dominated by detritic coal (Si et al., 2015a). In a more recent research by the authors, a numerical modelling approach which includes sequential stress analysis and fracture slip evaluation was developed to model the microseismicity generation in longwall coal mining. The modelling approach was then applied to simulate microseismic occurrence and associated energy release prior to the seismic anomaly at Coal Mine Velenje. The model results were compared to field observations in terms of logarithmic event energy and frequency-magnitude distribution of microseismic events. In this study, the modelling approach developed is applied to model seismic characteristics during longwall coal extraction towards a heterogeneous zone inferred from time-lapse seismic tomography. The rock strength of the elements and fracture attributes within the zone are varied, respectively. The induced microseismicity are investigated in terms of event counts and weekly released energy. This model provides a tool to obtain a better understanding of factors influencing mininginduced microseismicity, and lays a foundation for the prediction of rock bursts or coal and gas outbursts using recorded microseismic data. 2. RECORDED MICROSEISMIC EVENTS AND ANALYSIS AT COAL MINE VELENJE Coal Mine Velenje is located on the largest coal deposit in Slovenia. The multi-level mining combined with the longwall top coal mining (LTCC) method is used at Coal Mine Velenje to mine a coal seam which is up to 160 metres thick in the centre of the coalfield (Si et al., 2015a). During LTCC extraction at longwall panel K. -50/C, time-lapse seismic tomography was performed over a 100 m × 141 m area ahead of the advancing longwall face (Si et al., 2015a). Specifically, a total of 40 receiver and 40 source boreholes were placed along the intake and return gateroads with a regular spacing of around 2.5 m. Each receiver was equipped with 3 receiver components, i.e., X-, Yand Z-components, monitoring the P-wave velocities parallel to the gateroad, perpendicular to the gateroad and in the vertical direction, respectively. During the survey, explosives in boreholes were used to generate P-waves, and P-wave velocities were computed and interpolated to produce velocity tomograms for every receiver component. During the first of two campaigns, when the monitored zone was 95 m ahead of the advancing face, a relatively high velocity zone was detected diagonally across the centre of the area, as presented in Fig. 1. This heterogeneous zone is considered to be xylite-dominated coal with a relatively high strength, as compared to less strong detritic coal that also occurs in the coal deposit. The unconfined compressive strength of xylite in the mine is known to be around twice of that for detrite. In order to assess the dynamic behaviour of the coal seam in response to longwall mining, continuous microseismic monitoring measurements were carried out at the same panel during a 12 week period from 23 May to 28 August 2011 (Si et al., 2015a). When the longwall face reached the xylite-rich zone, a decrease in microseismic event counts accompanied by an increase in the average released seismic energy was observed (Fig. 2). Fig. 1. LTCC face K. -50/C P-wave velocity tomograms in Ycomponent for the 1st tomography campaign (after Si et al., 2015a). Fig. 2. Recorded weekly average released energy from microseismic events and event counts against face advance. The analysis of the microseismic data has shown that the bi-weekly frequency-magnitude distribution of recorded microseismic events follows the Gutenberg-Richter relationship, with the b value reflecting the scaling of microseismic event magnitude. In addition, the weekly histogram of the released seismic energy follows a Gaussian distribution, which is characterised by the mean of the distribution μ, and the standard deviation σ. It was observed that these features of microseismic events were quite steady in the first eighth weeks, and deviated after reaching the xylite-rich zone (Fig. 3 & Fig. 4). Considering that microseismic events primarily arise from fracture slippage, the b value for the GutenbergRichter relationship is related to the scaling of fracture sizes in the coal seam. Similarly, the fitted mean value  and standard deviation  of the Gaussian distribution are associated with the fracture sizes and size distribution, respectively. In view of the consistency in ,  and the b values during the first eight weeks, it was assumed that the fracture sizes and size distribution within the coal panel were consistent over this period. The deviations in the b,and  values, event counts and average energy release when approaching the xylite-rich zone suggest that, except for rock strength, the fractures within the xylite-rich zone differ from those in the coal seam. Based on the modelling work of triaxial loadings to fractured rock mass embedded with DFN following a power law size distribution using a coupled DEM-DFN model, samples with lower fracture intensity has higher rock strength and elastic modulus, and samples with lower fracture size distribution exponent a tend to have greater rock strength (Harthong et al., 2012). In this respect, it is deduced that fractures within the xylite-rich zone have lower intensity and power-law exponent a related to the size distribution. Fig. 3. Calculated b values for frequency-magnitude distribution of microseismic events recorded during two consecutive production weeks. Fig. 4. Fitted Gaussian distribution parameters to the logarithmic event energy during each production week. 3. MODELLING METHODOLOGY In this study, a numerical approach which considers fracture slippage based on the stress and failure state of the model is applied to generate microseismicity in longwall coal mining. Salamon (1993) and Board (1994) were the first to implement fractures along which slip can take place to form a microseismic event in elastic models. The authors of this paper developed their model in FLAC3D and incorporated a strain-softening constitutive model to describe the post-failure behaviour of the rock mass realistically. The modelling is carried out by referring to the following procedure: (1) Model construction and fracture implementation. A model is first established in FLAC3D to represent the longwall panel layout and surrounding strata. Mechanical and strength