Seismicity in the mining environment is controlled by factors including stope and development blasting, the presence of geological features, and stress conditions. The Goldcorp Eleonore mine is located in the James Bay region, Quebec, Canada. It’s 800-metre depth makes Eleonore a relatively shallow mine when compared to other seismically active Canadian mines. Despite the mine’s depth, seismicity is a geotechnical hazard that may be arguably attributed to a particular stress regime and complex geology. An improved understanding of the seismic responses following blasting can decrease seismic risk and is beneficial to mine planning and productivity. Seismic responses to blasting were spatially delineated using a density-based clustering approach. The spatial characteristics of clusters were assessed using Principal Component Analysis (PCA). The best-fit planar representation of seismic event clusters was identified. The orientation of the best-fit planar representations was then compared to the mine’s local jointing to investigate the causative seismic source mechanism for these events. The results of this study show that seismicity is linked to local jointing, and in particular to the different structural domains.
Blasting is a significant factor in triggering seismic events at mine sites (Vallejos and McKinnon, 2008). Seismicity is defined as a stress wave resulting from inelastic deformation or failure in the rock mass (Hudyma and Mikula, 2002). Seismicity in the mining environment is controlled by factors including stress, geological structures or rock mass weakness, and mining activities. This induced seismicity—directly connected to mining operations—is associated with formations of fractures at stope faces and with movement on major discontinuities (Gibowiicz and Kijko, 1994). Fig. 1 illustrates the different source mechanisms of induced seismicity in an underground mine environment (Hudyma et al., 2003). Many authors have observed that well-located seismic events exhibit strong spatial clustering (Leslie and Vezina, 2001; Dogde and Sprenke, 1992; Kijko et al., 1993). Hudyma and Mikula (2002) hypothesized that clusters of seismic events represent a separate seismic source mechanism. Limited quantitative means of assessing a seismic source mechanism have been presented in the scientific literature especially in the case of clusters of seismic events. A better understanding of induced seismicity source mechanisms in underground mining can help to optimize mining operations, reduce delays and production losses. Understanding the main source mechanism in mines is essential to a better prediction of the rock mass response to mining.
Duchesne, Mathieu J. (Geological Survey of Canada) | Brake, Virginia I. (Geological Survey of Canada) | Hu, Kezhen (Geological Survey of Canada) | Giroux, Bernard (INRS-ETE) | Walker, Emilie (Laval University)
In many civil or mining engineering works, the stresses and deformations of natural or excavated slopes due to the combined effect of self-weight and initial stresses are of interest. Because of the mathematical complexities of this problem, however, no complete exact solution exists for the simplest case, that of assuming the stress-strain relation of the rock to be perfectly elastic.
Efforts have therefore been directed toward numerical and experimental technique. The stresses within an elastics lope have been obtained by LaRochelie,1 using the photoelastic and finite difference method to determine the difference and sum of principal stresses. Subsequently, Finn,2 Hoyaux and Ladanyi,3 and Duncan and Dunlop4 attempted to solve the same problem by using the finite element method. The problem was also investigated by Brown and Goodman5 and Brown and King6 who emphasize the importance of the effect of loading or unloading procedure on the stress distribution within the slope.
Although the geometry of the slope and the boundary conditions involved are identical or similar, the results obtained by these various authors by no means agree. It is therefore necessary to review briefly the results of elastic analysis in order to lend credence to the methods used in the solution.
Although the stress-strain behavior of some rocks may be reasonably approximated by the elastic model, other rocks generally exhibit an elasto-plastic behavior with strain hardening or strain softening as shown in Fig. 1. Experiments show that for most rocks, the stress-strain relationship is approximately linear from the origin to the point P (neglecting the small concave region under low stresses). At P, the curve deviates (Fig. 1--Stress-strain relations of rook (Available in full paper)), from linearity and yielding starts to occur. Beyond P, the stress may either increase with strain as shown by curve PA (strain hardening) or decrease with strain (strain softening) after a peak stress is reached as shown by curve PB. The actual behavior depends on the type of rock and the confining pressure. For a given type of rock, an increase in confining pressure gradually transforms strain-softening behavior into strain hardening behavior. As a first step toward this more realistic solution,the stress-strain relationship is assumed to be elastic, perfectly plastic for the determination of the stresses and deformations in a vertical slope of soft rock.
Two methods of solution were used in this paper, the lumped parameter Model7 and the finite element method, so that the results and their effectiveness may be compared and large errors arising from computational techniques may be detected.
Complete solutions of stresses and displacements within elastic slopes of several inclinations have been obtained by LaRochelie.<,sup>1 The principal stress difference was determined by using a gelatin model with Young's modulus E-2.5 psi and Poisson's ratio µ-0.5. The sum of the principal stresses was computed by finite difference solution of the Laplace equation. The normalized maximum shear stresses 4max/¿H, where ¿ is the density of the material and H is the height of the vertical slope, are plotted in Fig. 2.