The Effect of Water Pressures on the Stability of Closely Jointed Rock

Provider: ITASCA


The objective of this research work was to establish a numerical modeling approach to compute the distribution of water pressures in a pit slope in low permeability fractured rocks, and the response of water pressure with time to mining.

The failure of a slope necessitates one or more of the following mechanisms: sliding on discontinuities, opening of discontinuities (such as joints) and failure or yield of intact material. The latter mechanism may involve shear yield in a weak material, such as granular material, or brittle failure of stronger material. The main effect of fluid on all these mechanisms involves the pressure exerted by the fluid. Fluid pressure acts to reduce the effective normal stress on a sliding surface, whether it is a joint surface or a shear band within a granular material, thus reducing the available shear resistance. The same concept of effective stress (total stress minus pore pressure) also is believed to apply to fracture initiation in brittle rock. Finally, there is the direct effect of fluid pressure in a crack or joint, acting as a driving force in the direction normal to the joint. A stability calculation based on the mechanisms described above relies on knowledge of the fluid pressure distribution within all elements of the slope.

In this study, all major parameters affecting groundwater flow and pore pressure distribution in the rock slopes were investigated, including: hydraulic conductivity, heterogeneity (including the zone of relaxation) and anisotropy of the hydraulic conductivity, specific yield and specific storage, rock mass properties, and classification, excavation rate, pit geometry, recharge boundaries and their distance from the pit, infiltration rate and discrete fracture network (DFN). It was discovered that the parameters that affect pore pressures in the LOP slopes can be grouped together in few dimensionless parameters that can be used to determine the dominant processes and most efficient modeling approximations.