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Over the last decade, the advantages of discrete fracture network (DFN) models over more conventional tools for key block stability analysis have become increasingly apparent. Without their need for a series of simplifying assumptions regarding the fracture system, rock wedge formation and excavation geometry, DFN's ability to accurately capture the underground rock mass is clear. Coupled with the probabilistic consideration of block formation and joint strength parameters, they provide a valuable tool to the engineer for risk-based underground stability assessments. However, recent changes in DFN technology have allowed a step change in modelling realism to be incorporated. A major improvement is the ability to generate DFN models directly conditioned to photogrammetric surveys so that the kinematic assessment is carried out on a structural description that accurately reflects the scanned location. This conditioned DFN model is embedded within an unconditioned stochastic description of the rock mass away from the scanned rock mass exposure, thus, providing a model that is constrained by the available geotechnical data (boreholes, scanning, trace mapping) but accurately conditioned to the key observed structures. The result is an ability to optimise excavation and ground support designs with a method that intelligently handles the natural heterogeneity imposed by the rock mass, combining what we see with what we know.

Two different pre-conditioning techniques have been applied at the Sur Andes mine sector (SuaPi) of the El Teniente mine in order to improve caving performance of the primary copper ore, which can be considered as a typical heavily veined massive, competent and unfractured rock masses. Hydraulic fracturing (HF) and blasting under confined conditions (BUCC) have been applied to a significant portion of the ore column to be mined. Both techniques introduce new open fractures into the massive rock mass with the aim of improving fragmentation performance at the draw points. A range of rock mass characterisation activities were undertaken before and after pre-conditioning took place in order to evaluate any change in rock mass condition. These geotechnical campaigns included both drill core logging and borehole camera (BHC) inspection and mapping. Mapping of the borehole walls allow the identification of the massive rock mass including the healed veins, the sub-horizontal HF fractures and also the sub-vertical (both radial and concentric to the blast hole) BUCC fractures. Using these rock mass characterisation properties, a Discrete Fracture Network (DFN) model was developed for both HF and BUCC fractures in order to quantify the occurrence of new open fractures within the primary ore. The DFN models allow the estimation of in situ fragmentation following preconditioning and these data were compared with fragmentation performance measured at the draw points in the SuaPi mine Sector. This paper presents the results of the pre-conditioning on the rock mass, the DFN modelling procedure undertaken (particularly the BUCC fractures), the characterisation of the preconditioning intensity and how it is related to the fragmentation performance at the SuaPi mine sector.

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