The behaviour of a rock mass is influenced greatly by the presence and nature of discontinuity networks. A major challenge in rock engineering is the development of a reliable methodology to characterize the quality of a rock mass. Rock mass characterization relies on in-situ observations complemented by field and laboratory testing. Core logging and/or structural mapping often describe the structural regime of a site. At the feasibility stage and in the early stages of mining often the only available rock mechanics information is from core logging, but as greater access to excavations becomes available traditional scanline mapping or some of its variations can be used to update and improve the geomechanical structural model. Mapping, however, can be time-consuming and is often hindered by production activities. An image-analysis methodology for automatic core logging that relies on the use of photographic images is proposed here. The technique utilizes image-processing algorithms to recognize breaks in core. The process is easy to automate and can be easily modified to measure any of the suggested corelogging parameters—Rock Quality Designation (RQD), core recovery, fracture frequency, etc. The methodology can be readily adapted to the needs of most mining operations and, arguably, can provide a more consistent and efficient method of determining the geomechanical properties of core. Applications are presented here that demonstrate the potential and limitations of this evolving technology.
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