Automated Core Logging Technology for Geotechnical Assessment: A Study on Core from the Cadia East Porphyry Deposit

作者: Cassady L. Harraden , Matthew J. Cracknell , James Lett , Ron F. Berry , Ronell Carey

DOI: 10.5382/ECONGEO.4649

关键词: Ground supportRock mass ratingCore recovery parametersDrillHyperspectral imagingGeologyData collectionGeotechnical engineeringVolcanic rockLogging

摘要: The Cadia East porphyry deposit, located approximately 20 km south of Orange, New South Wales, Australia, contains a significant resource copper and gold. This is hosted within the Forest Reefs Volcanics spatially temporally associated with Intrusive Complex. To extract ore, underground mine currently uses block cave mining method. geotechnical model provides data inputs into range numerical empirical analysis methods that make up foundation for design. These provide input construction stress models, caveability ground support design, fragmentation analysis. encompasses two commonly used rock classification systems quantify conditions: (1) mass rating (RMR) (2) tunneling quality index (Q index). RMR Q are calculated from estimates designation (RQD), number fracture sets, roughness, alteration, spacing. Geologists engineers collect information to produce these by manually logging sections drill core, time-consuming task can result in inconsistent data. Modern automated core scanning technologies offer opportunities rapidly larger samples core. generate large volumes spectrally consistent data, including surface laser profiling system. Core models detailed measurements location, orientation, roughness oriented combined other morphological mineralogical outputs hyperspectral estimate systematically over contiguous intervals. goal this study was develop proof-of-concept methodology extracts parameters topographic collected Hyperspectral were case assess methods. results show both contribute be extracted approach an opportunity capture geologic, mineralogical, at scale too achieve via manual collection.

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