Geotechnical Domaining for the Aktogay Porphyry Deposit supported by Machine Learning Techniques
Event - Tucson, USAPorphyry geological systems are typically challenging to quanitify through the geotechnical characterization process. The scale of many modern prophyry deposits, and associated rock mass heterogeneity requires a large characterization dataset from which the geotechnical domaining can be done. The presented case study demonstrates a rigourious workflow supported by Machine Learning (ML) to geotechnically characterize a copper porphyry deposit located in Central Asia. The operation comprises two a
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