Automatic Block Modelling Using Locally Adaptive Machine Learning – Dr Alexander Wilson

Speaker: Dr Alexander Wilson, Technical Product Owner – DRIVER, Minerva Intelligence Abstract: Numeric block modelling (interpolation) is a huge part of the Resource Reporting lifecycle of any mineral deposit; however, its rarely used to its true potential. Most projects assay for 30-40 elements, collect mineral percentages, measure density, magnetic susceptibility, RQD, recovery, etc., but they rarely block model all these data attributes. DRIVER was created so that all attributes can be quickly and accurately estimated into block models so they can be used as an invaluable resource for improving ore deposit knowledge. DRIVER's unique technology works to extend block modelling to all data simultaneously, assuming little about the deposit, the AI tools are capable of automatically identifying and locally adapting to many of the complex geological challenges that these natural systems present – including folded and geometrically non-stationary deposits. ________________________________________________________________________ This webinar is part of the Sustainable Minerals Institute's Julius Kruttschnitt Mineral Research Centre (JKMRC) Friday Seminar Series – recorded 4th November 2022). Learn more about the JKMRC Friday Seminar Series: https://smi.uq.edu.au/event/10734/jkmrc-friday-seminars-2022