His areas of expertise include the estimation, simulation, validation and classification of mineral resources using standard and advanced geostatistical methods. David's experience also includes the application of conditional simulations for mineral resources classification, drill hole spacing optimization and the characterization of geological and multivariate grade uncertainty and risk. He has drafted geostatistical and mineral resource technical documents in English, Spanish and French, including the mineral resource estimation chapters of various NI43-101 and JORC compliant technical reports. Commodities within David’s expertise include base metals, precious metals, and, more recently, iron, phosphate and coal.
Prior to Joining SRK, David led multidisciplinary groups in the implementation of 3D modelling technologies for mineral resources estimation and grade control. Later, he conducted advanced research in Geostatistics at the University of Alberta, during his Mining Engineering doctoral studies, and at the Stochastic Mine Planning Laboratory of McGill University, as an associate researcher.
David keeps active research partnerships with the academia in Canada and the United States of America and has published over 19 papers in peer-reviewed journals and conference proceedings. He has taught basic and advanced Geostatistics courses in English, Spanish, and French for universities and the industry in Canada, Russia, Morocco, and Latin America. He uses his programming skills in FORTRAN, C++, Datamine Macro Language and Python to develop customized geostatistical and mineral resources applications and workflows.
