David joined the team in February 2009 as a specialist Mathematical Analyst. David obtained a BSc with Honours at the University of Queensland, achieving First Class Honours and being awarded a University Medal. On completing this degree, he undertook a Master of Philosophy degree in Physics.

At Geovariances, he has led or been a part of geostatistical consulting studies with linear and nonlinear geostatistics (Kriging, Uniform Conditioning, Conditional Simulation, drill-hole spacing analysis) in a range of commodities, including gold, iron ore, lateritic nickel, and coal. He has run many training courses in both geostatistical theory and the use of Geovariances software and has lectured the Geostatistics course at the University of Queensland. David is also active in software development and testing for Isatis.neo.

Claire Faucheux joined Geovariances in 2010 as an engineering consultant applying geostatistics to environmental fields. After graduating with a diploma of Ingénieur Agronome (equivalent to MSc.) from the Ecole Nationale Supérieure d’Agronomie de Rennes, she gained experience in sampling for water quality assessment at IRSTEA as well as in geostatistics for soil pollution and air quality at MinesParisTech.

Her geostatistical and statistical expertise allows her to conduct exploratory data analysis, sampling optimization, geostatistical estimations and simulations to build cartography, quantify uncertainties and delineate contaminated surfaces and volumes. Claire mainly applies these techniques to soil contamination and air quality while responding to client-centered needs. Her scientific software skills include Isatis, Kartotrak, and R.

As part of our experienced training team, Claire can offer her expertise in English and French.

Pedram Masoudi joined Geovariances in 2019 as a consultant and trainer following his postdoctoral project on the geostatistical characterization of contaminated soil by Cs-137. With his expertise in Isatis.neo geostatistical software and Python programming language, he is interested in developing and testing new methods and algorithms for integrating and interpreting geophysical and geological data. Pedram has a wide range of skills, including mineral resource estimation compliant with the JORC standards, petroleum reservoir characterization involving time-depth conversion and petrophysics, facies modeling, and geotechnical studies related to liquefaction (CPT, SPT, and EM). He also specializes in cartography of contaminated soil with a focus on radioprotection.

Roberto holds a Mining Engineer Bachelor’s degree from the School of Mines of the Federal University of Ouro Preto (UFOP) and a Master’s and a Ph.D. degree in geostatistics from the Federal University Rio Grande do Sul (UFRGS). His expertise is in implicit geological modeling, uncertainty assessment in geological models, ore grades estimation, and simulation workflows according to the international mineral reporting codes. He is also strongly proficient in Python and machine-learning techniques applied to geosciences. Along with his career as a geostatistician, he has developed custom geostatistical and machine learning-based solutions and Python codes for the mining industry. He currently works as a mineral resources consultant at Geovariances Latin America.