3D morphology and machine learning chemistry of indicator minerals: new insights for mineral exploration
François-Xavier Masson currectly at ISTO will present us his research on news insights for mineral exploration from machine learning.
Abstract
Mineralization in bedrock is frequently covered by Quaternary sediments. Morphology and chemistry of indicator minerals are common techniques applied in mineral exploration to target the source of deposits. This seminar aims to present exploration techniques such as 3D morphology quantification applied to gold grains to estimate the distance of transport and the use of magnetite chemistry combined with machine learning to classify deposit types and identify the source.