Predictive Geometallurgy - SGA Shortcourse


Predictive Geometallurgy - SGA Shortcourse

Tolosana Delgado, R.; Pereira, L.; Frenzel, M.; Da Assuncao Godinho, J. R.; Birtel, S.; de Boever, W.; Dosbaba, M.; Taylor, R.; Gutzmer, J.

Abstract

Geometallurgy aims to optimise the mineral value chain based on a spatially resolved, precise and quantitative understanding of the geology and mineralogy of the ores. Predictive geometallurgy goes beyond this by introducing forecasting models for ore behaviour, and taking into account operational economics and global mineral markets. The course is divided into two main blocks: First, introductory presentations on advanced material characterization as well as current principles and applications of geometallurgy are pre-recorded, and can be watched independently by the audience.
The second part of the course will consist of a live interactive session with time to discuss questions on the talks with the presenters. Its major goal is to enforce the concepts developed in the first part of the course through hands-on exercises using web-based apps. This will allow participants to get a good feel for the data types common in geometallurgical programmes, and how they can be integrated into a geometallurgical model to be used in mine planning, scheduling and mine optimisation.

Keywords: Geometallurgy; 3D particle characterization; geostatistics; particle-based separation modelling

  • Vortrag (Konferenzbeitrag) (Online Präsentation)
    SGA Biennial meeting, 26.-31.03.2022, Rotorua, New Zealand

Permalink: https://www.hzdr.de/publications/Publ-35935