Predictive Geometallurgy- State of the Art


Predictive Geometallurgy- State of the Art

Birtel, S.; Büttner, P.; Frenzel, M.; Bachmann, K.; Tolosana Delgado, R.; Gutzmer, J.

The 45 minutes talk gives a brief overview of the approach of the Helmholtz Institute Freiberg for Resource Technology, followed by an introduction into Geometallurgy, Predictive Geometallurgy respectively. From the analytical perspective there will be a focus on SEM based automated image analysis. This data is the basis for further data processing, statistical assesment and interpretations. Depending on data availability, operational stage (exploration extraction) different levels of geometallurgical models can be created. This will be illustrated in case studies, showing the work flow and result for the development of 1) 3D resource potential model of a historic tailings dam to recover Sn, 2) Methodology for mineralogical deportment prediction of In as a by- product from complex ore types, 3) 3D first order geomet model of a primary deposit to recover PGE as by product

Keywords: Geometallurgy; predictive geometallurgical model; SEM based automated mineralogy; data analysis

  • Invited lecture (Conferences)
    InRec Stakeholder Meeting (Geometallurgy applied to industrial Mineral operations), 24.-25.04.2019, Trondheim, Norway

Permalink: https://www.hzdr.de/publications/Publ-29120
Publ.-Id: 29120