Geometallurgy From Exploration to Remediation

Overview

Environmental and socio-economic demands in the exploitation of future mineral resources require a comprehensive collection and evaluation of mineralogical, geochemical, lithological and physical attributes, and, metallurgical properties about ore bodies along with their inherent variability. This process must be initiated from the early stages of exploration to processing of the ore and remediation of the mine waste because such information has a direct impact on all aspects of development. Geometallurgy is the scientific discipline that integrates all of the mineralogical, geological, mining and processing data into an accurate ore body model that forms the basis for optimization of production and environmental management during the entire life of the project, thereby reducing operational risks, optimizing recovery efficiency, and minimizing environmental impact within the framework of a sound financial model.  With the recent trend to digital transformation sweeping the industry, entailing widespread application of automation and software on a desire to increase value creation in the mining process, it becomes even more important that this is based on a sound geometallurgical model that captures the variability within the ore body. The aim of this course is to present the implementation of quantitative mineralogical and metallurgical data (grinding, mineral processing) in ore processing and geometallurgical models and their application in actual mine situations.

Course Content

1. WHAT IS GEOMETALLURGY 

2. SAMPLE SELECTION FOR METALLURGICAL TESTING

3. ORE CHARACTERIZATION

  3a. MINERALOGICAL METHODS

  3b. PROCESS MINERALOGY CASE STUDIES

  3c. HARDNESS & OTHER METALLURGICAL TESTS

4. GEOMETALLURGICAL MODELING & CASE STUDIES

5. STOCHASTIC MODELLING

Instructors

Hugh de Souza, Director, Technical Services SGS Minerals, Lakefield, Ontario

In this role Hugh provides technical advice on geochemical, mineralogical and other SGS services applied in exploration and mining. In addition, he is involved in implementation of new mineralogical and geochemical technologies in mineral exploration. Prior to that he managed SGS geochemical, mineralogical and diamond labs over the last 20 years. He holds a BA Honours in Environmental Sciences (Lancaster), MSc in Geochemistry (Leeds) & PhD in Isotope Geology (Edinburgh).

Tassos Grammatikopoulos, Senior Geoscientist SGS Minerals

Tassos has over 25 years experience in the minerals industry much of it in the application of process mineralogy in metallurgical programs. He has been with SGS Lakefield Research as a senior mineralogist / geoscientist since 1997 and is responsible for interfacing with metallurgists and geologists in support of flow sheet development and design, and integration of data for a wide range of metals and commodities.  He has a B.Sc. from University of Patras, Greece , a M.Sc. from Acadia University, NS, and a PhD from Queen’s University, ON in Mineralogy/Economic Geology. He is currently also an Adjunct Professor in the Department of Mining and Materials Engineering at McGill University. 

David Hatton, Geometallurgy Group Manager, SGS Minerals

David is a Metallurgist with a specialty in Mathematical modelling. He completed an honours degree in Industrial Mathematics before beginning a PhD in flotation circuit modelling at the University of Cape Town, South Africa. He has more than 15 years experience in the industry and has led site process surveys on all 6 continents.  David worked for JKTech in Australia as a flotation specialist before joining SGS in the Geomet group. He has experience in site surveying and modelling of Copper, Zinc, Nickel, Platinum, Gold, and Lead flotation circuits. In 2018 David took over as manager of the Geomet group. David has a strong Mathematical background. He has developed many of the fundamental equations and algorithms in SGS’s in house Geometallurgical simulation software IGS. These include process optimization methodologies, economic models as well as risk quantification through Monte Carlo analysis. David is fluent in English and Afrikaans.