Geometallurgy Conference 2023

Programme

The preliminary programme can be downloaded here.

Conference Themes

• Sampling and core logging
• Practical tools and methodologies for ore characterization and testing
• Geostatistics, data integration and modelling 
• Incorporation of predictive mining, processing, and environmental models into the resource model
• Strategic and operational geometallurgy 
• Case studies 
• Sustainability

Call for Papers and Key Dates

Prospective authors are invited to submit abstracts for this conference. Abstracts should be in English, word documents, not more than 500 words (ideally between 200-300 words). Abstracts should have a title and the details of the author. Please email abstracts and requests to be added to the conference mailing list to Gugu Charlie: Conference Co-ordinator, SAIMM at gugu@saimm.co.za

KEY DATES 

• 28 April 2023 – Submission of abstracts deadline 
• 7 June 2023 – Submission of papers deadline 
• 4 September 2023 – Technical Workshop 
• 5-6 September 2023 – Conference 
• 7 September 2023 – Technical Visit

Keynote Speakers

Glen Nwaila
Director of the Wits Mining Institute and Adjunct Professor at the School of Geosciences, University of the Witwatersrand, South Africa

Glen Nwaila is the Director of the Wits Mining Institute and Adjunct Professor at the School of Geosciences, University of the Witwatersrand (Wits). Prior to joining Wits in 2017, he worked in the mining and consulting industries for 12 years, where he led teams of mining professionals and audits in mineral resources management and extractive metallurg. In mining, Glen led the geology functions for various companies. He also served as Manager at Deloitte Technical Mining Advisory DIvision. Glen has been an Erasmus Mundus Scholar at Uppsala University since 2018. He completed his PhD with Magna Cum Laude at the Würzburg University in Germany, MSc Chemical Engineering from the University of Cape Town and holds a Geology Honours degree from the University of Johannesburg. Glen is a Professional Natural Scientist with the South African Council for Natural Scientific Professions  (SACNASP) and is a Fellow of the Geological Society of South Africa (FGSSA). Glen and his students work on geometallurgy, machine learning, and spatial data analytics research projects related to multiscale and multivariate data integration to enable optimal decision-making in the presence of uncertainty.

Dr. Jared Deutsch,
President, Resource Modeling Solutions Ltd., Canada

Dr. Deutsch leads Resource Modeling Solutions and directs geometallurgical modeling projects. Dr. Deutsch has experience in mineral resource estimation and geometallurgical modeling for complex hard rock deposits. He specializes in integrating metallurgical data with machine learning into mineral resource models for better process predictions and increased mine value. He holds advanced degrees in both extractive metallurgy and geostatistics. Prior to joining Resource Modeling Solutions, he was a geometallurgist and geostatistician on the Carlin Trend at Newmont. Dr. Deutsch is the founder and editor of Geostatistics Lessons providing guidance on the application of geostatistics.

Kathy Ehrig 
BHP, Australia

Kathy completed a PhD in Geology from the University of California-Berkeley in 1991 and left San Francisco in 1992 to join the former WMC as a research geologist to work on the genesis of the Olympic Dam deposit, and to provide mineralogical support to the metallurgy department. In 2006, she moved to Adelaide to lead the development of the world's largest and most comprehensive geometallurgy program as Principal Geometallurgist for BHP. In 2017, she received a Professional Excellence Award from the AusIMM and Doctor of Science honoris causa from Flinders University in recognition of her contribution to the geological and geometallurgical understanding of the Olympic Dam deposit. In 2020 the Australian Geoscience Council (AGC)  announced Kathy as the inaugural winner of the Roy Woodall medal for her work in documenting the geology and mineralogy of the Olympic Dam deposit, and she was also awarded the Society of Economic Geologists Silver Medal for the detailed and ground‐breaking work with respect to geology and metallurgy at the world-class Olympic Dam deposit, leading the development of geometallurgy as a discipline. In 2022 the Australian Academy of Science awarded Kathy the Haddon Forrester King Medal and Lecture (Career award) in recognition for her insights and research leadership into the complex geological events involved in the formation of the supergiant copper-uranium-gold-silver ore deposit at BHP's Olympic Dam mine. In 2023, Kathy was elected to the US National Academy of Engineering. Kathy has delivered more than 65 presentations at conferences around the globe on the Olympic Dam orebody, and the science of geometallurgy more broadly.

Lidia Auret
Senior Process Data Scientist, Stone Three

Lidia Auret is a senior process data scientist (research and training focus) at Stone Three and holds extraordinary/honorary associate professor positions at the Chemical Engineering departments of Stellenbosch University and University of Cape Town. Lidia obtained her PhD in 2010 (Stellenbosch University) on random forests for process monitoring. She served as lecturer and senior lecturer at Process Engineering (SU) from 2012 to 2018 – specializing in dynamic modelling, process control and statistical analysis. From 2019, she has served various roles at Stone Three – an Industrial Internet-of-Things machine vision sensor and data analytics provider to the mining industry. These roles included profit-and-loss manager for the process monitoring business unit and product manager for process monitoring services. Her research interests include data analytics and machine learning for process monitoring in industrial processes. Lidia has authored 40 peer-reviewed publications and supervised 3 PhD and 23 Masters students. She is a member of the Southern African Institute of Mining and Metallurgy and an executive committee member of the South African Council for Automation and Control.

Professor Aubrey N Mainza,
Department of Chemical Engineering, University of Cape Town

Aubrey Mainza is a Professor and Head of the Department of Chemical Engineering at the University of Cape Town (UCT) in South Africa. He is a Deputy Director and Head of Comminution and Classification Research in the Centre for Minerals Research He has 23 years of collective experience in academia, research, and industry. His area of expertise is in comminution and classification and uses Discrete Element Method (DEM), Computational Fluid Dynamics (CFD), and Positron Emission Particle Tracking (PEPT) as tools in his modelling methods. He has participated in many local and international research projects and has worked on numerous comminution circuit design and optimisation projects in various parts of the world. Aubrey has published widely in the international mineral processing journals and aligned disciplines literature. He has supervised many postgraduate students to graduation some of whom hold high positions in industry and is still an active supervisor of postgraduate students. He has held the position of Chairman for the Global Comminution Collaborative (GCC) and chairperson for the International Comminution Researchers Association (ICRA) African Chapter and chairperson for the Western Cape Branch of the Southern Africa Institute of Mining and Metallurgy (SAIMM) and is currently a committee member of all these associations. Aubrey is on many advisory committees for international conferences such as the European Symposium on Comminution and Classification and is a consultant for the Minerals Engineering International Comminution Conference.

Registration Fees

*The early bird registration is valid until  4 June 2023

Registration Process

For detailed instructions about the event registration process, please download the PDF helpfile...

CPD

ECSA and SACNASP CPD points will be allocated to all attending delegates

Sponsorship & Exhibition

There are various sponsorship and exhibition packages available for this conference to help you increase your brand visibility and also gain direct access to your ideal customers

Download a detailed sponsorship prospectus or contact the Conference Coordinator
Gugu Charlie
Tel: 27 11 538 0238
Email: gugu@saimm.co.za

Venue and Accommodation

Stretched across the Bottelary Hills in the Stellenbosch winelands, just 30 minutes from Cape Town, Hazendal wine estate is a world-class destination offering culture, cuisine, golf and entertainment for the entire family.

The Vine Guest House
www.vineguesthouse.co.za
7 minutes' drive
info@vineguesthouse.co.za
12 Rooms
+27 21 865 2233

Devonvale Golf Estate
www.devonvaleestate.co.za
7 minutes' drive
info@devonvale.co.za
Up to 40 Rooms
+27 21 865 2080

Devon Valley Hotel
www.devonvalleyhotel.com
12 minutes' drive
reservations@devonvalleyhotel.com
Up to 40 Rooms'
+27 21 865 2012

The Jewel 5* B&B
www.thejewelcpt.com
20 minutes' drive
jewel@slabproperty.co
7 Five-Star Suites
+27 21 007 3794

Kunjani Wines
www.kunjaniwines.co.za
10 minutes' drive
info@kunjaniwines.co.za
4 Villas'
+27 74 116 9029

Technical Workshop

Monday, 4 September 2023
This workshop is limited to 40 delegates

Machine Learning for Geometallurgical Modeling

Practical Techniques and Applications

Typical geometallurgical data is massively multivariate with complex relationships and sparse sampling. These features pose challenges for traditional regression and geostatistical modeling approaches when predicting and scaling the spatial distributions of rock and metallurgical properties. This workshop will address machine learning techniques that can be applied to manage nonadditive and unequally sampled geometallurgical measurements with limited data.

Workshop Overview

The emphasis of the workshop is on practical techniques for options to regress metallurgical attributes and integrate the machine learned models into traditional resource models. Topics covered will include:

• Common challenges associated with geometallurgical data
• Data preprocessing strategies for managing multiple data scales, uneven sampling, and compositional constraints that occur in metallurgical, geochemical, and geotechnical sources of information
• Multilinear regression and metrics to quantify model effectiveness
• Model assessment with resampling strategies (K-fold validation) and noise robustness
• Nonparametric regression with random forest, stochastic gradient boosting, and deep neural networks for integrating multiple data sources
• Combining the machine learning preprocessing, regression, and validation strategies for generating a spatial model of geometallurgical properties using geostatistical techniques

Coverage of these topics will include a brief overview of theory, and hands on demonstrations of strategies that can be applied to common geometallurgical challenges. Geometallurgical training data will be provided to participants, and access to software with worked exercises, so that participants can experiment with the presented strategies.

Presented By

This workshop will be presented by Dr. Jared Deutsch of Resource Modeling Solutions Ltd. Jared has experience in mineral resource estimation and geometallurgical modeling for complex hard rock deposits, holding advanced degrees in both extractive metallurgy and geostatistics. He specializes with integration of metallurgical data with machine learning into mineral resource models for better process predictions and increased mine value.

Resource Modeling Solutions is an Alberta, Canada based company providing consulting services and software in support of the mining and petroleum industries. Resource Modeling Solutions publishes RMSP, a high performance geostatistical modeling software for building auditable resource modeling workflows and quantifying resource uncertainty. More information on Resource Modeling Solutions and the workshop presenter is available at https://resourcemodelingsolutions.com/

Registration Fee: ZAR4 500

Workshop Sponsored by:

Post Conference Technical Visit

The post conference technical visit is limited to 15 delegates.

Thursday, 7 September 2023
08:00   - Departure (delegates to meet at the Main reception of the Hazendal Wine Estate)
09:00     - Arrival at Stone Three main office 
              - Introductions
              - Stone Three technology and services overview presentation
              - SmartROC (remote operations center) tour

12:00     - Lunch

12:30     - Depart to smart sensor production facility

              - Smart sensor technology demonstration

              - Smart sensor production facility tour

15:00     - End of site visit

About Stone Three

We combine expert services with the power of machine learning to help our customers increase their productivity, and keep their people safer, happier, and healthier.

Stone Three is a leading expert in the field of smart sensing solutions, industrial data science and advanced process control. With more than 800 active smart sensor systems implemented or projects in progress, our systems and services have contributed significantly to throughput and metal recovery improvement initiatives of our clients. Leading with services, and harnessing technology, we work with an ecosystem of partners to integrate complementary technical solutions that deliver insights and control solutions that achieve operational improvement objectives.  Our extensive experience enables pointed advisories from our solution consulting team, early and throughout a mineral processing site’s lifecycle.

Moreover, Stone Three’s SmartROC™ remote operations center is well positioned to provide continued services to sites during and after the delivery phase of a project, ensuring the availability of domain expertise to support operations with data analytics and predictive insights. Our mission is to provide real time productivity support, with outcomes based operational advisories and advanced automation where practical.

Registration Fee: ZAR700

CONTACT

FOR FURTHER INFORMATION, CONTACT:
Conference Coordinator, Gugu Charlie.
Tel: 27 11 538 0238
Email: gugu@saimm.co.za