Instructors: Marcelo Godoy, Newmont Mining Corporation, USA; Roussos Dimitrakopoulos, McGill University, Canada; and Guy Desharnais, SGS Canada Inc., Canada
Content and Objectives
This course is designed according to the latest regulations on public reporting of Mineral Resources. It aims at showing how state-of-the-art statistical and geostatistical techniques help answering the requirements of those regulations in an objective and reproducible manner. A particular emphasis is put on understanding sampling and estimation errors and how to assign levels estimation confidence through the application of resource classification fundamentals. In addition to a solid introduction to mining geostatistics this course provides a comprehensive overview of industry’s best practices in the broader field of Mineral Resource estimation.
Attendees will learn:
• How to use statistical inference to identify problems with the data
• How to produce models that address the needs of mining companies
• Compliance with NI43-101, SEC Industry Guide 7 and JORC
• Effective workflows from data preparation to resource classification
• How to validate, reconcile and communicate resource estimation results
• The fundamentals of resource classification and how to apply them in practice
• How to produce auditable and reproducible resource estimates
• Estimation of grade control models and best practices in ore selection
• How to leverage costly geometallurgical testing to reduce risk
• How to use conditional simulations to quantify uncertainty in resource estimates
• How to integrate orebody simulations into mine planning
To register or for more information please contact:
Deborah Frankland
Canada Research Chair and Laboratory Administrator
COSMO – Stochastic Mine Planning Laboratory
Department of Mining and Materials Engineering
McGill University
Frank Dawson Adams Building, Room 123A
3450 University Street
Montreal, Quebec H3A 0E8
Canada
Tel.: (514) 398-5461
E-mail: admcrc.mining@mcgill.ca
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