Geostatistical Mineral Resource/Ore Reserve Estimation and ... - SME

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August 29, 2011
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Registration includes course notes, lunch, and morning and afternoon
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Participation in this course may be a valid activity towards continuing
professional development with up to 26 contact hours.
Participants receive a Certificate of Completion.
Notification of Cancellation received in writing up to August 29,
2011 (minimum of 10 working days before the course) will incur a
20% cancellation fee. No refund will be made after this time. An
alternative participant may be nominated.
INSTRUCTORS
MARCELO GODOY is a Principal Geostatistician with Golder
Associates and provides specialized services in the application of geostatistical
and mine planning techniques for resource estimation, reserve
estimation and risk assessment. Marcelo has a PhD in geostatistics and
strategic mine planning and has been involved in a wide variety of
resource estimation studies for a diverse range of commodities including
precious and base metals, iron ore, coal and industrial minerals. His
experience also includes audits and due diligence reviews for major
mining companies and financial institutions around the world. Over the
last five years Marcelo has managed a series of mine feasibility studies
for copper, gold and iron ore projects. Through audits of operations and
reconciliation reviews he has developed a solid understanding of how
mineral resources are converted into recoverable reserves.
JEAN-MICHEL RENDU graduated as a mining engineer from École des
Mines de Saint Etienne, France, and obtained a Master’s and a
Doctorate in mining engineering from Columbia University, New York.
In 2001 he retired as Vice President Resources and Mine Planning of
Newmont Mining Corporation, with responsibilities for estimation and
public reporting of resources and reserves, and for mining engineering
services worldwide. He is now an executive consultant with Snowden,
Australia. He is the author of approximately 50 publications on mining,
and authored textbooks on geostatistics and cutoff grade estimation. He
is an elected member of the U.S. National Academy of Engineering and
a past director of SME. He was recognised by SME as a Distinguished
Member and a Krumb Lecturer, and received the SME President’s
Citation, the SME Daniel C. Jackling Award, and the AIME Mineral
Economics Award.
ROUSSOS DIMITRAKOPOULOS is currently the Canada Research
Chair in Sustainable Mineral Resource Development and Optimization
Under Uncertainty and Director of the COSMO Laboratory, McGill
University, Montreal, Canada. Previously he was Professor and Director
of the Bryan Research Centre, Univ. of Queensland, Australia. He holds
a PhD in Stochastic Modelling from Ecole Polytechnique, Montreal,
and a MSc from the University of Alberta, Edmonton. He has been
working on risk analysis, risk-based optimization in open pit mine
design, and production scheduling. Roussos has been Senior
Geostatistician with Newmont Mining Co., Denver, and Senior
Consultant with Geostat Systems International. He has taught short
courses and worked in Australia, North America, South America,
Europe, the Middle East, South Africa and Japan.
VENUE DETAILS
McGill University
Department of Mining and Materials Engineering
3450 University Street
Frank Dawson Adams Building, Room 126
Montreal, Quebec, Canada H3A 2A7
admcrc.mining@mcgill.ca
LOGISTICS
Lectures are given from 9 AM (refreshments at 8:30 AM) to 5 PM with
two 15 minute coffee breaks and one hour lunch break.
COSMO – Stochastic Mine Planning Laboratory
Mining Engineering
http://cosmo.mcgill.ca
COSMO – Stochastic Mine Planning Laboratory, a global centre for
leading-edge research and graduate education in “orebody modelling
and strategic mine planning with uncertainty”, is supported by
AngloGold Ashanti, Barrick, BHP Billiton, De Beers, Newmont, Vale,
and The Canada Research Chairs Program, NSERC, CFI.
www.smenet.org
Professional Development
Series 2011
STRATEGIC RISK QUANTIFICATION
AND MANAGEMENT
FOR ORE RESERVES AND
MINE PLANNING
Geostatistical Mineral
Resource/Ore Reserve
Estimation and Meeting
the New Regulatory
Environment:
Step by step from
sampling to grade control
Marcelo Godoy, Golder Associates., Chile;
Jean Michel Rendu, Executive Consultant Snowden, Australia;
and Roussos Dimitrakopoulos, McGill University, Canada
SEPTEMBER 12-16, 2011
Montreal, Canada
Mining E ngineering
COSMO Lab

Geostatistical Mineral Resource/Ore Reserve Estimation and Meeting the
New Regulatory Environment: Step by step from sampling to grade control
The 2010 AusIMM Spectrum
Series Vol. 17: “Advances in Orebody
Modeling and Strategic Mine Planning I:
Old and New Dimensions in a Changing
World” is included with the
course materials
CONTENT AND OBJECTIVES
This course is designed according to the latest regulations
on public reporting of resources/reserves.
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 the derivation of the amplitude of sampling
and estimation errors with advanced techniques
like conditional simulation.
ATTENDEES WILL LEARN:
• Demonstrate how standard statistical
techniques help solve problems of sample
reliability
• Understand when and how geostatistics can
improve resource estimates
• Apply geostatistics to predict dilution and
adapt reserve estimates to that predicted
dilution
• Learn how geostatistics can help you
categorize your resources in an objective
manner
• Demystify conditional simulation and show
how it addresses all the above problems
• Understand principles of NI43-101, SEC
Industry Guide 7, and SME Guide
COURSE OUTLINE
Steps to be followed to estimate resources and
reserves, and where problems may occur
(Rendu)
• Drilling, sampling and assaying
• Geologic model and block model
• From mineral resource to mineral (ore) reserve
• Feasibility study: what will go wrong?
Review of rules and regulations concerning
public reporting of exploration information,
mineral resources and reserves (Rendu)
• Governing principles in NI43-101, SEC
Industry Guide 7, and SME Guide
• International requirements
• Role of Qualified/Competent Person
Statistical analysis of sampling quality control
data (Godoy)
• How to detect a sample bias
• Sampling variances from duplicate datasets
• “Statistical” capping of high sample values
Geological modeling (“domaining”) (Godoy)
• Statistical testing of domains
• Hard, soft or semi-soft limits?
• Influence of domains on resource estimates
Variography (Godoy)
• Intuitive presentation of variograms
• Selection of composite size, directions,
regularization angle and lag distance
• Variogram, spatial covariance or correlogram?
• Real or transformed (log, indicator) data?
• Nugget effect and sampling error
• Variogram modeling with interactive programs
Interpolation (Godoy)
• Anatomy of a kriging
• Conditional bias or oversmoothing? Simple or
ordinary kriging?
PLEASE NOTE it is strongly recommended that participants
bring a laptop and that no previous exposure to statistics and
geostatistics is required.
• Kriging with transformed data and from
samples of different types
• Validation techniques for resource block
models
Resource classification (Godoy and
Dimitrakopoulos)
• Current categories and guidelines
• Parker’s rule and others quantitative criteria
based on precision of estimates
• The derivation of estimation error variance in
classical geostatistics
• Introduction to conditional simulation
From resources to reserves (Godoy and
Dimitrakopoulos)
• Reconciliation with grade control and
production data
• “Recoverable” RR in selective open pit
operations
• Change of support, uniform conditioning and
indicator kriging
• Dilution and loss predicted from simulation
• Geostatistics of BH data: BH kriging and
simulation
WHO SHOULD ATTEND
Exploration and mine geologists, resource analysts,
mining engineers, and anyone acting in the
role of “qualified” or “competent person”.