Advanced Resource Estimation and Simulation

Course presenters: Oscar Rondon – Principal Geostatistician; Ian Glacken – Executive Consultant

Taking your resource estimation knowledge to the next level

This three-day practical course builds on the introductory information in the four-day or five-day Resource Estimation course and covers the following topics:

• A refresher of kriging
• Overview of kriging approaches: Ordinary, Simple, Indicator, Cokriging – when are they useful and applicable?
• The dispersion variance and the change of support
• How we predict the mining tonnage-grade curve from sample data – global change of support
• How we predict the tonnage-grade curves of mining blocks from large block estimates
• The differences between global and local changes of support
• What is non-linear estimation and when is it useful?
• What is a recoverable resource? Recoverable resource techniques
• How we assess grade risk in mining
• Conditional simulation of single variables (univariate) and multiple variables
• What is multivariate simulation and why is it useful?
• Categorical simulation for rock types.

This course addresses some of the key issues in mining and mineral resource estimation, and covers many ways to get more out your grade and geological data. Following a review and refresher of the kriging equations, we look at the various flavours of kriging and when they are applicable. The particular advantages of non-linear kriging approaches such as single and multiple indicator kriging are covered.

An overview of the concept of the dispersion variance leads onto a consideration of recoverable resources – that is, predicting the tonnage and grade available at the time of mining, either from the sample data (a global change of support) or from a large block estimate (local change of support). The three main recoverable resource techniques – uniform conditioning (including local uniform conditioning), multiple indicator kriging and conditional simulation – are covered in detail.

We consider the concept of assessing grade and geological risk through simulation and provide an overview of the more popular and applicable simulation techniques, including sequential gaussian simulation, sequential indicator simulation, turning bands, and others. Simulation of geological features is addressed via a consideration of categorical simulation. Finally, the simulation of multiple variables is covered, looking at the most applicable multivariate simulation techniques.

Throughout the course, concepts and best practice are illustrated via the use of activities which use GSLIB-style software and Supervisor software on real-world datasets – supplied for the course by Snowden Optiro. All attendees receive a free temporary Supervisor software licence.

In-house /Online or Onsite training is a cost-effective way of getting your whole team trained. Get in touch to find out more.