Risk Analysis and Mineral Resource Classification

Gain a sound understanding of the concepts and techniques of conditional simulations for application to common mining issues



Geostatistical simulation techniques provide robust and valuable tools for helping to solve mining problems associated with risk and uncertainty. This course will provide you with a sound understanding of the concepts and techniques of conditional simulations for application to common mining issues. Practical solutions to post-process simulations, assessing the uncertainty related to your estimates (grades, geology,…) are presented and discussed.

An overview of the methods used for mineral resources categorization is also presented, along with a practical session.  Methods covered range from Kriging variance to conditional simulations, and include an introduction to spatial sampling density variance, which measures the efficiency of a drilling pattern.

Key Features

This course is focused on mining issues

  • Simulations for continuous and categorical variables
  • Simulation concepts and theory explained in a clear and concise way
  • Comparison between the different methods to categorize your mineral resources between measured, indicated and inferred; use of simulations for building resources categories and new geostatistical tools such as spatial sampling density variance
  • Demonstrations and examples using Isatis
  • Plenty of hands-on exercises with Isatis to reinforce and explore concepts

Who should attend

This course is aimed at geologists, engineers and others seeking a sound theoretical and practical knowledge of conditional simulations for mining applications.

Course content

  • Reminders of linear and non-linear geostatistics and their role in assessing uncertainty: dispersion variance, change of support, information effect, etc.
  • Simulating continuous variables: Turning Bands and Direct Block Simulation
  • Simulating categorical variables: Sequential Indicator
  • A comprehensive guide to simulation using Isatis
  • Uncertainty on recoverable resources estimates
  • Resource classification from sampling criteria to confidence intervals from simulations
  • Explanations and practical examples on other tools to quickly assess your mineral resources categories.
  • Case studies: Assessing risk and uncertainty of grade estimates


As the course refers to advanced geostatistical concepts, it is highly recommended that attendees have a reasonable knowledge of variography and kriging.