Risk analysis for mineral resource estimates generally relies on the use of conditional simulation.

Conditional simulation offers the perfect platform to tackle issues related to risk analysis. Conditional simulation, by characterizing spatial variability and producing multiple equi-probable realizations of the orebody, allows you to characterize uncertainty in a way single resource estimates cannot. They pave the way for:

• Quantitative assessment of uncertainties;
• Production of probability based indicators and maps;
• Supporting Monte Carlo risk analysis;
• Reproducing the orebody heterogeneities; and
• Capturing and reducing the space of uncertainty via scenario reduction, allowing effective multiple scenario analysis.

For scenario reduction, Isatis Simulation Reduction module offers a quick way to identify grade realizations which best represent the whole space of uncertainty. This approach is easy to set up in an industrial context and the selected scenarios are more manageable, which means it can be readily implemented to characterise the risk attached to a project due to the uncertainty on the resource for:

• Open pit optimization and mine scheduling;
• Evaluation of projects when taking financial and technical uncertainties into account; and
• Mine optimization for a portfolio of deposits.

Conditional simulation can also be used for:

• Recoverable resource estimation particularly when additivity is an issue; and to characterise the precision of recoverable estimates.
• Sampling optimisation; and
• Resource classification.