Project Evaluation by Sensitivity, Scenario and Risk Analysis

Preliminary project evaluation is relevant to the evaluation process of the decision makers (or executives) prior to making the critical business choices. Important to the assessment is an integrated sensitivity, scenario and risk analysis at every stage of a mining project. This should include the evaluation of different options taking into account uncertainties. Construction of interactive financial computer models where each element is functionally integrated into a fully integrated life-cycle allows rapid and automatic study of the sensitivity of each element through changes in the value of an input. The scenario analysis is the effect of changing more than one input at a time, organised through scenarios in a decision tree. Risk analysis is an integrated analysis of the effect of all uncertainties of the parameters, using Monte Carlo simulation. Key to the asset decisions process is that the decision maker is provided with the essential integrated decision information. We have clustered this information into several scenario groups. Within each group, two levels of uncertain information are distinguished: discrete scenarios critical for the decisions; and remaining uncertainty within the scenario (risk analysis) which can be modelled by continuous probability density functions (pdfÆs). For an asset, the relevant scenarios in each group and the associated continuous pdfÆs need to be defined. When the scenario groups and associated pdfÆs have been defined for the asset, the decision process can be started by structuring the different scenario groups in a Scenario Tree. A Scenario Tree contains decision and end nodes. Each end node corresponds to a completely defined mine project or asset model. The calculations for each end node result in a set of stochastic realisations for the reserves, production forecast, cash flow, and profitability indicators (NPV, IRR, DPR). Thus, a deterministic and fully probabilistic multi-commodity analysis tool is provided to investigate the sensitivity and robustness of decisions.