Many integrated evaluation teams use stochastic simulation only to estimate cumulative probability resource curves for exploration assets. Three deterministic cases are then anchored to P90-P50-P10 points of the curve and serve as the basis for in-depth engineering and exploration economics modelling. As illustrated by Delta prospect, discrepancies between resulting NPV approximations and true prospect NPV may be material.

Since it may take another generation to break the wall between deterministic and stochastic ways of exploration project assessment, this paper suggests an interim workflow method to reconcile both mindsets. The method builds on the ability of modern software to pre-estimate the shape of NPV probability distribution curve. Once the shape is available, a discretization shortcut is applied to obtain relevant NPV distribution fractiles and weights. Equivalent resource fractiles are then ‘reverse-fitted’ using the stochastic value cloud. Finally, discrete cases reflecting such calculated resource fractiles are handed over for deterministic engineering and valuation. With the illustrative Delta prospect, application of the method resulted in picking P70-P32-P16 resource fractiles to ensure the best fit to true (stochastic) NPV.

The proposed method provides a practical way to commingle the strongest features of simulation, discretization and in-depth engineering approaches. It is supported by Full Cycle tools embedded in industry standard software for probabilistic risk, resource and value assessments.

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