How Details of the Geometallurgical Optimisation Influence Overall Value

The precise formulation of a geometallurgical optimisation problem is by necessity a simplification of reality. It includes implicit choices such as data availability or mining block geometry. Additional data can be ore body data, production data or market data. Often these choices are predetermined by the software, the workflow or corporate culture and as such are not even queried. There are several aspects that might play a role in the optimization. They include not only the spatial model on which the selection of mining blocks and the potential mining sequence are based, but also the complexity of the processing model, the way in which uncertainty is treated, the scope of responsibility and the complexity of the model. In addition the timing of the optimization and the availability (or lack thereof) of information influence the outcome of any optimization.

We show that different modelling choices and different model formulations for the same mine can lead to very different processing choices, substantially different NPV’s , opposite investment decisions and so to overall different values for the entire operation. The selection of adequate simplifications and corresponding formulations for the optimisation problem is thus an important task in itself.

For this purpose we introduce a method quantifying the impact of certain simplifications prior to the optimization itself. E.g. for the effect of mining block choices the effect depends mainly on the spatial structure and the structure of the processing gain function. Both can be quantified beforehand. Likewise the effect of additional data depend on the increase of information. Again this can be quantified from a spatial model.

Based on the outcome appropriate simplifications can be selected for the geometallurgical optimization.