| Popis: |
Understanding uncertainty in resource models is a significant requirement of mineral resource evaluation. Geostatistical simulation is one method that can be used to quantify uncertainty and Sequential Gaussian Simulation (SGS) is one of the easiest techniques to understand and implement. Using SGS provides both a spatial model of a given variable and the ranges around that variable at any number of scales. The Jay kimberlite pipe is located in the southeastern quadrant of the EKATI property. Drilling to date has identified three kimberlitic domains characterized by varying lithological properties. These domains are not separated by hard contacts, but rather by boundaries that are transitional. Within these domains, vertical trends exist; in particular, diamond grade increases with depth. For these reasons, Jay required an in-depth investigation of the best uncertainty-based grade modelling method to use. Grade was modelled by organic SGS and by using the stepwise conditional transform (SCT) to incorporate a trend into the simulation routine. Although the SGS results were valid, they did not fully reproduce the trend and therefore, the results did not fully match the geological interpretation of the deposit. The SCT results reproduced the trend, however, did not correspond to the variability of the data and therefore under-represented the actual uncertainty in the model. This was confirmed through detailed uncertainty calculation and probabilistic resource classification. Therefore, the SGS model was chosen as the preferred uncertainty-based grade model for the Jay pipe. |
Full Text from ScienceDirect