500 This approach requires an understanding of the before and after blasting conditions, discerning between the grade distribution of each block when they are isolated, and the mixed statistics as the blocks are combined and selectivity is no longer possible. The representation of this logic is presented in Figure for the results of muck pile #4, where the block statistics are differentiable on the overlayed grade distribution (on the left), solely considering the geologic aspects of each block. The right-hand-side plot represents the statistics of the same muck pile after the blasting, with all blocks combined and including operational parameters, such as the cutoff grade for material classification. The simulation also differentiates subdivisions in the grade distribution to represent the percentiles of the statistics, where P80 matches the selected cutoff grade to differentiate between ore and waste. From this observation, we can interpret that for 80% of the simulations the muck pile #4 will be labeled as waste, while 20% of the cases may actually be ore. This uncertainty in the correct classification of the material will drive special considerations on what is the correct destination for each muck pile and the economic impact of the decision. Figure 2 - (left) Grade distribution of each block before blasting. (right) Combined statistics after blasting. The output results from the simulation process generate a pool of percentiles {1%, 2.5%, 5%, 10%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 90%, 95%, 97.5%, 99%} that is reduced to key percentiles, henceforth described as scenarios (for the stochastic implementation), all of them assumed to be equally possible to occur (from best to worst case scenario). The mean values for each scenario are displayed in Table , where the cells containing the grades are highlighted based on material classification: red for waste, and yellow for ore. P50 column represents mean grades from the grade distribution modelling, for comparison purposes. Table 1 – Muck piles’ mean grade values (Cu%) for each scenario under analysis. Muck pile ID P5 Scenario 1 P10 Scenario 2 P30 Scenario 3 P50 Scenario 4 P70 Scenario 5 P90 Scenario 6 P95 Scenario 7 1 - - - - - - - 2 0.3382% 0.3386% 0.3394% 0.3400% 0.3405% 0.3414% 0.3418% 3 0.3207% 0.3228% 0.3271% 0.3300% 0.3330% 0.3373% 0.3394% 4 0.2567% 0.2617% 0.2724% 0.2798% 0.2874% 0.2986% 0.3041% 5 0.2789% 0.2806% 0.2847% 0.2881% 0.2923% 0.3008% 0.3069% 6 0.2361% 0.2391% 0.2456% 0.2499% 0.2544% 0.2609% 0.2641% 7 0.3599% 0.3642% 0.3733% 0.3797% 0.3864% 0.3964% 0.4015% 8 0.2408% 0.2449% 0.2538% 0.2601% 0.2667% 0.2766% 0.2815% 9 0.3287% 0.3333% 0.3428% 0.3498% 0.3567% 0.3672% 0.3725%
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