Assessing dilution, ore loss and profit differences from various hand-drawn dig limits compared to optimal ore-waste delineationsin deposits of variable heterogeneity

For every blast pattern, zones of unique material types need to be classified before mining. Most material types can be summarized into different kinds of ore and waste. Blocks generated from blasthole assays are too small to be selectively mined, so areas with a single material classification meeting the mine’s selective mining unit must be defined. Current industry standard practices are to manually draw ore/waste dig limits, but this process is subjective and results in quantities of dilution and ore loss that can be improved upon to enhance the profitability of mining operations. In this study, two weeks of production data from a homogeneous copper (Cu) porphyry and heterogeneous manto-type Cu deposit were used to assess the variability in the hand-drawn dig limits of 20 geologists, mining engineers and ore control specialists, which were compared with the optimal ore/waste delineation. The profit for 20 distinct hand-drawn dig limits for the homogeneous mine varied by 3.7 percent, from $10.5 million to $10.9 million, averaging at $10.8 million. The percentage was nearly double for the more heterogeneous mine at 5.9 percent, from $17.9 million to $19.0 million, averaging at $18.6 million. Using the optimal ore waste delineation, the profit increased to $11.0 million (1.9 percent increase) and $19.3 million (7.0 percent increase) for the homogeneous and heterogeneous deposit, respectively. The natural variability, diggability requirement and selectivity are identified as the main drivers of ore loss and dilution. Recommendations are provided for reducing the subjectivity in manual hand-drawn dig limits by integrating dig limit optimization algorithms as a tool to assist practitioners. Background Dig limits are usually hand-drawn on mining software by a geologist, mine engineer or ore control specialist who attempts to group blocks with grades estimated from blasthole assays while meeting a selective mining unit (SMU), but in the process of creating mineable units there is always some degree of dilution and ore loss. The dig limit optimizations tested to date have mostly been on limited datasets and usually compared with a single hand-drawn dig map. Here, real data from two different copper mines are used, and 20 geologists, mine engineers and ore control specialists were asked to delineate ore and waste boundaries to assess variability with hand-drawn maps of the same data. This paper seeks to determine the differences in manual hand-drawn dig limits and compare these to optimized dig limits to estimate the improvable ore loss and dilution for enhancing the profitability of mining operations. The optimized dig limits are generated using an objective algorithm, and the optimal material classifications are used to compare against the more subjective manually drawn limits. Methods The approach here uses block model grades in a section with ore and waste transitions, which needs to be grouped using dig limits or polygons to isolate mineable units of each material type. First, 20 geologists, mining engineers and ore control specialists were asked to manually delineate ore and waste zones from the block model map, requiring only to maintain the specified SMU size. The same block model is used in an optimization algorithm to determine the optimal ore and waste boundaries that maximize profit while respecting the SMU size. The ore loss, dilution and profit were then calculated to assess differences within the hand-drawn maps and compare them with the optimal dig limits. Data from mines with distinct heterogeneity were used to determine how the variance in manual hand-drawn limits and potential improvement using objective, optimal-grade control methods scale with more discontinuity (top of Fig. 1). The data were presented in the same format to each ore control practitioner to study differences in how each delineates the ore and waste boundaries (bottom of Fig. 1). Results and discussion The profit for the heterogeneous deposit varied by $1.1 million (5.9 percent), from $17.9 million to $19.0 million, which is significantly more than for the homogeneous deposit, which varied by $0.4 million (3.7 percent), from $10.5 million to $10.9 million. Figure 1: Spatial map of the 10 × 10 × 15 m block Cu grades for the homogeneous Cu porphyry and heterogeneous manto-type Cu deposit with a schematic showing how ore and waste boundaries are drawn on 5 × 5 m blocks with various amounts of ore lossor dilution, depending on the practitioner. Other metrics like the Cu metal in the ore and waste also showed higher variability for the more heterogeneous deposit (Table 1). On average, dilution and ore loss increased for the more heterogeneous deposit by 5.6 and 4.6 percent, respectively. The financial impact of suboptimal dig limit determination due to subjective, manual hand-drawn polygons is more severe with higher-variability deposits, which have many sharp contacts between high-grade ore and waste. Most of the areas delineated as ore or waste were consistent between all the dig maps. The maps at the top of Fig. 2 show all the polygons drawn for both deposits and highlights blocks that were classified differently. For the homogeneous Cu porphyry, 76.4 percent of blocks all had the same classification while 23.6 percent differed. As expected, for the more variable heterogeneous deposit, 67.8 percent had the same classification and 32.2 percent differed, demonstrating more inconsistency in the material classification for the heterogeneous deposit compared to the more homogeneous deposit. Similar to the manual hand-drawn dig limits, most of the dilution and ore loss for the optimized dig limits occurs along ore/waste transitions (bottom of Fig. 2). Dilution plus ore loss increased by nearly a factor of two from a total of 8.7 percent to 15.0 percent for the homogeneous and heterogeneous Cu deposit, respectively.Both the average hand-drawn and optimized dig limits achieved a greater portion of the single-block sorting profit for the homogeneous deposit compared to the heterogeneous deposit (Table 2). The optimal dig limits compared to the hand-drawn limit average increased the profit by $0.20 million (1.9 percent) and $0.70 million (7.0 percent) for the homogeneous and heterogeneous deposit, respectively. Table 2 summarizes the various performance metrics demonstrating the overall improvements from the averaged manual dig limits, optimized dig limits and individual block sorting. The benefits of more accurately sorting the ore and waste blocks increased for the more heterogeneous deposit, also confirming that the more variable deposit will benefit more from improved selectivity. Conclusions Figure 2: Maps showing the 20 dig limits and material classification for the optimal dig boundaries for the (a) homogeneous Cu porphyryand (b) heterogeneous manto-type Cu deposit. To study the dilution and ore loss from inaccurate dig limits, mining engineers, geologists and ore control specialists were asked to manually delineate ore and waste boundaries in two-week production data from the same homogeneous Cu porphyry and heterogeneous manto-type Cu mine. Due to the difficulty of manually clustering materials correctly and the subjectivity of the procedure, significant variability was observed in the 20 hand-drawn dig limits, resulting in variable amounts of improvable dilution and ore loss. Employing objective dig limit optimization workflows eliminates discrepancies in hand-drawn dig limits, resulting in economic benefits that scale with the deposit’s heterogeneity. Comparing the individual blocks used to develop an SMU with the optimized dig limits also suggests that improving the selectivity results in additional benefits, allowing dilution and ore loss to be further reduced. The benefits of more accurately sorting ore and waste are especially important for mines with more variable, discontinuous grades, which exhibit higher heterogeneity. References A list of all references is available in the full paper.

Assessing dilution, ore loss and profit differences from various hand-drawn dig limits compared to optimal ore-waste delineationsin deposits of variable heterogeneity

Authored by: Found Faraj

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Mining Engineering’s Weekly Rundown: Episode 74

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To view this article you must be a member of SME/UCA.

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