Risk-Based Optimization of Post-Blast Dig-Limits Incorporating Blast Movement and Grade Uncertainties with Multiple Destinations in Open-Pit Mines

Dig-limits optimization is one of the most important steps in the grade control process at open-pit mines. It aims to send blasted materials to their optimal destinations to maximize the profitability of mining projects. Grade and blast movement are key uncertainties that affect the optimal determination of dig-limits. This paper presents an integrated workflow for optimizing dig-limits under grade and blast movement uncertainties. The proposed methodology incorporates these uncertainties into the grade control process to enhance material classification and destination optimization, thereby minimizing ore loss and dilution. A multivariate geostatistical simulation workflow is developed to capture spatial uncertainties in grade distribution and blast movement distance and direction. By applying projection pursuit multivariate transformation and sequential Gaussian simulation for modeling blast movement distances at all locations and flitches within the bench section, the anticipated D-like shape from blasting is reproduced, and uncertainty is quantified. The maximum expected profit method effectively determines optimal material destinations under uncertainty improving overall mining profitability. The proposed risk-based dig-limits optimization model accounts for mining equipment selectivity, irregular bench shapes, and varying orebody orientations, resulting in operational and economically viable dig-limits. A case study on a porphyry copper deposit demonstrated the significant impact of blast movement on ore loss and dilution, emphasizing the need for accurate blast movement modeling and its integration into grade control procedures. By accounting for differential blast movement, the proposed workflow ensures reliable post-blast material classifications, reducing suboptimal decisions, thus improving project profitability and operational efficiency.