Standardizing the Mine-Call-Factor for Three (3) Generational Models—A Case Study for ASARCO Mission Mine, AZ

Mine reconciliation is the comparison of an estimate of a long-range resource model, short-range model, ore control model, or a mine production plans, or schedule measured against survey measurements of stockpiles and dumps and production records, usually compared with the final processing metal produced. Mission Mine’s current reconciliation system does not take into consideration the establishment of reconciliation factors, or it nominally assists in confirming the grade and tonnage estimation efficiency of long-range, short-range, and ore control models or diligently estimate resource/reserve models and survey pick-ups compared to actual or budgeted production. The main objective of the project is to establish an automated reconciliation processing system and implement a new system to measure the operation's performance against targets, confirm the grade and tonnage estimation efficiency of mineral resource and ore control models, ensure the accurate valuation of mineral assets, and provide key performance indicators for ore control predictions. Establishing reconciliation factors often takes a rigorous process and over an extended period to arrive at appropriate values/factors for a deposit. The presentation summarizes the case study of the reconciliation evaluation between three long-range models produced from 2019 and 2025 for Mission Pit. Mine reconciliation factors for F1, F4, FLTM, FSRM and FMRLR evaluated for the process indicated varying variances for all three models. Results from evaluation consistently showed acceptable predictions with tonnage, grade and contained copper predicting averages within 0% to 10% for all models within a twelve-month period for F1. FLTM factors showed variances of 10% to 17% lower for tonnages and contained metal within the twelve-month period for all three models but the grade was within acceptable limits. FMRLR factors consistently showed lower percentage variance in tonnages, high variance in grade and lower variance in contained metal for all three models. The contained metal variance predicted for all three models by production were 9%, 8% and 10% lower for 2019, 2022 and 2025 respectively.