Standardizing the Mine-Call-Factor for Three (3) Generational Models—A Case Study for ASARCO Mission Mine, AZ
摘要
MineMine reconciliationReconciliation is the comparison of an estimate of a long-rangeLong-Range resource modelModel, short-rangeShort-Range modelModel, ore control modelModel, or a mineMine production plans, or schedule measured against surveySurvey measurements of stockpiles and dumps and production records, usually compared with the final processingProcessing metalMetal produced. Mission MineMine’s currentCurrent reconciliationReconciliation system does not take into consideration the establishment of reconciliationReconciliation factors, or it nominally assists in confirming the gradeGrade and tonnageTonnage estimation efficiencyEfficiency of long-rangeLong-Range, short-rangeShort-Range, and ore control modelsModel or diligently estimate resource/reserve modelsModel and surveySurvey pick-ups compared to actual or budgeted production. The main objective of the project is to establish an automated reconciliationReconciliation processingProcessing system and implement a new system to measure the operationOperation's performancePerformance against targets, confirm the gradeGrade and tonnageTonnage estimation efficiencyEfficiency of mineral resourceMineral resources and ore control modelsModel, ensure the accurate valuation of mineral assets, and provide key performance indicatorsKey Performance Indicator (KPI) for ore control predictions. Establishing reconciliationReconciliation 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 reconciliationReconciliation evaluationEvaluation between three long-rangeLong-Range modelsModel produced from 2019 and 2025 for Mission Pit. MineMine reconciliationReconciliation factors for F1, F4, FLTM, FSRM and FMRLR evaluated for the process indicated varying variances for all three modelsModel. Results from evaluationEvaluation consistently showed acceptable predictions with tonnageTonnage, gradeGrade and contained copperCopper predicting averages within 0% to 10% for all modelsModel within a twelve-month period for F1. FLTM factors showed variances of 10% to 17% lower for tonnagesTonnage and contained metalMetal within the twelve-month period for all three modelsModel but the gradeGrade was within acceptable limits. FMRLR factors consistently showed lower percentage variance in tonnagesTonnage, high variance in gradeGrade and lower variance in contained metalMetal for all three modelsModel. The contained metalMetal variance predicted for all three modelsModel by production were 9%, 8% and 10% lower for 2019, 2022 and 2025 respectively.