Geometallurgical testing enhances process plant forecasting by integrating mineralogical, textural, and ore property data across the deposit, enabling more precise predictions of metallurgical performance like throughput, recovery, and energy use.
It develops spatial block models of ore hardness and processing behavior using methods such as SPI or Bond tests to reconcile laboratory results with actual plant performance, cutting mill throughput forecast errors from about 17% to below 3%(Bulled et al., n.d.).
Through regular testing cycles that combine drill core sampling, modeling tools like CEET, and ongoing reconciliation, the approach stabilizes operations, improves mine planning, and better aligns production with sales commitments.
By reducing the impact of ore variability, it also enhances energy efficiency and concentrate quality while encouraging stronger collaboration across departments.
Reference:
Bulled, D., Leriche, T., Blake, M., Thompson, J., & Wilkie, T. (n.d.). Improved Production Forecasting Through Geometallurgical Modeling.
