Optimising stope design through economic and geotechnic assessments of predictions made at a meter scale resolution using the sites' reconciled data.

The final geometry of open stopes often diverges from the design, creating unintentional volumes of overbreak and underbreak. Tools, such as the Stability Chart, are used for predicting overbreak, but its limitations regarding the precision of the predictions and the exclusion of underbreak have constrained the benefits of a predictive tool at the design stage. Furthermore, the economic aspects are not integrated when addressing geomechanical stope design. This paper presents how understanding and predicting stope performance at a meter-scale resolution through a multivariate model can be used for assessing the geotechnical (overbreak and underbreak) and economic stope performance. These predictions estimate the magnitude and location of overbreak and underbreak across the design surface, and are used to resolve the expected geometry of the mined void. The incorporation of a predicted mined void with grade values from a block model allows for a comprehensive economic stope performance estimate. This work is a significant step towards a stope design and planning process that minimizes the stability issues, dilution and loss of ore across the stope. As designing for higher ore recovery increases the potential for dilution and vice versa, this approach allows for the value realised from mining a stope to be maximised by quantifying this inherent economic trade-off. The enhanced resolution of both data and predictions has allowed for a more comprehensive evaluation of the predicted stope performance and economic outcomes during the design phase. This marks a notable advancement in the ability to design and plan the optimal stope. • A new probabilistic stope design approach for assessing the expected mining void. • Utilises data at a meter scale resolution and a multivariate model. • A comprehensive evaluation of the predicted overbreak and underbreak. • Incorporation of grade to quantify the economic trade-off of different designs. • It marks a notable advancement in designing and planning the optimal stope. [ABSTRACT FROM AUTHOR]