Ore grades are monitored regularly in cave mines through drawpoint sampling. Automating grade monitoring through deploying X-ray fluorescence (XRF) sensors on the buckets of production loaders has been proposed as an alternative approach to address the issues around the traditional practice of drawpoint sampling. Bucket-mounted sensors can also be employed for bulk ore sorting underground. This study is aimed at evaluating the deployment of XRF sensors on production loaders as an opportunity for grade monitoring or bulk ore sorting in caving operations. The mill feed grade prediction performances of the drawpoint sampling program and mine planning software were assessed for the Cadia East panel cave mine. The results showed that the drawpoint samples underestimated the mill feed quality during a 10-month investigation period. The cave portions with bulk ore sorting potential were linked to the extraction level layout to estimate the number of drawpoints where sensors could be situated for diverting ore and waste. Samples obtained from the mine were tested to evaluate the ability of a lab-scale proxy of a bucket-mounted XRF sensor system to measure copper and gold grades. R-squared values of 0.84 and 0.68 were achieved between the predicted and measured copper and gold grades of the samples, respectively. Sensor test results are promising in revealing the potential to utilize XRF sensors underground. Future test work is encouraged to further validate the applicability of XRF sensors in an underground mining environment.

Conceptual bulk ore sorting studies are essential for determining a potential improvement in mine economics before undertaking on-site sensor trials. Two approaches, block modelling and drill core compositing, are applied to simulate the bulk ore sorting performance of mining operations. While one employs the grade data of a block model, the other approach utilizes composited drill core grades. This study aimed at comparing these two approaches by estimating in-situ grade heterogeneities and simulating the bulk ore sorting performances of the currently active caves of the Cadia East panel cave mine. The results show that block modelling tends to smooth the grade variability that initially exists in the drill core grade data. Particularly in the portions of the deposit where drilling is sparse or widely spaced compared to the selected block size, block modelling leads to lower grade heterogeneity and bulk ore sorting performance estimates. However, when the drill hole data is nonrepresentative of the area of interest, block modelling can predict more realistic bulk ore sorting performances compared to drill core grades. The assessments performed with the blocks and drill core composites of various sizes showed that grade heterogeneity was adversely affected by an increased sorting scale due to averaged metal grades.

Bulk ore sorting is a preconcentration method applied to bulk streams or batches of material. The effectiveness of bulk ore sorting relies on the degree of the naturally occurring in situ grade heterogeneity of an ore deposit. The blending of ore during mining and material handling degrades the in situ grade heterogeneity initially present in an orebody and reduces the potential to apply bulk ore sorting. Block and panel cave mines experience mixing from the establishment of caves to the delivery of the caved ore to concentrators. This study focused on tracking the grade heterogeneity and quantifying the impact of mixing on the sorting potential of the Cadia East panel cave mine via the reconciliation of the grade measurements performed at different locations. The results showed that the copper and gold grades were almost fully homogenized via various mixing events identified for the mine. The tracked grade heterogeneity values revealed that the mixing during material handling, which included ore blending according to mine planning, reduced the grade variability more drastically than the mixing within the caves. As the ore travelled from its original in situ location, the grade distributions gradually transformed, and the grades eventually normalized around the mean values. Only insignificant amounts of low-grade material that could have potentially been discarded were reported to the on-belt sensor located at the surface. The results of this study are significant for cave mines exploring sorting systems for preconcentration as they highlight how mixing can impact the variability in ore grades.