Palabora Lift 1 block cave: understanding the grade behaviour

Abstract

Palabora Mining Company commenced mining of the Lift 1 block cave in 2001. Lift 1 is now nearing completion, and this paper will discuss the challenges around the reconciliation and forecasting of grades during the life of Lift 1. Particular emphasis will be placed on the impact of the open pit failure which took place in 2004 and its impact on the grades later on in Lift 1. The paper will look at the different caving mechanisms which have contributed to, and impacted on, the recovered metal from the block cave. It will also look at how the cave management was impacted by the coarse fragmentation of the cave, which was a first worldwide at the time, and the interaction between practical mining constraints and idealised caving strategies. In the latter stages of the mine, some particularly surprising grade behaviour was experienced, and plausible explanations for this behaviour will be presented relating to the open pit failure material and cave back shapes. Concluding remarks will discuss how the experiences learned from Palabora Lift 1 can potentially benefit Palabora Lift 2 and other future caving operations.

Block cave ore reserves: Are we reporting a reserve or potential inventory?

“…Fortunately, changes to mixing (dilution) parameters only have marginal impacts on reserves, particularly for orebodies with heights of draw >500 m. A significant change in grade behaviour is not observed during the early stages of draw i.e "if we mixed high grade material with similar high grade material we still end up with high grade material" (Diering et al 2018). In general, the uniform distribution of mineralisation provides a predictable forecast for ore recovery, especially during the first half of a drawpoints production period.…”

Development of a model for economic control of loading in sublevel caving mines

“…The model is built mainly to predict the cave front in caving operations. PCSLC model (Diering 2007) 6/10 The model does not incorporate grade monitoring and assumes ore left on above level will be recovered on below levels conclusively but the literature shows a more chaotic flow.…”

Drawpoint loading optimization strategies in block caving: A case study of Palabora Mining Company

“…This leads to lower recoveries, with more fines and dilution. The study by Diering et al, (2018) suggest various factors that contribute to such a high content of dolerite, which leads to fines accumulating in the drawpoint much quicker. This challenge requires selective mining, which is difficult to accomplish in block caving.…”

“…Grade performance is influenced by various factors, which may range from the underground block size, plant recoveries, loading strategies and market conditions dictating the drawing rates, as well as the size and distribution of the drawpoints, and waste or dolerite content (Diering et al, 2018). In this research study we intend to highlight some of the strategies to employ to optimize drawpoint loading.…”