Journal of the Southern African Institute of Mining and Metallurgy
versão On-line ISSN 2411-9717
versão impressa ISSN 0038-223X
CHITIYO, G. et al. Predictability of pothole characteristics and their spatial distribution at Rustenburg Platinum Mine. J. S. Afr. Inst. Min. Metall. [online]. 2008, vol.108, n.12, pp.733-740. ISSN 2411-9717.
Prediction of pothole characteristics is a challenging task, confronting production geologists at the platinum mines of the Bushveld Complex. The frequency, distribution, size, shape, severity and relationship (FDS3R) of potholes has a huge impact on mine planning and scheduling, and consequently cost. It is with this in mind that this study was initiated. Quantitative analysis of potholes indicates that pothole size (area covered) can be described by two partly overlapping lognormal distributions. These are referred to as Populations A (smaller) and B (larger). The range of observed pothole sizes conforms to a simple double exponential growth model based on Newton's Cooling Curve. A third size range of very large potholes (Population C) that could not be modelled properly within the proposed growth model is interpreted as to represent a very early phase of aggressive regional thermo-chemical erosion and potholing. In general, potholes are dominantly quasi circular with only a subordinate tendency of elongation. In the UG2, potholes with elongated forms are more prevalent in the size range between 20 and 500 m diameter. In the Merensky Reef elongated potholes are more common in the size range above 50 m in diameter. Although not distinctly visible, elongation of potholes in both the UG2 and the Merensky Reef show a net north/south orientation. Using shapes of pothole rims and floor areas, documented for the UG2 in the Waterval Shaft area, it is demonstrated that the northern, down-dip edges of potholes have steeper dips than the southern, up-dip edges. Spatial distribution studies using a uniform quadrant method suggest that in both the UG2 and the Merensky Reef, the potholes are randomly distributed, with a tendency towards clustering. Clustering appears to be more prevalent in the smaller Population A potholes. Bearing all findings in mind, it is found that the model of thermo-chemical erosion of the cumulus floor by new influxes of superheated magma best explains the observed data. Partial to complete melting of the cumulate floor occurred in three phases. The first represents the emplacement of hot magma. This magma, due to turbulent flow and high chemical and physical potential, aggressively attacks the existing floor (crystal mush on the magma/floor interface). Regional erosion is manifested by large, often coalescing potholes. During the second phase, when the magma emplacement process ceased and cooling in situ started, two distinct periods of pothole formation ensued. The first is related to rapid cooling along the relatively steep part of the Newton Cooling Curve, when Population B potholes nucleated randomly and grew rapidly with concurrent convective overturn and largely laminar flow condition. The second period of cooling occurred on the shallow-dipping part of the Newton Cooling Curve. Population A pothole growth became more subdued and nucleation appears to have been, at least locally, clustered. The final phase of this proposed 'super magma cycle' was introduced when chromitite crystallization and precipitation terminated pothole formation. This was followed sequentially by pyroxene and plagioclase crystallization to form the typical cyclic units of the Critical Zone. No suitable proxy could be found for the prediction of pothole density of potholes associated with the UG2 (likely due to limited spatial data coverage), and these are best predicted by extrapolation. The Merensky Reef slope index, in contrast, provides a proxy for pothole density, enabling prediction with reasonable confidence. This predictive model has been verified using underground information. The findings made during the course of this investigation have, when implemented, significant impact. Successful implementation will not only allow enhanced resource and reserve definition, but also better mine planning and scheduling