Resumen

PEROLD, J.  y  BIRCH, C.. Benefits of including resistivity data in a resource model - an example from the Postmasburg Manganese Field. J. S. Afr. Inst. Min. Metall. [online]. 2019, vol.119, n.3, pp.271-278. ISSN 2411-9717.  http://dx.doi.org/10.17159/2411-9717/2019/v119n3a6.

Due to the challenging geological environment of the Postmasburg Manganese Field (PMF), a study was conducted to determine if any benefits would derive from the inclusion of resistivity data during three-dimensional (3D) modelling of the manganese resource. This was achieved by estimating manganese resources from 2011/2012 drilling data and comparing them with manganese resources estimated from the same drilling data and resistivity data collected during 2013 and 2017. Both models were adjusted to limit their extent to the same 3D modelling space. Significant volume and tonnage differences were observed for all lithological units. The greatest differences were noted in the manganiferous zones of alteration - 7.200 Mt for the geological model versus 3.700 Mt for the geoelectric model. This study showed that the inclusion of resistivity data can reduce exploration costs significantly, as a direct consequence of the resistivity data allowing more accurate siting of boreholes. This decreases the number of boreholes, samples, and analyses required due to the 3D electrical delineation of mineralized areas prior to drilling. An additional benefit is the ability to more correctly forecast the net present value of an operation due to more accurate estimation of manganese resources and stripping ratios. This is clearly demonstrated by the estimated gross profit estimation of R409 million for the geological resource model versus R264 million for the geoelectric resource model. The addition of resistivity data can, therefore, reduce exploration costs and can increase confidence in geological and financial modelling. It would be reasonable to conclude that this approach could also be used for karst-hosted massive sulphide deposits.

Palabras clave : resource estimation; manganese; resistivity data; financial modelling.

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