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Applied Earth Science
Transactions of the Institutions of Mining and Metallurgy: Section B
Volume 122, 2013 - Issue 1
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Original Article

Measuring and modelling of dry bulk rock density for mineral resource estimation

Pages 16-29 | Received 23 Jan 2013, Accepted 13 May 2013, Published online: 03 Dec 2013
 

Abstract

Rock density information is needed for the estimation of ore tonnage, and also for determining the amount of contained metal; this is because mineralisation grades are usually reported as a ratio of the economically viable components, metals or minerals, to weight units (e.g. grams/tonne). Despite the obvious importance of rock density for the accurate estimation of tonnage and grade of mineral resources, this parameter is often overlooked and receives significantly less attention than assayed metal grades. In particular, the quantity and spatial distribution of the rock density measurements may be chosen without considering the impact of the rock density measurements on the mineral resource estimation. This paper attempts to address several issues associated with current practices of rock density modelling. The first part of the paper overviews the methods most commonly used for measuring the dry bulk density (DBD) of rocks for the estimation of mineral resources. This is followed by a second part proposing the methodology of geostatistical modelling of the rock densities which is suggested as a mathematically supported approach for choosing optimal sampling grids for density samples. It is supported by several case studies of the deposits where geostatistically optimal DBD sampling grids were estimated and proposed for definition of the Measured and Indicated resources and for the grade control purpose. It was noted that the exploration team needs to assure that DBD data collected during the drilling campaigns are not only sufficient for definition of resources and reserves but are also closely enough spaced to allow accurate grade control. The optimal for grade control DBD grids, according to the geostatistical analysis, is similar to the chemical assay grids required for definition of the Measured resources or, less commonly, Indicated resources of the studied deposits.

The author expresses his sincere gratitude to J. Phillips, M. Wlasenko, T. James and A. Lye for providing their data for this study. C. Welton, G. Broadbent, M. Stewart, R. Minnitt and anonymous reviewer of AES journal have reviewed the paper with many useful comments and corrections which are gratefully acknowledged.

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