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Mineralogy and Petrology

, Volume 112, Supplement 2, pp 673–684 | Cite as

Microdiamond grade as a regionalised variable – some basic requirements for successful local microdiamond resource estimation of kimberlites

  • Johann StiefenhoferEmail author
  • Malcolm L. Thurston
  • David E. Bush
Original Paper
  • 126 Downloads

Abstract

Microdiamonds offer several advantages as a resource estimation tool, such as access to deeper parts of a deposit which may be beyond the reach of large diameter drilling (LDD) techniques, the recovery of the total diamond content in the kimberlite, and a cost benefit due to the cheaper treatment cost compared to large diameter samples. In this paper we take the first step towards local estimation by showing that micro-diamond samples can be treated as a regionalised variable suitable for use in geostatistical applications and we show examples of such output. Examples of microdiamond variograms are presented, the variance-support relationship for microdiamonds is demonstrated and consistency of the diamond size frequency distribution (SFD) is shown with the aid of real datasets. The focus therefore is on why local microdiamond estimation should be possible, not how to generate such estimates. Data from our case studies and examples demonstrate a positive correlation between micro- and macrodiamond sample grades as well as block estimates. This relationship can be demonstrated repeatedly across multiple mining operations. The smaller sample support size for microdiamond samples is a key difference between micro- and macrodiamond estimates and this aspect must be taken into account during the estimation process. We discuss three methods which can be used to validate or reconcile the estimates against macrodiamond data, either as estimates or in the form of production grades: (i) reconcilliation using production data, (ii) by comparing LDD-based grade estimates against microdiamond-based estimates and (iii) using simulation techniques.

Keywords

Microdiamond Variography Variance-support curve Size frequency distribution Simulation 

Notes

Acknowledgements

The authors would like to thank the De Beers Group of Companies, Debswana, De Beers Canada Inc. and Anglo American Corporation for permission to publish this work. Mr. Cuan Lohrentz is acknowledged for his assistance in the computational aspects of the simulation studies. Dr Christian Lantuéjoul is acknowledged for his input in the formulation of the non-adjacent sample covariance. We thank the two anonymous reviewers and editor Alan Kobussen for their thorough efforts which improved the quality of this publication.

Supplementary material

710_2018_566_MOESM1_ESM.pdf (387 kb)
ESM 1 (PDF 387 kb)

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Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2018

Authors and Affiliations

  • Johann Stiefenhofer
    • 1
    • 2
    Email author
  • Malcolm L. Thurston
    • 1
  • David E. Bush
    • 3
  1. 1.Technical and SustainabilityDe Beers Group Services (Pty) LtdJohannesburgSouth Africa
  2. 2.MinRes, Corporate DivisionAnglo American Operations LtdJohannesburgSouth Africa
  3. 3.Z Star Mineral Resource Consultants (Pty) LtdCape TownSouth Africa

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