Geostatistical Simulation Techniques Applied to Kimberlite Orebodies and Risk Assessment of Sampling Strategies

  • Jacques Deraisme
  • David Farrow
Part of the Quantitative Geology and Geostatistics book series (QGAG, volume 14)

Typically a kimberlite diatreme has several different geological zones. The upper portion is generally filled with the sedimentary crater facies, the central zone is more typically an in situ massive series of volcanic breccias and the lower regions comprise a complex root zone. Depending on the local degree of erosion, not all zones remain at any particular kimberlite occurrence.

A method of simulating the simpler internal geologies seen in the central region had previously been developed using a geometrical technique. In the upper reaches of the diatreme zone, the geologies have more complicated geometries and the approach adopted for the central regions needs to incorporate a more sophisticated method of simulating the internal geologies.

The similarity between the sedimentary facies that comprise the crater zone infill and the sequences that the oil industry targets as oil reservoirs suggest a similar technique could be applied to the simulation of internal geology of crater zone of kimberlite pipes.

Previous work has shown that a truncated gaussian approach can be useful, but the restrictions on facies relationships have limited its implementation. Plurigaussian simulation allows more complex interrelationships to exist between the simulated zones.

In conjunction with other geometric simulations, plurigaussian simulation can be used to guide sampling programs to optimise sampling layouts and sample size and ensure that the goals of the sampling programs are attainable. This paper focuses on the application of the combination of these simulation techniques and will be illustrated by a case study.


Debris Flow Reference Surface Gaussian Variable Kimberlite Pipe Internal Geology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer 2005

Authors and Affiliations

  • Jacques Deraisme
    • 1
  • David Farrow
    • 2
  1. 1.GeovarianceFrance
  2. 2.MRM - TSS, De Beers Consolidated Mines Ltd.South Africa

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