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Sampling, simulation and estimation of secondary diamond deposits

Abstract : The exploration for diamonds and the evaluation of secondary diamond deposits are challenging processes due to the lack of reliable data and/or the sparsity thereof. Continued effort is required to maintain an understanding of these types of deposits as they are explored, sampled and exploited. This thesis address and researches the following : - Demonstrate the clustering of kimberlites and determine the average size of kimberlite targets. - A classification tree was applied to exploration indicator minerals and a model using known kimberlite targets was built, then applied to new areas to identify kimberlite targets. - Marine environments with complex trapping mechanisms are difficult to sample. In some situations there is very little or even no grade information available but a sample optimisation study is required. A shaded pencil sketch is used and statistically manipulated to create simulations for use as a first approximation to optimise sampling. - Sample optimisation studies in deep water marine deposits are well suited to make use of the Cox process to create simulations. The discrete nature of diamonds require a minimum critical size for samples to be representative. Using Cox simulations, the effect of sample size on the accuracy of kriged blocks and panel results is researched. - In recent years, some tailings resources have become economical to remine. Optimal sample size and spacing of samples and a method to do local block estimates was developed and applied to a kimberlite tailings resource.
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Submitted on : Wednesday, January 23, 2013 - 9:47:03 AM
Last modification on : Wednesday, November 17, 2021 - 12:31:19 PM


  • HAL Id : pastel-00780063, version 1


Christian Prins. Sampling, simulation and estimation of secondary diamond deposits. Applied geology. École Nationale Supérieure des Mines de Paris, 2011. English. ⟨NNT : 2011ENMP0031⟩. ⟨pastel-00780063⟩



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