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Conference Proceedings

Sixth International Mining Geology Conference

Conference Proceedings

Sixth International Mining Geology Conference

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Simulations of the Muyumkum Uranium Roll Front Deposit by Using Truncated Plurigaussian Method

The uranium grade in roll front deposits is the result of successive processes that can be summarised in two steps. First a sedimentary phase, which gives the deposit support, then an oxidation-reduction phenomenon, which leads to the uranium deposit itself. In order to simulate such a deposit, it is important to mimic these different phases. The final aim of such a study is to localise the uranium itself and to reproduce the internal heterogeneity of the orebody in order to simulate the recovery process._x000D_
The idea in this paper is not to reproduce a genetic approach but to consider the final image of the deposit. Three approaches are proposed. The first one consists of simulating the facies of the sedimentary deposit. The second approach reproduces the distribution of facies resulting from oxidation phenomenon (reduced or oxidised facies). The third approach consists of simulating the mineralisation at the interface of reduced and oxidised areas using the definition of a new data set determined by the grade values. At the end of each approach, the uranium grade could be simulated facies by facies according to the corresponding distribution characteristics._x000D_
The plurigaussian method dedicated to random set simulations is well-suited for the facies simulations of deposits resulting from several sedimentary processes whether correlated or not. In this paper, the benefit of this method is demonstrated in an actual case study._x000D_
FORMAL CITATION:Fontaine, L and Beucher, H, 2006. Simulation of the Muyumkum uranium roll front deposit by using truncated plurigaussian method, in Proceedings Sixth International Mining Geology Conference, pp 205-216 (The Australasian Institute of Mining and Metallurgy: Melbourne).
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  • Simulations of the Muyumkum Uranium Roll Front Deposit by Using Truncated Plurigaussian Method
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  • Published: 2005
  • PDF Size: 1.925 Mb.
  • Unique ID: P200606023

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