Modelling Asymmetrical Facies Successions Using Pluri-Gaussian Simulations

  • Thomas Le Blévec
  • Olivier Dubrule
  • Cédric M. John
  • Gary J. Hampson
Part of the Quantitative Geology and Geostatistics book series (QGAG, volume 19)


An approach to model spatial asymmetrical relations between indicators is presented in a pluri-Gaussian framework. The underlying gaussian random functions are modelled using the linear model of co-regionalization, and a spatial shift is applied to them. Analytical relationships between the two underlying gaussian variograms and the indicator covariances are developed for a truncation rule with three facies and cut-off at 0. The application of this truncation rule demonstrates that the spatial shift on the underlying gaussian functions produces asymmetries in the modelled 1D facies sequences. For a general truncation rule, the indicator covariances can be computed numerically, and a sensitivity study shows that the spatial shift and the correlation coefficient between the gaussian functions provide flexibility to model the asymmetry between facies. Finally, a case study is presented of a Triassic vertical facies succession in the Latemar carbonate platform (Dolomites, Northern Italy) composed of shallowing-upward cycles. The model is flexible enough to capture the different transition probabilities between the environments of deposition and to generate realistic facies successions.


Gaussian Function Transition Rate Spatial Shift Asymmetrical Relation Sequence Indicator Simulation 
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.



The authors would like to thank the Earth Science and Engineering Department of Imperial College for a PhD studentship grant for T. Le Blévec and Total for funding O. Dubrule professorship at Imperial College.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Thomas Le Blévec
    • 1
  • Olivier Dubrule
    • 1
  • Cédric M. John
    • 1
  • Gary J. Hampson
    • 1
  1. 1.Imperial College, Royal School of MinesLondonUK

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