1887

Abstract

Summary

In this work, the Stochastic Partial Differential Equation approach is used to model the underlying Gaussian random fields in the PluriGaussian models. This approach allows to perform conditional simulations with computational complexity nearly independent of the size of the data sets. Furthermore, by using non-homogeneous operators, this framework allows to handle varying anisotropies and model complex geological structures. The model is presented and the proposed simulation algorithm is described. The methodology is illustrated through two synthetic data sets.

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/content/papers/10.3997/2214-4609.201902174
2019-09-02
2024-03-29
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References

  1. Armstrong, M., Galli, A., Beucher, H., Le Loc'h, G., Renard, D., Doligez, B., Eschard, R. and Geffroy, F. [2011] Plurigaussian simulation in geosciences.Springer-Verlag, Berlin.
    [Google Scholar]
  2. Emery, X., Arroyo, D. and Pelâez, M. [2014] Simulating Large Gaussian Random Vectors Subject to Inequality Constraints by Gibbs Sampling. Mathematical Geosciences, 46, 265–283.
    [Google Scholar]
  3. Lantuéjoul, C. and Desassis, N. [2012] Simulation of a Gaussian random vector: a propagative version of the Gibbs sampler. In: The 9th international geostatistics congress. 174–181.
    [Google Scholar]
  4. Lindgren, F., Rue, H. and Lindström, J. [2011] An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 73(4), 423–498.
    [Google Scholar]
  5. Pereira, M. and Desassis, N. [2018a] Efficient simulation of Gaussian Markov random fields by Chebyshev polynomial approximation. arXiv preprint arXiv:1805.07423.
    [Google Scholar]
  6. Pereira, M. and Desassis, N. [2018b] Finite element approximation of non-Markovian random fields. arXiv preprint arXiv:1811.03004.
    [Google Scholar]
  7. Whittle, P. [1954] On stationary processes in the plane. Biometrika, 434–449.
    [Google Scholar]
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