Abstract
This paper is presenting a methodology to handle rigorously soft probabilities in Multiple Point Statistics (MPS) simulation for facies modeling. It is based on the second generation algorithm for MPS simulation using efficient Direct Sampling of the training image. The soft probabilities are considered as local target proportions corresponding to a support size defined by a radius of influence. The acceptation of a data event found in the training image is tempered by its consistency with the target probabilities. Test results are presented to illustrate the efficiency of the technique.
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References
Allard, D., Comunian, A., & Renard, P. (2012). Probability aggregation methods in geoscience. Mathematical Geosciences, 44(5), 545–581.
Chugunova, T., & Hu, L. (2008). Multiple-point simulations constrained by continuous auxiliary data. Mathematical Biosciences, 40(2), 133–146.
Mariethoz, G., Renard, P., & Straubhaar, J. (2010). The direct sampling method to perform multiple-point geostatistical simulations. |textitWater Resource Research, 46, (11).
Strebelle, S. (2002). Conditional simulation of complex geological structures using multiple-point statistics. Mathematical Geosciences, 34(1), 1–22.
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Biver, P., Mariethoz, G., Straubhaar, J., Chugunova, T., Renard, P. (2014). Handling Soft Probabilities in Multiple Point Statistics Simulation. In: Pardo-Igúzquiza, E., Guardiola-Albert, C., Heredia, J., Moreno-Merino, L., Durán, J., Vargas-Guzmán, J. (eds) Mathematics of Planet Earth. Lecture Notes in Earth System Sciences. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32408-6_17
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DOI: https://doi.org/10.1007/978-3-642-32408-6_17
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