Multiple Point Statistics: A Review

作者: Pejman Tahmasebi

DOI: 10.1007/978-3-319-78999-6_30

关键词:

摘要: Geostatistical modeling is one of the most important tools for building an ensemble probable realizations in earth science. Among them, multiple-point statistics (MPS) has recently gone under a remarkable progress handling complex and more realistic phenomenon that can produce large amount expected uncertainty variability. Such progresses are mostly due to recent increase advanced computational techniques/power. In this review chapter, developments MPS thoroughly reviewed. Furthermore, advantages disadvantages each method discussed as well. Finally, chapter provides brief on current challenges paths might be considered future research.

参考文章(87)
Julien Straubhaar, Alexandre Walgenwitz, Philippe Renard, Parallel Multiple-Point Statistics Algorithm Based on List and Tree Structures Mathematical Geosciences. ,vol. 45, pp. 131- 147 ,(2013) , 10.1007/S11004-012-9437-Y
N. Sheehan, S. Torquato, Generating microstructures with specified correlation functions Journal of Applied Physics. ,vol. 89, pp. 53- 60 ,(2001) , 10.1063/1.1327609
Helge H. Haldorsen, Elvind Damsleth, Stochastic Modeling (includes associated papers 21255 and 21299 ) Journal of Petroleum Technology. ,vol. 42, pp. 404- 412 ,(1990) , 10.2118/20321-PA
Håkon Toftaker, Håkon Tjelmeland, Construction of Binary Multi-grid Markov Random Field Prior Models from Training Images Mathematical Geosciences. ,vol. 45, pp. 383- 409 ,(2013) , 10.1007/S11004-013-9456-3
J. H. Fang, P. P. Wang, Random field generation using simulated annealing vs. fractal-based stochastic interpolation Mathematical Geosciences. ,vol. 29, pp. 849- 858 ,(1997) , 10.1007/BF02768905
Julián M. Ortiz, Clayton V. Deutsch, Indicator Simulation Accounting for Multiple-Point Statistics Mathematical Geosciences. ,vol. 36, pp. 545- 565 ,(2004) , 10.1023/B:MATG.0000037736.00489.B5
Oscar Peredo, Julián M. Ortiz, Parallel implementation of simulated annealing to reproduce multiple-point statistics Computers & Geosciences. ,vol. 37, pp. 1110- 1121 ,(2011) , 10.1016/J.CAGEO.2010.10.015
Clayton V. Deutsch, Libing Wang, Hierarchical object-based stochastic modeling of fluvial reservoirs Mathematical Geosciences. ,vol. 28, pp. 857- 880 ,(1996) , 10.1007/BF02066005