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Abdollahifard, Mohammad Javad, Baharvand, Mohammad, Mariéthoz, Grégoire (2019) Efficient training image selection for multiple-point geostatistics via analysis of contours. Computers & Geosciences, 128. 41-50 doi:10.1016/j.cageo.2019.04.004

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Reference TypeJournal (article/letter/editorial)
TitleEfficient training image selection for multiple-point geostatistics via analysis of contours
JournalComputers & Geosciences
AuthorsAbdollahifard, Mohammad JavadAuthor
Baharvand, MohammadAuthor
Mariéthoz, GrégoireAuthor
Year2019 (July)Volume128
PublisherElsevier BV
DOIdoi:10.1016/j.cageo.2019.04.004Search in ResearchGate
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Mindat Ref. ID455887Long-form Identifiermindat:1:5:455887:7
GUID0
Full ReferenceAbdollahifard, Mohammad Javad, Baharvand, Mohammad, Mariéthoz, Grégoire (2019) Efficient training image selection for multiple-point geostatistics via analysis of contours. Computers & Geosciences, 128. 41-50 doi:10.1016/j.cageo.2019.04.004
Plain TextAbdollahifard, Mohammad Javad, Baharvand, Mohammad, Mariéthoz, Grégoire (2019) Efficient training image selection for multiple-point geostatistics via analysis of contours. Computers & Geosciences, 128. 41-50 doi:10.1016/j.cageo.2019.04.004
In(2019) Computers & Geosciences Vol. 128. Elsevier BV

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Abdollahifard, Mohammad J. (2016) Fast multiple-point simulation using a data-driven path and an efficient gradient-based search. Computers & Geosciences, 86. 64-74 doi:10.1016/j.cageo.2015.10.010
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Feng, Wenjie, Wu, Shenghe, Yin, Yanshu, Zhang, Jiajia, Zhang, Ke (2017) A training image evaluation and selection method based on minimum data event distance for multiple-point geostatistics. Computers & Geosciences, 104. 35-53 doi:10.1016/j.cageo.2017.04.004
Levy, Shiran, Friedli, Lea, Mariéthoz, Grégoire, Linde, Niklas (2024) Conditioning of multiple-point statistics simulations to indirect geophysical data. Computers & Geosciences, 187. 105581 doi:10.1016/j.cageo.2024.105581
Abdollahifard, Mohammad J., Nasiri, Behrooz (2017) Exploiting transformation-domain sparsity for fast query in multiple-point geostatistics. Computational Geosciences, 21. 289-299 doi:10.1007/s10596-016-9612-1
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