Shale anisotropy model building based on deep neural networks
Author:
Affiliation:
1. Department of Civil and Environmental Engineering, National University of Singapore
Publisher
Society of Exploration Geophysicists
Link
https://library.seg.org/doi/pdf/10.1190/segam2019-3215466.1
Reference14 articles.
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2. Bestagini, P., V. Lipari, and S. Tubaro, 2017, A machine learning approach to facies classification using well logs: 87th Annual International Meeting, SEG, Expanded Abstracts, 2137–2142, doi: 10.1190/segam2017-17729805.1.
3. Cáceres, A., X. Emery, and R. Riquelme, 2010, Truncated Gaussian kriging as an alternative to indicator kriging: Proceeding of 4th International Conference on Mining Innovation, Santiago, Chile, 23–25.
4. Crack models for a transversely isotropic medium
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1. Study the elastic properties and the anisotropy of rocks using different machine learning methods;Geophysical Prospecting;2020-07-31
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