Generating geologically realistic 3D reservoir facies models using deep learning of sedimentary architecture with generative adversarial networks
Abstract This paper proposes a novel approach for generating 3-dimensional complex geological facies models based on deep generative models. It can reproduce a wide range of conceptual geological models while possessing the flexibility necessary to honor constraints such as well data. Compared with...
Guardado en:
Autores principales: | Tuan-Feng Zhang, Peter Tilke, Emilien Dupont, Ling-Chen Zhu, Lin Liang, William Bailey |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
KeAi Communications Co., Ltd.
2019
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Materias: | |
Acceso en línea: | https://doaj.org/article/2d915f0f0add477db016aee0965eb3c5 |
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