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A Deep-Learning-Based Approach for Reservoir Production Forecast under Uncertainty
  • 2024-01-08
元数据
名   称 A Deep-Learning-Based Approach for Reservoir Production Forecast under Uncertainty
科技资源标识 CSTR:11738.14.NCDC.XDA14.PP5730.2024
DOI 10.2118/205000-PA
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摘   要 This paper presents a deep-learning-based proxy modeling approach to efficiently forecast reservoir pressure and fluid saturation in heterogeneous reservoirs during waterflooding.
学科分类
170.50
关键词
coupled generative adversarial network permeability deep-learning-based
作者 Zhi Zhong,Alexander Y. Sun,Bo Ren,Yanyong Wang
论文类型： journal
论文网址： https://onepetro.org/SJ/article/26/03/1314/455290/A-Deep-Learning-Based-Approach-for-Reservoir
期刊名称： SPE Journal
出版时间： 2021-09-01
引用和标注
数据引用
Zhi Zhong,Alexander Y. Sun,Bo Ren,Yanyong Wang. A Deep-Learning-Based Approach for Reservoir Production Forecast under Uncertainty. 国家冰川冻土沙漠科学数据中心(http://www.ncdc.ac.cn), 2024. https://cstr.cn/CSTR:11738.14.NCDC.XDA14.PP5730.2024.
Zhi Zhong,Alexander Y. Sun,Bo Ren,Yanyong Wang. A Deep-Learning-Based Approach for Reservoir Production Forecast under Uncertainty. 国家冰川冻土沙漠科学数据中心(http://www.ncdc.ac.cn), 2024. https://www.doi.org/10.2118/205000-PA.
许可协议
知识共享许可协议   本作品采用 知识共享署名 4.0 国际许可协议进行许可。
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