Surrogate permeability modelling of low -permeable rocks using convolutional neural networks

被引：0
|
作者：
Tian, Jianwei [1 ]
Qi, Chongchong [2 ]
Sun, Yingfeng [3 ]
Yaseen, Zaher Mundher [4 ]
机构：
[1] Univ Western Australia, Sch Engn, Perth, WA 6009, Australia
[2] Cent South Univ, Sch Resources & Safety Engn, Changsha 410083, Peoples R China
[3] China Univ Min & Technol, Sch Emergency Management & Safety Engn, Beijing 100083, Peoples R China
[4] Ton Duc Thang Univ, Fac Civil Engn, Sustainable Dev Civil Engn Res Grp, Ho Chi Minh City, Vietnam
来源：
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING | 2020年 / 366卷
关键词：
PORE STRUCTURE CHARACTERIZATION; ENHANCED GAS RECOVERY; DIGITAL ROCK; POROUS-MEDIA; CO2; STORAGE; SHALE; COAL; TRANSPORT; PREDICTION; RESERVOIR;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
引用
收藏
页数：15
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