Data-Driven Proxy Modeling of Water Front Propagation in Porous Media-Reference-Cited by-同舟云学术

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Data-Driven Proxy Modeling of Water Front Propagation in Porous Media

Published:2022-07-03 Issue:6 Volume:36 Page:465-487
ISSN:1061-8562
Container-title:International Journal of Computational Fluid Dynamics
language:en
Short-container-title:International Journal of Computational Fluid Dynamics

Author:

Saberali Behzad¹^ORCID,Zhang Kai¹^ORCID,Golsanami Naser²³^ORCID

Affiliation:

1. School of Petroleum Engineering, China University of Petroleum (East China), Qingdao, People’s Republic of China

2. State Key Laboratory of Mining Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao, People’s Republic of China

3. College of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao, People’s Republic of China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shandong Province

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Mechanics of Materials,Energy Engineering and Power Technology,Condensed Matter Physics,Aerospace Engineering,Computational Mechanics

Link

https://www.tandfonline.com/doi/pdf/10.1080/10618562.2022.2153835

Reference54 articles.

1. Application of Machine Learning and Artificial Intelligence in Proxy Modeling for Fluid Flow in Porous Media

2. Development Of Proxy Models For Reservoir Simulation By Sparsity Promoting Methods And Machine Learning Techniques

3. Mechanism of Fluid Displacement in Sands

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