Unveiling the Effect of Complex Components on CO2-Oil Minimum Miscibility Pressure: Insights from Deep Convolutional Neural Networks

Author:

Fan Jiarui1,Yao Mingze2,Fan Zhiqiang3,Chen Peng4,He Kun56ORCID,Wang Dayong1ORCID

Affiliation:

1. Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, School of Energy and Power Engineering, Dalian University of Technology, Dalian 116023, P. R. China

2. Information Science and Technology College, Dalian Maritime University, Dalian 116026, P. R. China

3. School of Mechanics, Civil Engineering and Architecture, Northwestern Polytechnical University, Xi’an 710072, P. R. China

4. Research Institute of Drilling and Production, Liaohe Oilfield of PetroChina, Panjin 124010, P. R. China

5. Research Institute of Petroleum Exploration and Development, PetroChina, Beijing 100083, P. R. China

6. National Key Laboratory of Continental Shale Oil, Daqing 163002,, P. R. China

Funder

National Natural Science Foundation of China

Key Research and Development Projects of Shaanxi Province

Dalian Leading Academic and Key Plan Project

Publisher

American Chemical Society (ACS)

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