Integration of Domain Knowledge and Data-Driven Modeling Evaluation Process for Predicting Minimum Miscible Pressure of CO<sub>2</sub>–Oil Systems in CCUS-Reference-Cited by-同舟云学术

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Integration of Domain Knowledge and Data-Driven Modeling Evaluation Process for Predicting Minimum Miscible Pressure of CO₂–Oil Systems in CCUS

Published:2023-11-21 Issue:23 Volume:37 Page:18652-18665
ISSN:0887-0624
Container-title:Energy & Fuels
language:en
Short-container-title:Energy Fuels

Author:

Zhang Xing¹,Xu Hang¹^ORCID,Wang Kunjuan²,Yang Shenglai³,Shen Bin³,Zhao Ruiming⁴,Guo Huiying⁵,Zhang Yuankai⁵,Gao Xinyuan³

Affiliation:

1. College of Petroleum, China University of Petroleum, Beijing at Karamay 834000, PR China

2. College of Information Science and Engineering, China University of Petroleum, Beijing 102249, PR China

3. China University of Petroleum, Beijing 102249, PR China

4. Sinopec Northwest Oilfield Branch, Urumqi 830000, PR China

5. China National Petroleum Corp Xinjiang Oil Field Research Institute of Petroleum Exploration and Development, Karamay 834000, PR China

Funder

Natural Science Foundation of Xinjiang Province

Publisher

American Chemical Society (ACS)

Subject

Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.energyfuels.3c03292

Reference42 articles.

1. Influence of Reservoir Spatial Heterogeneity on a Multicoupling Process of CO₂Geological Storage

2. World Carbon Dioxide Emissions: 1950–2050

3. Status and progress of worldwide EOR field applications

4. Estimation of minimum miscibility pressure during CO2 flooding in hydrocarbon reservoirs using an optimized neural network

5. The genetic algorithm based back propagation neural network for MMP prediction in CO2-EOR process

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Determination of Gas–Oil minimum miscibility pressure for impure CO2 through optimized machine learning models;Geoenergy Science and Engineering;2024-11

2. Utilizing Artificial Intelligence Techniques for Modeling Minimum Miscibility Pressure in Carbon Capture and Utilization Processes: A Comprehensive Review and Applications;Energy & Fuels;2024-07-25

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