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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Predicting minimum miscible pressure in pure CO2 flooding using machine learning: Method comparison and sensitivity analysis
Harith F. Al-Khafaji, Qingbang Meng, Wakeel Hussain, et al.
Fuel (2023) Vol. 354, pp. 129263-129263
Closed Access | Times Cited: 21

Showing 21 citing articles:

Development of multiple explicit data-driven models for accurate prediction of CO2 minimum miscibility pressure
Saad Alatefi, Okorie E. Agwu, Reda Abdel Azim, et al.
Process Safety and Environmental Protection (2024) Vol. 205, pp. 672-694
Closed Access | Times Cited: 11
Comprehensive Review of the Determination and Reduction of the Minimum Miscibility Pressure during CO2 Flooding
Guoliang Song, Y. Gloria Meng, Chengli Zhang, et al.
ACS Omega (2024) Vol. 9, Iss. 13, pp. 14747-14765
Open Access | Times Cited: 9
A Comprehensive Summary of the Application of Machine Learning Techniques for CO2-Enhanced Oil Recovery Projects
Xuejia Du, Sameer Salasakar, Ganesh Thakur
Machine Learning and Knowledge Extraction (2024) Vol. 6, Iss. 2, pp. 917-943
Open Access | Times Cited: 9
Determination of minimum miscibility and near-miscibility pressures for CO2-oil mixtures in shale reservoirs
Yilei Song, Zhaojie Song, Yasi Mo, et al.
Fuel (2025) Vol. 388, pp. 134531-134531
Closed Access | Times Cited: 1
Performance Prediction and Heating Parameter Optimization of Organic-Rich Shale In Situ Conversion Based on Numerical Simulation and Artificial Intelligence Algorithms
Yaqian Liu, Chuanjin Yao, Baishuo Liu, et al.
ACS Omega (2024) Vol. 9, Iss. 13, pp. 15511-15526
Open Access | Times Cited: 6
Determination of Gas–Oil minimum miscibility pressure for impure CO2 through optimized machine learning models
Chenyu Wu, Lu Jin, Jin Zhao, et al.
Geoenergy Science and Engineering (2024) Vol. 242, pp. 213216-213216
Closed Access | Times Cited: 6
RNN-based CO2 minimum miscibility pressure (MMP) estimation for EOR and CCUS applications
Erfan Mohammadian, Mohamad Mohamadi‐Baghmolaei, Reza Azin, et al.
Fuel (2023) Vol. 360, pp. 130598-130598
Closed Access | Times Cited: 13
Utilizing Artificial Intelligence Techniques for Modeling Minimum Miscibility Pressure in Carbon Capture and Utilization Processes: A Comprehensive Review and Applications
Menad Nait Amar, Hakim Djema, Khaled Ourabah, et al.
Energy & Fuels (2024) Vol. 38, Iss. 16, pp. 14891-14924
Closed Access | Times Cited: 5
A Reliable Model for Predicting Methane Solubility in Brine: Toward Effective Methane Emission Mitigation
Menad Nait Amar, Hakim Djema, Fahd Mohamad Alqahtani, et al.
Energy & Fuels (2025)
Closed Access
Enhancing reservoir characterization: A novel machine learning approach for automated detection and reconstruction of outliers-affected well log curves
Wakeel Hussain, Miao Luo, Muhammad Ali, et al.
Physics of Fluids (2025) Vol. 37, Iss. 3
Closed Access
Developing Robust Machine Learning Techniques to Predict Oil Recovery: A Comprehensive Field and Experimental Study
Wahib Yahya, Baolin Yang, Ayman Mutahar AlRassas, et al.
Geoenergy Science and Engineering (2025), pp. 213853-213853
Closed Access
A comprehensive review of minimum miscibility pressure determination and reduction strategies between CO2 and crude oil in CCUS processes
Zhuo Chen, Jiahui Chen, Xin Zhang
Fuel (2024) Vol. 384, pp. 134053-134053
Closed Access | Times Cited: 4
The Effect of Small Molecule Gas-Soluble Polymers on Minimum Miscibility Pressure During CO2 Injection
Farshid Torabi, Asghar Gandomkar
SPE Improved Oil Recovery Conference (2024)
Closed Access | Times Cited: 3
Modeling wax disappearance temperature using robust white-box machine learning
Menad Nait Amar, Noureddine Zeraibi, Chahrazed Benamara, et al.
Fuel (2024) Vol. 376, pp. 132703-132703
Closed Access | Times Cited: 3
Progress in carbon dioxide capture, storage and monitoring in geological landform
Phakamile Ndlovu, Rendani Bulannga, Liberty L. Mguni
Frontiers in Energy Research (2024) Vol. 12
Open Access | Times Cited: 3
Improved Least Squares Support Vector Machine Model Based on Grey Wolf Optimizer Algorithm for Predicting CO2–Crude Oil Minimum Miscibility Pressure
J. M. Li, Xiaoqiang Bian
Energy Technology (2024) Vol. 12, Iss. 5
Closed Access | Times Cited: 1
A Comprehensive Summary of the Application of Machine Learning Techniques for CO<sub>2</sub>-EOR Projects
Xuejia Du, Sameer Salasakar, Ganesh Thakur
(2024)
Open Access | Times Cited: 1
A point-interval prediction framework for minimum miscibility pressure of CO2-crude oil systems
Haoyu Chen, Yong Zheng, Hai Huang, et al.
Fuel (2024) Vol. 381, pp. 133573-133573
Closed Access | Times Cited: 1
Integration of Domain Knowledge and Data-Driven Modeling Evaluation Process for Predicting Minimum Miscible Pressure of CO2–Oil Systems in CCUS
Xing Zhang, Hang Xu, Kunjuan Wang, et al.
Energy & Fuels (2023) Vol. 37, Iss. 23, pp. 18652-18665
Closed Access | Times Cited: 3
Twofold Machine-Learning and Molecular Dynamics: A Computational Framework
Christos Stavrogiannis, Filippos Sofos, Maria Sagri, et al.
Computers (2023) Vol. 13, Iss. 1, pp. 2-2
Open Access | Times Cited: 2
Microscale Multiphase Oil Displacement Simulation and Experimental Study Based on Microfluidics Approach
Jianshan Li, Xiao Qu, Xiao‐Bing Lu, et al.
Geoenergy Science and Engineering (2024) Vol. 244, pp. 213529-213529
Closed Access
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