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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:

Efficient deep-learning-based history matching for fluvial channel reservoirs
Suryeom Jo, Hoonyoung Jeong, Baehyun Min, et al.
Journal of Petroleum Science and Engineering (2021) Vol. 208, pp. 109247-109247
Closed Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Convolutional – recurrent neural network proxy for robust optimization and closed-loop reservoir management
Yong Do Kim, Louis J. Durlofsky
Computational Geosciences (2023) Vol. 27, Iss. 2, pp. 179-202
Closed Access | Times Cited: 24
Leveraging machine learning in porous media
Mostafa Delpisheh, Benyamin Ebrahimpour, Abolfazl Fattahi, et al.
Journal of Materials Chemistry A (2024) Vol. 12, Iss. 32, pp. 20717-20782
Open Access | Times Cited: 8
Fourier Neural Operator for Solving Subsurface Oil/Water Two-Phase Flow Partial Differential Equation
Kai Zhang, Yuande Zuo, Hanjun Zhao, et al.
SPE Journal (2022) Vol. 27, Iss. 03, pp. 1815-1830
Closed Access | Times Cited: 37
Reservoir automatic history matching: Methods, challenges, and future directions
Piyang Liu, Kai Zhang, Jun Yao
ADVANCES IN GEO-ENERGY RESEARCH (2023) Vol. 7, Iss. 2, pp. 136-140
Open Access | Times Cited: 20
A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach
Hongsheng Wang, Seyyed A. Hosseini, Alexandre M. Tartakovsky, et al.
Journal of Hydrology (2024) Vol. 636, pp. 131219-131219
Closed Access | Times Cited: 6
A Machine Learning-Based Approach to Automatic Multi-Model History Matching and Dynamic Prediction
Feng Guoqing, Mo Haishuai, Baofeng Wu, et al.
Arabian Journal for Science and Engineering (2025)
Closed Access
Learning-based pattern-data-driven forecast approach for predicting future well responses
Youngjoo Kim, Baehyun Min, Alexander Y. Sun, et al.
Journal of Petroleum Exploration and Production Technology (2025) Vol. 15, Iss. 2
Open Access
Applications of Geological Features Style Mixing for Reservoir History Matching
Seongin Ahn, Jonggeun Choe
SPE Journal (2025), pp. 1-19
Closed Access
Artificial intelligence in geoenergy: bridging petroleum engineering and future-oriented applications
Sungil Kim, Tea-Woo Kim, Suryeom Jo
Journal of Petroleum Exploration and Production Technology (2025) Vol. 15, Iss. 2
Open Access
Improved history matching of channelized reservoirs using a novel deep learning-based parametrization method
Reza Yousefzadeh, Mohammad Ahmadi
Geoenergy Science and Engineering (2023) Vol. 229, pp. 212113-212113
Closed Access | Times Cited: 12
Applications of Machine Learning in Subsurface Reservoir Simulation—A Review—Part I
Anna Samnioti, Vassilis Gaganis
(2023)
Open Access | Times Cited: 11
Adaptive Proxy-based Robust Production Optimization with Multilayer Perceptron
Cuthbert Shang Wui Ng, Ashkan Jahanbani Ghahfarokhi
Applied Computing and Geosciences (2022) Vol. 16, pp. 100103-100103
Open Access | Times Cited: 16
A review on optimization algorithms and surrogate models for reservoir automatic history matching
Yu-Long Zhao, Ruike Luo, Longxin Li, et al.
Geoenergy Science and Engineering (2023) Vol. 233, pp. 212554-212554
Closed Access | Times Cited: 9
A novel framework for predicting non-stationary production time series of shale gas based on BiLSTM-RF-MPA deep fusion model
Bin Liang, Jiang Liu, Lixia Kang, et al.
Petroleum Science (2024) Vol. 21, Iss. 5, pp. 3326-3339
Open Access | Times Cited: 3
An efficient transformer-based surrogate model with end-to-end training strategies for automatic history matching
Jinding Zhang, Jinzheng Kang, Kai Zhang, et al.
Geoenergy Science and Engineering (2024) Vol. 240, pp. 212994-212994
Closed Access | Times Cited: 2
Prediction of liquid surge volumes and flow rates for gas wells using machine learning
Youngwoo Yun, Tea-Woo Kim, Saebom Hwang, et al.
Journal of Natural Gas Science and Engineering (2022) Vol. 108, pp. 104802-104802
Closed Access | Times Cited: 9
Efficient Surrogate Modeling Based on Improved Vision Transformer Neural Network for History Matching
Daowei Zhang, Heng Li
SPE Journal (2023) Vol. 28, Iss. 06, pp. 3046-3062
Closed Access | Times Cited: 5
Intelligent Optimization of Gas Flooding Based on Multi-Objective Approach for Efficient Reservoir Management
Meng Gao, Chenji Wei, Xiangguo Zhao, et al.
Processes (2023) Vol. 11, Iss. 7, pp. 2226-2226
Open Access | Times Cited: 4
On the feasibility of an ensemble multi-fidelity neural network for fast data assimilation for subsurface flow in porous media
Yating Wang, Bicheng Yan
Expert Systems with Applications (2024), pp. 125774-125774
Closed Access | Times Cited: 1
Applications of Machine Learning in Subsurface Reservoir Simulation—A Review—Part I
Anna Samnioti, Vassilis Gaganis
Energies (2023) Vol. 16, Iss. 16, pp. 6079-6079
Open Access | Times Cited: 3
A Comparative Study for Deep-Learning-Based Methods for Automated Reservoir Simulation
Alaa Maarouf, Sofiane Tahir, Shi Su, et al.
SPE Reservoir Characterisation and Simulation Conference and Exhibition (2023)
Closed Access | Times Cited: 2
Reliable Initial Model Selection for Efficient Characterization of Channel Reservoirs in Ensemble Kalman Filter
D. S. Kim, Youjun Lee, Jonggeun Choe
Journal of Energy Resources Technology (2023) Vol. 145, Iss. 12
Closed Access | Times Cited: 2
Deep-Learning-Based Surrogate Reservoir Model for History-Matching Optimization
Alaa Maarouf, Sofiane Tahir, Shi Su, et al.
Day 3 Tue, November 30, 2021 (2022)
Closed Access | Times Cited: 4
Generative geomodeling based on flow responses in latent space
Suryeom Jo, Seongin Ahn, Changhyup Park, et al.
Journal of Petroleum Science and Engineering (2022) Vol. 211, pp. 110177-110177
Closed Access | Times Cited: 3
Combined mechanistic and machine learning method for construction of oil reservoir permeability map consistent with well test measurements
Evgenii Kanin, A.A. Garipova, С. А. Боронин, et al.
Petroleum Research (2024)
Open Access
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