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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:

A new robust predictive model for lost circulation rate using convolutional neural network: A case study from Marun Oilfield
Farshad Jafarizadeh, Babak Larki, Bamdad Kazemi, et al.
Petroleum (2022) Vol. 9, Iss. 3, pp. 468-485
Open Access | Times Cited: 18

Showing 18 citing articles:

Machine-learning predictions of solubility and residual trapping indexes of carbon dioxide from global geological storage sites
Shadfar Davoodi, Hung Vo Thanh, David A. Wood, et al.
Expert Systems with Applications (2023) Vol. 222, pp. 119796-119796
Closed Access | Times Cited: 58
Predicting uniaxial compressive strength from drilling variables aided by hybrid machine learning
Shadfar Davoodi, Mohammad Mehrad, David A. Wood, et al.
International Journal of Rock Mechanics and Mining Sciences (2023) Vol. 170, pp. 105546-105546
Closed Access | Times Cited: 28
Artificial intelligence for drilling lost circulation: A systematic literature review
Haytham H. Elmousalami, Ibrahim Sakr
Geoenergy Science and Engineering (2024) Vol. 239, pp. 212837-212837
Closed Access | Times Cited: 12
Predicting Loss of Circulation During Drilling Using Decision Trees and Ensemble Learning Algorithms
T. N. T. Tran, Quốc Hoàng, Ngan Le, et al.
Springer proceedings in physics (2025), pp. 256-260
Closed Access
Prediction of permeability of highly heterogeneous hydrocarbon reservoir from conventional petrophysical logs using optimized data-driven algorithms
Amirhossein Sheykhinasab, Amir Ali Mohseni, Arash Barahooie Bahari, et al.
Journal of Petroleum Exploration and Production Technology (2022) Vol. 13, Iss. 2, pp. 661-689
Open Access | Times Cited: 22
Noise Cancellation Method for Mud Pulse Telemetry Based on Discrete Fourier Transform
Jingchen Zhang, Zitong Sha, Xingbin Tu, et al.
Journal of Marine Science and Engineering (2025) Vol. 13, Iss. 1, pp. 75-75
Open Access
Advanced Optimized Deep-Learning Model for Precise Evaluation of Subsurface Carbon Dioxide Trapping Efficiency
Shadfar Davoodi, Promise O. Longe, N. V. Makarov, et al.
Energy & Fuels (2025)
Closed Access
Assessing formation loss of circulation risks with mud-log datasets: resampling and classifying imbalanced datasets
David A. Wood
Elsevier eBooks (2025), pp. 247-286
Closed Access
Automated lost circulation severity classification and mitigation system using explainable Bayesian optimized ensemble learning algorithms
Haytham H. Elmousalami, Ibrahim Sakr
Journal of Petroleum Exploration and Production Technology (2024) Vol. 14, Iss. 10, pp. 2735-2752
Open Access | Times Cited: 3
Combined Deep Learning and Optimization for Hydrogen-Solubility Prediction in Aqueous Systems Appropriate for Underground Hydrogen Storage Reservoirs
Promise O. Longe, Shadfar Davoodi, Mohammad Mehrad, et al.
Energy & Fuels (2024) Vol. 38, Iss. 22, pp. 22031-22049
Closed Access | Times Cited: 3
Prediction of Lost Circulation in Southwest Chinese Oil Fields Applying Improved WOA-BiLSTM
Xianming Liu, Jia Wen, Zhilin Li, et al.
Processes (2023) Vol. 11, Iss. 9, pp. 2763-2763
Open Access | Times Cited: 7
Performance Comparison of Artificial Neural Network and Random Forest Models for Predicting the Compressive Strength of Fibre-Reinforced GGBS-Based Geopolymer Concrete Composites
Shimol Philip, M. Nidhi
Materials Circular Economy (2024) Vol. 6, Iss. 1
Closed Access | Times Cited: 1
Explainable machine-learning-based prediction of equivalent circulating density using surface-based drilling data
Gerald Kelechi Ekechukwu, Abayomi Adejumo
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Machine learning algorithm optimization for intelligent prediction of rock thermal conductivity: A case study from a whole-cored scientific drilling borehole
Yumao Pang, Bingbing Shi, Xingwei Guo, et al.
Geothermics (2023) Vol. 111, pp. 102711-102711
Closed Access | Times Cited: 4
Genetic programming application in predicting fluid loss severity
Mohamed Amish, Eta Etta-Agbor
Results in Engineering (2023) Vol. 20, pp. 101464-101464
Open Access | Times Cited: 4
A new approach to mechanical brittleness index modeling based on conventional well logs using hybrid algorithms
Milad Zamanzadeh Talkhouncheh, Shadfar Davoodi, Babak Larki, et al.
Earth Science Informatics (2023) Vol. 16, Iss. 4, pp. 3387-3416
Closed Access | Times Cited: 3
Prediction of plugging formulation based on PSO‐BP optimization neural network
Xudong Wang, Ye Chen, Mei Huang, et al.
Engineering Reports (2024) Vol. 6, Iss. 11
Closed Access
Lost Circulation Intensity Characterization in Drilling Operations: Leveraging Machine Learning and Well Log Data
Ahmad Azadivash
Heliyon (2024) Vol. 11, Iss. 1, pp. e41059-e41059
Closed Access
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