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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:

Application of Machine Learning for Lithofacies Prediction and Cluster Analysis Approach to Identify Rock Type
Mazahir Hussain, Shuang Liu, Umar Ashraf, et al.
Energies (2022) Vol. 15, Iss. 12, pp. 4501-4501
Open Access | Times Cited: 47

Showing 1-25 of 47 citing articles:

Artificial intelligence-based prediction of hydrogen adsorption in various kerogen types: Implications for underground hydrogen storage and cleaner production
Hung Vo Thanh, Zhenxue Dai, Zhengyang Du, et al.
International Journal of Hydrogen Energy (2024) Vol. 57, pp. 1000-1009
Closed Access | Times Cited: 26
Hydraulic flow unit and rock types of the Asmari Formation, an application of flow zone index and fuzzy C-means clustering methods
Seyedeh Hajar Eftekhari, Mahmoud Memariani, Zahra Maleki, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 19
Reservoir rock typing assessment in a coal-tight sand based heterogeneous geological formation through advanced AI methods
Umar Ashraf, Wanzhong Shi, Hucai Zhang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 19
Reservoir Quality Prediction of Gas-Bearing Carbonate Sediments in the Qadirpur Field: Insights from Advanced Machine Learning Approaches of SOM and Cluster Analysis
Muhammad Rashid, Miao Luo, Umar Ashraf, et al.
Minerals (2022) Vol. 13, Iss. 1, pp. 29-29
Open Access | Times Cited: 53
Classification of reservoir quality using unsupervised machine learning and cluster analysis: Example from Kadanwari gas field, SE Pakistan
Nafees Ali, Jian Chen, Xiaodong Fu, et al.
Geosystems and Geoenvironment (2022) Vol. 2, Iss. 1, pp. 100123-100123
Open Access | Times Cited: 43
Seismic driven reservoir classification using advanced machine learning algorithms: A case study from the Lower Ranikot/Khadro sandstone gas reservoir, Kirthar Fold Belt, Lower Indus Basin, Pakistan
Umar Manzoor, Muhsan Ehsan, Ahmed E. Radwan, et al.
Geoenergy Science and Engineering (2023) Vol. 222, pp. 211451-211451
Closed Access | Times Cited: 33
Machine learning - a novel approach to predict the porosity curve using geophysical logs data: An example from the Lower Goru sand reservoir in the Southern Indus Basin, Pakistan
Wakeel Hussain, Miao Luo, Muhammad Ali, et al.
Journal of Applied Geophysics (2023) Vol. 214, pp. 105067-105067
Closed Access | Times Cited: 28
Smart predictive viscosity mixing of CO2–N2 using optimized dendritic neural networks to implicate for carbon capture utilization and storage
Ahmed A. Ewees, Hung Vo Thanh, Mohammed A. A. Al‐qaness, et al.
Journal of environmental chemical engineering (2024) Vol. 12, Iss. 2, pp. 112210-112210
Closed Access | Times Cited: 14
Employing Statistical Algorithms and Clustering Techniques to Assess Lithological Facies for Identifying Optimal Reservoir Rocks: A Case Study of the Mansouri Oilfields, SW Iran
Seyedeh Hajar Eftekhari, Mahmoud Memariani, Zahra Maleki, et al.
Minerals (2024) Vol. 14, Iss. 3, pp. 233-233
Open Access | Times Cited: 13
Multi-well clustering and inverse modeling-based approaches for exploring geometry, petrophysical, and hydrogeological parameters of the Quaternary aquifer system around Debrecen area, Hungary.
Musaab A. A. Mohammed, Norbert Péter Szabó, Yetzabbel G. Flores, et al.
Groundwater for Sustainable Development (2024) Vol. 24, pp. 101086-101086
Open Access | Times Cited: 10
Advanced AI approach for enhanced predictive modeling in reservoir characterization within complex geological environments
Wakeel Hussain, Muhammad Ali, Rakhshanda Sadaf, et al.
Modeling Earth Systems and Environment (2024) Vol. 10, Iss. 4, pp. 5043-5061
Closed Access | Times Cited: 10
A Comprehensive Study on Optimizing Reservoir Potential: Advanced Geophysical Log Analysis of Zamzama Gas Field, Southern Indus Basin, Pakistan
Saddam Hussain, Asad Atta, Chaohua Guo, et al.
Physics and Chemistry of the Earth Parts A/B/C (2024) Vol. 135, pp. 103640-103640
Closed Access | Times Cited: 9
Prospect Evaluation of the Cretaceous Yageliemu Clastic Reservoir Based on Geophysical Log Data: A Case Study from the Yakela Gas Condensate Field, Tarim Basin, China
Wakeel Hussain, Muhsan Ehsan, Lin Pan, et al.
Energies (2023) Vol. 16, Iss. 6, pp. 2721-2721
Open Access | Times Cited: 19
Quantitative Characterization of Shallow Marine Sediments in Tight Gas Fields of Middle Indus Basin: A Rational Approach of Multiple Rock Physics Diagnostic Models
Muhammad Ali, Umar Ashraf, Peimin Zhu, et al.
Processes (2023) Vol. 11, Iss. 2, pp. 323-323
Open Access | Times Cited: 17
Interactive machine learning for segmenting pores of sandstone in computed tomography images
Yan Zhang, Zhiping Li, Hao Wu
Gas Science and Engineering (2024) Vol. 126, pp. 205343-205343
Closed Access | Times Cited: 6
A Gamma-ray spectroscopy approach to evaluate clay mineral composition and depositional environment: A case study from the lower Goru Formation, Southern Indus Basin, Pakistan
Wakeel Hussain, Miao Luo, Muhammad Ali, et al.
Journal of Applied Geophysics (2024) Vol. 226, pp. 105414-105414
Closed Access | Times Cited: 6
Data-driven machine learning approaches for precise lithofacies identification in complex geological environments
Muhammad Ali, Peimin Zhu, Huolin Ma, et al.
Geo-spatial Information Science (2024), pp. 1-21
Open Access | Times Cited: 6
An optimized neuro-fuzzy system using advance nature-inspired Aquila and Salp swarm algorithms for smart predictive residual and solubility carbon trapping efficiency in underground storage formations
Mohammed A. A. Al‐qaness, Ahmed A. Ewees, Hung Vo Thanh, et al.
Journal of Energy Storage (2022) Vol. 56, pp. 106150-106150
Closed Access | Times Cited: 23
Analyzing the seismic attributes, structural and petrophysical analyses of the Lower Goru Formation: A case study from Middle Indus Basin Pakistan
Fodé Tounkara, Muhsan Ehsan, Muhammad Nasar Iqbal, et al.
Frontiers in Earth Science (2023) Vol. 10
Open Access | Times Cited: 14
A multidisciplinary approach to facies evaluation at regional level using well log analysis, machine learning, and statistical methods
Jar Ullah, Huan Li, Umar Ashraf, et al.
Geomechanics and Geophysics for Geo-Energy and Geo-Resources (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 13
Application of Deep Learning for Reservoir Porosity Prediction and self Organizing Map for Lithofacies Prediction
Mazahir Hussain, Shuang Liu, Wakeel Hussain, et al.
Journal of Applied Geophysics (2024) Vol. 230, pp. 105502-105502
Closed Access | Times Cited: 5
Machine Learning Based Reservoir Characterization and Numerical Modeling from Integrated Well Log and Core Data
Abdul-Muaizz Koray, Dung Bui, Emmanuel Appiah Kubi, et al.
Geoenergy Science and Engineering (2024) Vol. 243, pp. 213296-213296
Closed Access | Times Cited: 5
A novel machine learning approach for interpolating seismic velocity and electrical resistivity models for early-stage soil-rock assessment
Mbuotidem David Dick, Andy Anderson Bery, Nsidibe Ndarake Okonna, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 3, pp. 2629-2648
Closed Access | Times Cited: 4
Classifying lithofacies from well logs using supervised machine learning, cluster, and principal component analysis plus stacking model combinations
David A. Wood
Elsevier eBooks (2025), pp. 111-150
Closed Access
Physics-integrated neural networks for improved mineral volumes and porosity estimation from geophysical well logs
Prasad Pothana, Kegang Ling
Energy Geoscience (2025), pp. 100410-100410
Open Access
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