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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:

Evaluation of machine learning methods for lithology classification using geophysical data
Thiago Santi Bressan, Marcelo Kehl de Souza, Tiago Jonatan Girelli, et al.
Computers & Geosciences (2020) Vol. 139, pp. 104475-104475
Closed Access | Times Cited: 183

Showing 1-25 of 183 citing articles:

Prediction of rockhead using a hybrid N-XGBoost machine learning framework
Xing Zhu, Jian Chu, Kangda Wang, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2021) Vol. 13, Iss. 6, pp. 1231-1245
Open Access | Times Cited: 110
Lithology prediction from well log data using machine learning techniques: A case study from Talcher coalfield, Eastern India
Thinesh Kumar, Naresh Kumar Seelam, G. Srinivasa Rao
Journal of Applied Geophysics (2022) Vol. 199, pp. 104605-104605
Closed Access | Times Cited: 69
Utilizing integrated artificial intelligence for characterizing mineralogy and facies in a pre-salt carbonate reservoir, Santos Basin, Brazil, using cores, wireline logs, and multi-mineral petrophysical evaluation
Jean Carlos Rangel Gavidia, Guilherme Furlan Chinelatto, Mateus Basso, et al.
Geoenergy Science and Engineering (2023) Vol. 231, pp. 212303-212303
Closed Access | Times Cited: 48
Imputation of missing well log data by random forest and its uncertainty analysis
Runhai Feng, Darío Graña, Niels Balling
Computers & Geosciences (2021) Vol. 152, pp. 104763-104763
Closed Access | Times Cited: 82
A Data-Driven Approach for Lithology Identification Based on Parameter-Optimized Ensemble Learning
Zhixue Sun, Baosheng Jiang, Xiangling Li, et al.
Energies (2020) Vol. 13, Iss. 15, pp. 3903-3903
Open Access | Times Cited: 73
3D geological structure inversion from Noddy-generated magnetic data using deep learning methods
Jiateng Guo, Yunqiang Li, Mark Jessell, et al.
Computers & Geosciences (2021) Vol. 149, pp. 104701-104701
Closed Access | Times Cited: 65
A Comparative Study of Convolutional Neural Networks and Conventional Machine Learning Models for Lithological Mapping Using Remote Sensing Data
Hojat Shirmard, Ehsan Farahbakhsh, Elnaz Heidari, et al.
Remote Sensing (2022) Vol. 14, Iss. 4, pp. 819-819
Open Access | Times Cited: 64
A Comparison of Machine Learning Algorithms in Predicting Lithofacies: Case Studies from Norway and Kazakhstan
Timur Merembayev, Darkhan Kurmangaliyev, Bakhbergen E. Bekbauov, et al.
Energies (2021) Vol. 14, Iss. 7, pp. 1896-1896
Open Access | Times Cited: 62
Gas channels and chimneys prediction using artificial neural networks and multi-seismic attributes, offshore West Nile Delta, Egypt
Amir Ismail, Hatem Farouk Ewida, Sahar Nazeri, et al.
Journal of Petroleum Science and Engineering (2021) Vol. 208, pp. 109349-109349
Closed Access | Times Cited: 56
Performance evaluation of boosting machine learning algorithms for lithofacies classification in heterogeneous carbonate reservoirs
Watheq J. Al‐Mudhafar, Mohammed A. Abbas, David A. Wood
Marine and Petroleum Geology (2022) Vol. 145, pp. 105886-105886
Closed Access | Times Cited: 50
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
Well-Logging-Based Lithology Classification Using Machine Learning Methods for High-Quality Reservoir Identification: A Case Study of Baikouquan Formation in Mahu Area of Junggar Basin, NW China
Jun‐Long Zhang, Youbin He, Yuan Zhang, et al.
Energies (2022) Vol. 15, Iss. 10, pp. 3675-3675
Open Access | Times Cited: 40
Pattern Classification
Katherine L. Silversides
Encyclopedia of earth sciences series/Encyclopedia of earth sciences (2023), pp. 1061-1063
Closed Access | Times Cited: 40
Combination of Machine Learning and Kriging for Spatial Estimation of Geological Attributes
Gamze Erdogan Erten, Mahmut Yavuz, Clayton V. Deutsch
Natural Resources Research (2022) Vol. 31, Iss. 1, pp. 191-213
Closed Access | Times Cited: 39
Lithology identification using graph neural network in continental shale oil reservoirs: A case study in Mahu Sag, Junggar Basin, Western China
Guoqing Lu, Lianbo Zeng, Shaoqun Dong, et al.
Marine and Petroleum Geology (2023) Vol. 150, pp. 106168-106168
Closed Access | Times Cited: 35
Unsupervised machine learning and multi-seismic attributes for fault and fracture network interpretation in the Kerry Field, Taranaki Basin, New Zealand
Amir Ismail, Ahmed A. Radwan, Mahmoud Leila, et al.
Geomechanics and Geophysics for Geo-Energy and Geo-Resources (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 29
An automatic identification method of imbalanced lithology based on Deep Forest and K-means SMOTE
Xinyi Zhu, Hongbing Zhang, Quan Ren, et al.
Geoenergy Science and Engineering (2023) Vol. 224, pp. 211595-211595
Closed Access | Times Cited: 25
Coal structure identification based on geophysical logging data: Insights from Wavelet Transform (WT) and Particle Swarm Optimization Support Vector Machine (PSO-SVM) algorithms
Zhongzheng Tong, Yanjun Meng, Jinchuan Zhang, et al.
International Journal of Coal Geology (2023) Vol. 282, pp. 104435-104435
Closed Access | Times Cited: 23
Evaluating StackingC and ensemble models for enhanced lithological classification in geological mapping
Sasan Farhadi, Samuele Tatullo, Mina Boveiri Konari, et al.
Journal of Geochemical Exploration (2024) Vol. 260, pp. 107441-107441
Open Access | Times Cited: 11
When geoscience meets generative AI and large language models: Foundations, trends, and future challenges
Abdenour Hadid, Tanujit Chakraborty, D. Busby
Expert Systems (2024) Vol. 41, Iss. 10
Closed Access | Times Cited: 9
Mineral Prospectivity Mapping Based on a Novel Self-Ensembling Graph Convolutional Network
Yonghang Lou, Yue Liu
Mathematical Geosciences (2025)
Closed Access | Times Cited: 1
Artificial Intelligence and Machine Learning to enhance critical mineral deposit discovery
Rhys S. Davies, McLean Trott, Jaakko Georgi, et al.
Geosystems and Geoenvironment (2025), pp. 100361-100361
Open Access | Times Cited: 1
A machine learning methodology for multivariate pore-pressure prediction
H. Q. Yu, Guoxiong Chen, Hanming Gu
Computers & Geosciences (2020) Vol. 143, pp. 104548-104548
Closed Access | Times Cited: 59
A novel hybrid method of lithology identification based on k-means++ algorithm and fuzzy decision tree
Quan Ren, Hongbing zhang, Dailu Zhang, et al.
Journal of Petroleum Science and Engineering (2021) Vol. 208, pp. 109681-109681
Closed Access | Times Cited: 55
Random forests-based error-correction of streamflow from a large-scale hydrological model: Using model state variables to estimate error terms
Youchen Shen, Jessica Ruijsch, Meng Lü, et al.
Computers & Geosciences (2021) Vol. 159, pp. 105019-105019
Open Access | Times Cited: 55
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