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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:

Gaussian mixture model deep neural network and its application in porosity prediction of deep carbonate reservoir
Yingying Wang, Liping Niu, Luanxiao Zhao, et al.
Geophysics (2021) Vol. 87, Iss. 2, pp. M59-M72
Closed Access | Times Cited: 21

Showing 21 citing articles:

Probabilistic inversion of seismic data for reservoir petrophysical characterization: Review and examples
Darío Graña, Leonardo Azevedo, Leandro de Figueiredo, et al.
Geophysics (2022) Vol. 87, Iss. 5, pp. M199-M216
Closed Access | Times Cited: 53
Porosity prediction through well logging data: A combined approach of convolutional neural network and transformer model (CNN-transformer)
Youzhuang Sun, Shanchen Pang, Junhua Zhang, et al.
Physics of Fluids (2024) Vol. 36, Iss. 2
Open Access | Times Cited: 11
Application of the dynamic transformer model with well logging data for formation porosity prediction
Youzhuang Sun, Shanchen Pang, Yong-An Zhang, et al.
Physics of Fluids (2024) Vol. 36, Iss. 3
Open Access | Times Cited: 5
Quantitative ultrasonic characterization of fractal-based pore distribution homogeneity with variable observation scales in heterogeneous medium
Lin Li, Yijia Chen, Zhiyuan Ma, et al.
Ultrasonics (2025) Vol. 149, pp. 107596-107596
Closed Access
Seismic Porosity Prediction in Tight Carbonate Reservoirs Based on a Spatiotemporal Neural Network
Fei Li, Zhiyi Yu, Wang Yong-gang, et al.
Processes (2025) Vol. 13, Iss. 3, pp. 788-788
Open Access
Rapid Estimation of Truck Cycle Time in Open-Pit Mine Haulage Based on Feature-Optimized Machine Learning
Chengkai Fan, Na Zhang, Bei Jiang, et al.
Mining Metallurgy & Exploration (2025)
Closed Access
A data-driven workflow based on multisource transfer machine learning for gas-bearing probability distribution prediction: A case study
Jiuqiang Yang, Niantian Lin, Kai Zhang, et al.
Geophysics (2023) Vol. 88, Iss. 4, pp. B163-B177
Closed Access | Times Cited: 9
Estimating pore pressure in tight sandstone gas reservoirs: A comprehensive approach integrating rock physics models and deep neural networks
Han Jin, Cai Liu, Zhiqi Guo
Journal of Applied Geophysics (2024), pp. 105526-105526
Closed Access | Times Cited: 2
Porosity: Some characterization techniques
Marly Terezinha Quadri Simões da Silva, Felipe Perretto, Marianna do Rocio Cardoso, et al.
Materials Today Proceedings (2023)
Closed Access | Times Cited: 6
Seismic prediction of porosity in tight reservoirs based on transformer
Zhaodong Su, Junxing Cao, Tao Xiang, et al.
Frontiers in Earth Science (2023) Vol. 11
Open Access | Times Cited: 6
Porosity estimation based on the shear modulus inversion of seismic shear wave
Fucai Dai, Feng Zhang, Xiangyang Li, et al.
Geophysics (2024) Vol. 89, Iss. 5, pp. M123-M135
Closed Access | Times Cited: 1
Heterogeneous reservoir prediction of ultra-deep strike-slip fault-damaged zone constrained with local seismic anomaly data
Xiangwen Li, Jingye Li, Xukui Feng, et al.
Earth Science Informatics (2022) Vol. 15, Iss. 3, pp. 1427-1441
Closed Access | Times Cited: 4
Application of machine learning in corrosion inhibition study
R. Dorothy, Thankappan Sasilatha, S. Rajendran, et al.
Zastita materijala (2022) Vol. 63, Iss. 3, pp. 280-290
Open Access | Times Cited: 4
Accurate identification of traps and pinch-outs on a stratigraphic reservoir-A case from Hala’alate Mountain in the Junggar Basin, China
Xinshuai Li, Xuesong Yang, Huilai Wang, et al.
PLoS ONE (2024) Vol. 19, Iss. 5, pp. e0303467-e0303467
Open Access
Ensemble of Neural Networks Utilizing Seismic Attributes for Rock‐Property Inversion With Uncertainty Estimation
Joseph Munezero Ntibahanana, S. Jianguo, Moïse Luemba, et al.
Earth and Space Science (2024) Vol. 11, Iss. 6
Open Access
Enhancing seismic porosity estimation through 3D sequence-to-sequence deep learning with data augmentation, spatial constraints, and geologic constraints
Minghui Xu, Luanxiao Zhao, Jingyu Liu, et al.
Geophysics (2024) Vol. 89, Iss. 4, pp. M93-M108
Closed Access
Phlogopite 40Ar/39Ar Geochronology for Guodian Skarn Fe Deposit in Qihe–Yucheng District, Luxi Block, North China Craton: A Link between Craton Destruction and Fe Mineralization
Qiwei Feng, Mingbo Gao, Chao Fu, et al.
Minerals (2024) Vol. 14, Iss. 7, pp. 690-690
Open Access
Joint inversion for facies and petrophysical properties based on a bi‐level optimization model
Wen Jin, Dinghui Yang, Yuanfeng Cheng, et al.
Geophysical Prospecting (2023)
Closed Access | Times Cited: 1
Probabilistic seismic inversion based on physics-guided deep mixture density network
Qianhao Sun, Zhaoyun Zong, Xin Li
Petroleum Science (2023) Vol. 21, Iss. 3, pp. 1611-1631
Open Access
Effective Porosity Seismic Inversion for Porous Media Saturated with an Ideal Fluid Using Simulated Annealing
Dongyong Zhou, Xiaotao Wen, Xilei He, et al.
Lithosphere (2022) Vol. 2022, Iss. Special 12
Open Access
Networks, obstacles, and resources for innovative performance: An analysis via neural networks for prediction in the manufacturing industry
Fernando Barrios Aguirre, Sandra Sanchís Mora, Luis Gabriel Gutiérrez Bernal, et al.
Journal of technology management & innovation (2022) Vol. 17, Iss. 4, pp. 40-47
Open Access
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