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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:

Predicting porosity, permeability, and tortuosity of porous media from images by deep learning
Krzysztof M. Graczyk, Maciej Matyka
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 110

Showing 1-25 of 110 citing articles:

An optimized XGBoost method for predicting reservoir porosity using petrophysical logs
Shaowei Pan, Zechen Zheng, Zhi Guo, et al.
Journal of Petroleum Science and Engineering (2021) Vol. 208, pp. 109520-109520
Closed Access | Times Cited: 176
Enhanced group method of data handling (GMDH) for permeability prediction based on the modified Levenberg Marquardt technique from well log data
Alvin K. Mulashani, Chuanbo Shen, Baraka Mathew Nkurlu, et al.
Energy (2021) Vol. 239, pp. 121915-121915
Closed Access | Times Cited: 75
Predicting permeability from 3D rock images based on CNN with physical information
Pengfei Tang, Dongxiao Zhang, Heng Li
Journal of Hydrology (2022) Vol. 606, pp. 127473-127473
Open Access | Times Cited: 57
Generalizable Permeability Prediction of Digital Porous Media via a Novel Multi‐Scale 3D Convolutional Neural Network
M.M.S. El-Morsy, Wael El‐Dakhakhni, Benzhong Zhao
Water Resources Research (2022) Vol. 58, Iss. 3
Closed Access | Times Cited: 39
Insights into the Application of Machine Learning in Reservoir Engineering: Current Developments and Future Trends
Hai Wang, Shengnan Chen
Energies (2023) Vol. 16, Iss. 3, pp. 1392-1392
Open Access | Times Cited: 24
Prediction of fluid flow in porous media by sparse observations and physics-informed PointNet
Ali Kashefi, Tapan Mukerji
Neural Networks (2023) Vol. 167, pp. 80-91
Open Access | Times Cited: 23
Tortuosity estimation and microstructure optimization of non-uniform porous heterogeneous electrodes
Zongli Chen, Ying Zhao
Journal of Power Sources (2024) Vol. 596, pp. 234095-234095
Closed Access | Times Cited: 11
Modeling transient natural convection in heterogeneous porous media with Convolutional Neural Networks
Adhish Guli Virupaksha, Thomas Nagel, François Lehmann, et al.
International Journal of Heat and Mass Transfer (2024) Vol. 222, pp. 125149-125149
Closed Access | Times Cited: 10
An improved convolutional neural network for predicting porous media permeability from rock thin sections
Shuo Zhai, Shaoyang Geng, Chengyong Li, et al.
Gas Science and Engineering (2024) Vol. 127, pp. 205365-205365
Closed Access | Times Cited: 8
Deep learning accelerated prediction of the permeability of fibrous microstructures
Barış Çağlar, Guillaume Broggi, Muhammad A. Ali, et al.
Composites Part A Applied Science and Manufacturing (2022) Vol. 158, pp. 106973-106973
Open Access | Times Cited: 33
Deep CNNs as universal predictors of elasticity tensors in homogenization
Bernhard Eidel
Computer Methods in Applied Mechanics and Engineering (2022) Vol. 403, pp. 115741-115741
Open Access | Times Cited: 32
Modelling of phenomena affecting blast furnace burden permeability using the Discrete Element Method (DEM) – A review
Raïsa Roeplal, Yusong Pang, Allert T. Adema, et al.
Powder Technology (2022) Vol. 415, pp. 118161-118161
Open Access | Times Cited: 29
Lab on a chip for a low-carbon future
Sujit S. Datta, Ilenia Battiato, Martin A. Fernø, et al.
Lab on a Chip (2023) Vol. 23, Iss. 5, pp. 1358-1375
Open Access | Times Cited: 22
Estimating permeability of 3D micro-CT images by physics-informed CNNs based on DNS
Stephan Gärttner, Faruk O. Alpak, Andreas Meier, et al.
Computational Geosciences (2023) Vol. 27, Iss. 2, pp. 245-262
Open Access | Times Cited: 19
Image segmentation and flow prediction of digital rock with U-net network
Fuyong Wang, Yun Zai
Advances in Water Resources (2023) Vol. 172, pp. 104384-104384
Closed Access | Times Cited: 19
Machine learning approaches for formation matrix volume prediction from well logs: Insights and lessons learned
Pamidi Venkata Durga Kannaiah, Neetish Kumar Maurya
Geoenergy Science and Engineering (2023) Vol. 229, pp. 212086-212086
Closed Access | Times Cited: 17
A self-supervised learning framework based on physics-informed and convolutional neural networks to identify local anisotropic permeability tensor from textiles 2D images for filling pattern prediction
John M. Hanna, José V. Aguado, Sébastien Comas-Cardona, et al.
Composites Part A Applied Science and Manufacturing (2024) Vol. 179, pp. 108019-108019
Open Access | Times Cited: 7
Physics-informed and data-driven discovery of governing equations for complex phenomena in heterogeneous media
Muhammad Sahimi
Physical review. E (2024) Vol. 109, Iss. 4
Open Access | Times Cited: 7
A computationally efficient modeling of flow in complex porous media by coupling multiscale digital rock physics and deep learning: Improving the tradeoff between resolution and field-of-view
Iman Nabipour, Amir Raoof, Veerle Cnudde, et al.
Advances in Water Resources (2024) Vol. 188, pp. 104695-104695
Open Access | Times Cited: 6
Active Darcy’s Law
Ryan R. Keogh, Timofey Kozhukhov, Kristian Thijssen, et al.
Physical Review Letters (2024) Vol. 132, Iss. 18
Open Access | Times Cited: 6
Point-cloud deep learning of porous media for permeability prediction
Ali Kashefi, Tapan Mukerji
Physics of Fluids (2021) Vol. 33, Iss. 9
Open Access | Times Cited: 37
Thermal conductivity analysis of porous NiAl materials manufactured by spark plasma sintering: Experimental studies and modelling
Szymon Nosewicz, G. Jurczak, Tomasz Wejrzanowski, et al.
International Journal of Heat and Mass Transfer (2022) Vol. 194, pp. 123070-123070
Open Access | Times Cited: 23
Transformer-based deep learning models for predicting permeability of porous media
Yinquan Meng, Jianguo Jiang, Jichun Wu, et al.
Advances in Water Resources (2023) Vol. 179, pp. 104520-104520
Closed Access | Times Cited: 14
Three-dimensional characterisation of pore networks and fluid flow in segregated heaps in the presence of crushed ore and agglomerates
Leiming Wang, Xingquan Zhang, Shenghua Yin, et al.
Hydrometallurgy (2023) Vol. 219, pp. 106082-106082
Closed Access | Times Cited: 13
Measurement of Effective Hydrogen-Methane Gas Diffusion Coefficients in Reservoir Rocks
Vladislav Arekhov, Timur Zhainakov, Torsten Clemens, et al.
SPE Reservoir Evaluation & Engineering (2023) Vol. 26, Iss. 04, pp. 1242-1257
Open Access | Times Cited: 13
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