Corrigendum to “An end-to-end approach to predict physical properties of heterogeneous porous media: Coupling deep learning and physics-based features” [Fuel 352 (2023) 128753] (Fuel (2023) 352, (S0016236123013662), (10.1016/j.fuel.2023.128753))

Yuqi Wu; Senyou An; Pejman Tahmasebi; Keyu Liu; Chengyan Lin; Serveh Kamrava; Chang Liu; Chenyang Yu; Tao Zhang; Shuyu Sun; Samuel Krevor; Vahid Niasar

doi:10.1016/j.fuel.2024.131358

Corrigendum to “An end-to-end approach to predict physical properties of heterogeneous porous media: Coupling deep learning and physics-based features” [Fuel 352 (2023) 128753] (Fuel (2023) 352, (S0016236123013662), (10.1016/j.fuel.2023.128753))

Yuqi Wu, Senyou An^*, Pejman Tahmasebi, Keyu Liu, Chengyan Lin, Serveh Kamrava, Chang Liu, Chenyang Yu, Tao Zhang, Shuyu Sun, Samuel Krevor, Vahid Niasar

^*Corresponding author for this work

Research output: Contribution to journal › Comment/debate › peer-review

Abstract

In this corrigendum the authors have removed an extra caption in Figure 10 in the above cited paper. Unfortunately, one of the captions was not removed when a revision was implemented on this figure during the review process. The caption of this figure should have read as: Figure 10. (a) Comparison of 2D original LR and HR-CycleGAN images, illustrating that the latter can better capture fine-scale structures of the samples; (b) Comparison of 3D original LR, HR-Bicubic, and HR-CycleGAN images, demonstrating that the HR-CycleGAN images can contain much finer details compared with other images. The authors would like to apologize for any inconvenience caused.

Original language	English (US)
Article number	131358
Journal	Fuel
Volume	364
DOIs	https://doi.org/10.1016/j.fuel.2024.131358
State	Published - May 15 2024

ASJC Scopus subject areas

General Chemical Engineering
Fuel Technology
Energy Engineering and Power Technology
Organic Chemistry

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Wu, Y., An, S., Tahmasebi, P., Liu, K., Lin, C., Kamrava, S., Liu, C., Yu, C., Zhang, T., Sun, S., Krevor, S., & Niasar, V. (2024). Corrigendum to “An end-to-end approach to predict physical properties of heterogeneous porous media: Coupling deep learning and physics-based features” [Fuel 352 (2023) 128753] (Fuel (2023) 352, (S0016236123013662), (10.1016/j.fuel.2023.128753)). Fuel, 364, Article 131358. https://doi.org/10.1016/j.fuel.2024.131358

@article{6f67be63991c4228987eebe727f7ea51,

title = "Corrigendum to “An end-to-end approach to predict physical properties of heterogeneous porous media: Coupling deep learning and physics-based features” [Fuel 352 (2023) 128753] (Fuel (2023) 352, (S0016236123013662), (10.1016/j.fuel.2023.128753))",

abstract = "In this corrigendum the authors have removed an extra caption in Figure 10 in the above cited paper. Unfortunately, one of the captions was not removed when a revision was implemented on this figure during the review process. The caption of this figure should have read as: Figure 10. (a) Comparison of 2D original LR and HR-CycleGAN images, illustrating that the latter can better capture fine-scale structures of the samples; (b) Comparison of 3D original LR, HR-Bicubic, and HR-CycleGAN images, demonstrating that the HR-CycleGAN images can contain much finer details compared with other images. The authors would like to apologize for any inconvenience caused.",

author = "Yuqi Wu and Senyou An and Pejman Tahmasebi and Keyu Liu and Chengyan Lin and Serveh Kamrava and Chang Liu and Chenyang Yu and Tao Zhang and Shuyu Sun and Samuel Krevor and Vahid Niasar",

note = "Publisher Copyright: {\textcopyright} 2024 Elsevier Ltd",

year = "2024",

month = may,

day = "15",

doi = "10.1016/j.fuel.2024.131358",

language = "English (US)",

volume = "364",

journal = "Fuel",

issn = "0016-2361",

publisher = "Elsevier",

}

Wu, Y, An, S, Tahmasebi, P, Liu, K, Lin, C, Kamrava, S, Liu, C, Yu, C, Zhang, T, Sun, S, Krevor, S & Niasar, V 2024, 'Corrigendum to “An end-to-end approach to predict physical properties of heterogeneous porous media: Coupling deep learning and physics-based features” [Fuel 352 (2023) 128753] (Fuel (2023) 352, (S0016236123013662), (10.1016/j.fuel.2023.128753))', Fuel, vol. 364, 131358. https://doi.org/10.1016/j.fuel.2024.131358

Corrigendum to “An end-to-end approach to predict physical properties of heterogeneous porous media: Coupling deep learning and physics-based features” [Fuel 352 (2023) 128753] (Fuel (2023) 352, (S0016236123013662), (10.1016/j.fuel.2023.128753)). / Wu, Yuqi; An, Senyou; Tahmasebi, Pejman et al.
In: Fuel, Vol. 364, 131358, 15.05.2024.

Research output: Contribution to journal › Comment/debate › peer-review

TY - JOUR

T1 - Corrigendum to “An end-to-end approach to predict physical properties of heterogeneous porous media

T2 - Coupling deep learning and physics-based features” [Fuel 352 (2023) 128753] (Fuel (2023) 352, (S0016236123013662), (10.1016/j.fuel.2023.128753))

AU - Wu, Yuqi

AU - An, Senyou

AU - Tahmasebi, Pejman

AU - Liu, Keyu

AU - Lin, Chengyan

AU - Kamrava, Serveh

AU - Liu, Chang

AU - Yu, Chenyang

AU - Zhang, Tao

AU - Sun, Shuyu

AU - Krevor, Samuel

AU - Niasar, Vahid

PY - 2024/5/15

Y1 - 2024/5/15

N2 - In this corrigendum the authors have removed an extra caption in Figure 10 in the above cited paper. Unfortunately, one of the captions was not removed when a revision was implemented on this figure during the review process. The caption of this figure should have read as: Figure 10. (a) Comparison of 2D original LR and HR-CycleGAN images, illustrating that the latter can better capture fine-scale structures of the samples; (b) Comparison of 3D original LR, HR-Bicubic, and HR-CycleGAN images, demonstrating that the HR-CycleGAN images can contain much finer details compared with other images. The authors would like to apologize for any inconvenience caused.

AB - In this corrigendum the authors have removed an extra caption in Figure 10 in the above cited paper. Unfortunately, one of the captions was not removed when a revision was implemented on this figure during the review process. The caption of this figure should have read as: Figure 10. (a) Comparison of 2D original LR and HR-CycleGAN images, illustrating that the latter can better capture fine-scale structures of the samples; (b) Comparison of 3D original LR, HR-Bicubic, and HR-CycleGAN images, demonstrating that the HR-CycleGAN images can contain much finer details compared with other images. The authors would like to apologize for any inconvenience caused.

UR - http://www.scopus.com/inward/record.url?scp=85186995798&partnerID=8YFLogxK

U2 - 10.1016/j.fuel.2024.131358

DO - 10.1016/j.fuel.2024.131358

M3 - Comment/debate

AN - SCOPUS:85186995798

SN - 0016-2361

VL - 364

JO - Fuel

JF - Fuel

M1 - 131358

ER -

Corrigendum to “An end-to-end approach to predict physical properties of heterogeneous porous media: Coupling deep learning and physics-based features” [Fuel 352 (2023) 128753] (Fuel (2023) 352, (S0016236123013662), (10.1016/j.fuel.2023.128753))

Abstract

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