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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.19939 |
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| _version_ | 1866929402847166464 |
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| author | Yang, Guang Xu, Ran Tian, Yusong Guo, Songyuan Wu, Jingyi Chu, Xu |
| author_facet | Yang, Guang Xu, Ran Tian, Yusong Guo, Songyuan Wu, Jingyi Chu, Xu |
| contents | This review examined the current advancements in data-driven methods for analyzing flow and transport in porous media, which has various applications in energy, chemical engineering, environmental science, and beyond. Although there has been progress in recent years, the challenges of current experimental and high-fidelity numerical simulations, such as high computational costs and difficulties in accurately representing complex, heterogeneous structures, can still potentially be addressed by state-of-the-art data-driven methods. We analyzed the synergistic potential of these methods, addressed their limitations, and suggested how they can be effectively integrated to improve both the fidelity and efficiency of current research. A discussion on future research directions in this field was conducted, emphasizing the need for collaborative efforts that combine domain expertise in physics and advanced computationald and data-driven methodologies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_19939 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Data-driven methods for flow and transport in porous media: a review Yang, Guang Xu, Ran Tian, Yusong Guo, Songyuan Wu, Jingyi Chu, Xu Fluid Dynamics This review examined the current advancements in data-driven methods for analyzing flow and transport in porous media, which has various applications in energy, chemical engineering, environmental science, and beyond. Although there has been progress in recent years, the challenges of current experimental and high-fidelity numerical simulations, such as high computational costs and difficulties in accurately representing complex, heterogeneous structures, can still potentially be addressed by state-of-the-art data-driven methods. We analyzed the synergistic potential of these methods, addressed their limitations, and suggested how they can be effectively integrated to improve both the fidelity and efficiency of current research. A discussion on future research directions in this field was conducted, emphasizing the need for collaborative efforts that combine domain expertise in physics and advanced computationald and data-driven methodologies. |
| title | Data-driven methods for flow and transport in porous media: a review |
| topic | Fluid Dynamics |
| url | https://arxiv.org/abs/2406.19939 |