Quadrilateral mesh optimisation method based on swarm intelligence optimisation
Abstract As oil and gas exploration advances, the growing complexity of geological conditions demands higher-quality quadrilateral meshes for spectral element method-based seismic simulations. For complex geological models, existing quadrilateral meshing algorithms struggle to generate high-quality...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-11071-1 |
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| author | Fen Zhang Jiuyun Tian Panpan LV Kaiyun Luo Yonggu Huang Shaohui Yang Fei Deng |
| author_facet | Fen Zhang Jiuyun Tian Panpan LV Kaiyun Luo Yonggu Huang Shaohui Yang Fei Deng |
| author_sort | Fen Zhang |
| collection | DOAJ |
| description | Abstract As oil and gas exploration advances, the growing complexity of geological conditions demands higher-quality quadrilateral meshes for spectral element method-based seismic simulations. For complex geological models, existing quadrilateral meshing algorithms struggle to generate high-quality meshes that meet the spectral element method’s requirements, often producing initial meshes with topological errors or concave elements, which compromise simulation accuracy. To address this, we propose a swarm intelligence-based secondary optimisation method, employing particle swarm optimisation (PSO), wolf pack algorithm (WPA), and firefly algorithm (FA) to iteratively refine distorted nodes. Results demonstrate that all three algorithms eliminate initial mesh defects, with WPA achieving the highest mesh quality, PSO exhibiting the fastest convergence, and FA performing least effectively. The optimised meshes meet the high-quality standards of the spectral element method, significantly improving simulation stability and computational efficiency, and laying a foundation for the further application of the spectral element method in seismic exploration. |
| format | Article |
| id | doaj-art-763515d6021f463d8a8774b2e8c8e6e5 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-763515d6021f463d8a8774b2e8c8e6e52025-08-20T03:45:57ZengNature PortfolioScientific Reports2045-23222025-07-0115112010.1038/s41598-025-11071-1Quadrilateral mesh optimisation method based on swarm intelligence optimisationFen Zhang0Jiuyun Tian1Panpan LV2Kaiyun Luo3Yonggu Huang4Shaohui Yang5Fei Deng6College of Computer Science and Cyber Security, Chengdu University of TechnologyCollege of Computer Science and Cyber Security, Chengdu University of TechnologyAcquisition Technology Institute, BGP Inc., CNPCAcquisition Technology Institute, BGP Inc., CNPCCollege of Computer Science and Cyber Security, Chengdu University of TechnologyCollege of Computer Science and Cyber Security, Chengdu University of TechnologyCollege of Computer Science and Cyber Security, Chengdu University of TechnologyAbstract As oil and gas exploration advances, the growing complexity of geological conditions demands higher-quality quadrilateral meshes for spectral element method-based seismic simulations. For complex geological models, existing quadrilateral meshing algorithms struggle to generate high-quality meshes that meet the spectral element method’s requirements, often producing initial meshes with topological errors or concave elements, which compromise simulation accuracy. To address this, we propose a swarm intelligence-based secondary optimisation method, employing particle swarm optimisation (PSO), wolf pack algorithm (WPA), and firefly algorithm (FA) to iteratively refine distorted nodes. Results demonstrate that all three algorithms eliminate initial mesh defects, with WPA achieving the highest mesh quality, PSO exhibiting the fastest convergence, and FA performing least effectively. The optimised meshes meet the high-quality standards of the spectral element method, significantly improving simulation stability and computational efficiency, and laying a foundation for the further application of the spectral element method in seismic exploration.https://doi.org/10.1038/s41598-025-11071-1Spectral element methodSwarm intelligence algorithmForward modelingSeismic explorationQuadrilateral mesh |
| spellingShingle | Fen Zhang Jiuyun Tian Panpan LV Kaiyun Luo Yonggu Huang Shaohui Yang Fei Deng Quadrilateral mesh optimisation method based on swarm intelligence optimisation Scientific Reports Spectral element method Swarm intelligence algorithm Forward modeling Seismic exploration Quadrilateral mesh |
| title | Quadrilateral mesh optimisation method based on swarm intelligence optimisation |
| title_full | Quadrilateral mesh optimisation method based on swarm intelligence optimisation |
| title_fullStr | Quadrilateral mesh optimisation method based on swarm intelligence optimisation |
| title_full_unstemmed | Quadrilateral mesh optimisation method based on swarm intelligence optimisation |
| title_short | Quadrilateral mesh optimisation method based on swarm intelligence optimisation |
| title_sort | quadrilateral mesh optimisation method based on swarm intelligence optimisation |
| topic | Spectral element method Swarm intelligence algorithm Forward modeling Seismic exploration Quadrilateral mesh |
| url | https://doi.org/10.1038/s41598-025-11071-1 |
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