Least squares reverse time migration imaging with illumination preconditioned based on improved PRP conjugate gradients
Abstract Least squares reverse time migration (LSRTM) imaging is the one of the most accurate methods for migration imaging at present, and Polak–Ribiere–Polyak conjugate gradient (PRPCG) for LSRTM has the good numerical performance but weak convergence, so we construct an optimization factor to imp...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-40578-8 |
| _version_ | 1797560062553620480 |
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| author | Xiaodan Zhang Rui Li Lin Cui Dongxiao Liu Guizhong Liu Zhiyu Zhang |
| author_facet | Xiaodan Zhang Rui Li Lin Cui Dongxiao Liu Guizhong Liu Zhiyu Zhang |
| author_sort | Xiaodan Zhang |
| collection | DOAJ |
| description | Abstract Least squares reverse time migration (LSRTM) imaging is the one of the most accurate methods for migration imaging at present, and Polak–Ribiere–Polyak conjugate gradient (PRPCG) for LSRTM has the good numerical performance but weak convergence, so we construct an optimization factor to improve the iteration direction of the gradient, which can automatically generate a sufficient descent direction. The improved PRPCG (IPRPCG) can reduce the data residual values and speed up the iteration. And the illumination preconditioned (IP) operator is employed to IPRPCG-LSRTM which solves the problem of low resolution due to the insufficient iterative gradient information. In this paper, the experiments show that the imaging results of the proposed method (IPRPCG-IP-LSRTM) is improved greatly in detail characterization and events continuity, the iterative curve converged faster significantly, and the normalized data residual was reduced by 6.55% on average, which improved the accuracy of migration imaging effectively. |
| first_indexed | 2024-03-10T17:54:06Z |
| format | Article |
| id | doaj.art-b02275429f304b6f981a3c1f644bcf83 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-10T17:54:06Z |
| publishDate | 2023-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-b02275429f304b6f981a3c1f644bcf832023-11-20T09:15:35ZengNature PortfolioScientific Reports2045-23222023-08-0113111910.1038/s41598-023-40578-8Least squares reverse time migration imaging with illumination preconditioned based on improved PRP conjugate gradientsXiaodan Zhang0Rui Li1Lin Cui2Dongxiao Liu3Guizhong Liu4Zhiyu Zhang5School of Electronic Information, Xi’an Polytechnic UniversitySchool of Electronic Information, Xi’an Polytechnic UniversitySchool of Electronic Information, Xi’an Polytechnic UniversitySchool of Electronic Information, Xi’an Polytechnic UniversitySchool of Information and Communications Engineering, Xi’an JiaoTong UniversitySchool of Automation and Information Engineering, Xi’an University of TechnologyAbstract Least squares reverse time migration (LSRTM) imaging is the one of the most accurate methods for migration imaging at present, and Polak–Ribiere–Polyak conjugate gradient (PRPCG) for LSRTM has the good numerical performance but weak convergence, so we construct an optimization factor to improve the iteration direction of the gradient, which can automatically generate a sufficient descent direction. The improved PRPCG (IPRPCG) can reduce the data residual values and speed up the iteration. And the illumination preconditioned (IP) operator is employed to IPRPCG-LSRTM which solves the problem of low resolution due to the insufficient iterative gradient information. In this paper, the experiments show that the imaging results of the proposed method (IPRPCG-IP-LSRTM) is improved greatly in detail characterization and events continuity, the iterative curve converged faster significantly, and the normalized data residual was reduced by 6.55% on average, which improved the accuracy of migration imaging effectively.https://doi.org/10.1038/s41598-023-40578-8 |
| spellingShingle | Xiaodan Zhang Rui Li Lin Cui Dongxiao Liu Guizhong Liu Zhiyu Zhang Least squares reverse time migration imaging with illumination preconditioned based on improved PRP conjugate gradients Scientific Reports |
| title | Least squares reverse time migration imaging with illumination preconditioned based on improved PRP conjugate gradients |
| title_full | Least squares reverse time migration imaging with illumination preconditioned based on improved PRP conjugate gradients |
| title_fullStr | Least squares reverse time migration imaging with illumination preconditioned based on improved PRP conjugate gradients |
| title_full_unstemmed | Least squares reverse time migration imaging with illumination preconditioned based on improved PRP conjugate gradients |
| title_short | Least squares reverse time migration imaging with illumination preconditioned based on improved PRP conjugate gradients |
| title_sort | least squares reverse time migration imaging with illumination preconditioned based on improved prp conjugate gradients |
| url | https://doi.org/10.1038/s41598-023-40578-8 |
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