Least squares reverse time migration imaging with illumination preconditioned based on improved PRP conjugate gradients

• Published in: Scientific reports 2023-08, Vol.13 (1), p.13623-13623, Article 13623
• Main Authors: Zhang, Xiaodan, Li, Rui, Cui, Lin, Liu, Dongxiao, Liu, Guizhong, Zhang, Zhiyu
• Format: Article
• Language: English
• Subjects: 704/2151; 704/2151/2809; Accuracy; Algorithms; Approximation; Efficiency; Humanities and Social Sciences; Illumination; multidisciplinary; Optimization; Regularization methods; Science; Science (multidisciplinary); Velocity
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-40578-8

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.