Preconditioned least-squares reverse time migration with energy imaging condition

Liu, Mengli; Huang, Jianping; Li, Chuang; Ren, Yingjun; Li, Zhenchun

doi:10.1190/segam2017-17684386.1

Cited by 2 publications

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In 2016, Liu et al [18] further derived an analytical step-length (ASL) formula for the acoustic CLSRTM. To solve the problem of cycle skipping caused by the large velocity error, Liu and Li [19] developed an LSRTM scheme with an extended imaging condition. In 2014, Dutta and Schuster [20], and Li et al [21] developed a viscoacoustic LSRTM method to enhance image resolution.…”

Section: Introductionmentioning

confidence: 99%

Elastic Correlative Least-Squares Reverse Time Migration Based on Wave Mode Decomposition

Zheng

Liu

et al. 2022

Processes

View full text Add to dashboard Cite

The conventional elastic least-squares reverse time migration (LSRTM) generally inverts the parameter perturbation of the model rather than the reflectivity of reflected P- and S-modes, which leads to difficulty in directly interpreting the physical properties of the subsurface media. However, an accurate velocity model that is needed by the separation of seismic records of conventional LSRTM is usually unavailable in real data, which limits its application. In this study, we introduce a new practical correlative LSRTM (CLSRTM) scheme based on wave mode decomposition without amplitude and phase distortion, which frees from separation of seismic records. In this study, we deduced the migration and the de-migration operators using the decoupled P- and S-wave equations in heterogeneous media, which needs no extra wavefield decomposition in simulated data. To accelerate the convergence and improve the efficiency of the inversion, we adopted an analytical step-length formula that can be incidentally computed during the necessary de-migration process and the L-BFGS algorithm. Two numerical examples demonstrate that the proposed method can compensate the energy of deep structures, and generate clear images with balanced amplitudes and enhanced resolution even for the fault structures beneath the salt dome.

show abstract

Section: Introductionmentioning

confidence: 99%

Elastic Correlative Least-Squares Reverse Time Migration Based on Wave Mode Decomposition

Zheng

Liu

et al. 2022

Processes

View full text Add to dashboard Cite

show abstract

“…Least-squares migration (LSM) is able to suppress the migration artifacts and produce high-quality images (Nemeth et al 1999 ; Tang and Biondi 2009 ; Dai and Schuster 2013 ; Li et al 2014 , 2015a ; Liu and Li 2015 ; Huang et al 2013 , 2015a ). However, the computational cost of LSM is high as it is solved by gradient-based optimization schemes (Huang et al 2015b ; Huang and Zhou 2015 ; Li et al 2016a ).…”

Section: Introductionmentioning

confidence: 99%

Regularized least-squares migration of simultaneous-source seismic data with adaptive singular spectrum analysis

Huang

et al. 2016

Pet. Sci.

Self Cite

View full text Add to dashboard Cite

Simultaneous-source acquisition has been recognized as an economic and efficient acquisition method, but the direct imaging of the simultaneous-source data produces migration artifacts because of the interference of adjacent sources. To overcome this problem, we propose the regularized least-squares reverse time migration method (RLSRTM) using the singular spectrum analysis technique that imposes sparseness constraints on the inverted model. Additionally, the difference spectrum theory of singular values is presented so that RLSRTM can be implemented adaptively to eliminate the migration artifacts. With numerical tests on a flat layer model and a Marmousi model, we validate the superior imaging quality, efficiency and convergence of RLSRTM compared with LSRTM when dealing with simultaneous-source data, incomplete data and noisy data.

show abstract

Preconditioned least-squares reverse time migration with energy imaging condition

Cited by 2 publications

References 14 publications

Elastic Correlative Least-Squares Reverse Time Migration Based on Wave Mode Decomposition

Elastic Correlative Least-Squares Reverse Time Migration Based on Wave Mode Decomposition

Regularized least-squares migration of simultaneous-source seismic data with adaptive singular spectrum analysis

Contact Info

Product

Resources

About