2017
DOI: 10.1190/geo2016-0254.1
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Elastic least-squares reverse time migration

Abstract: We use elastic least-squares reverse time migration (LSRTM) to invert for the reflectivity images of P-and S-wave impedances. Elastic LSRTM solves the linearized elastic-wave equations for forward modeling and the adjoint equations for backpropagating the residual wavefield at each iteration. Numerical tests on synthetic data and field data reveal the advantages of elastic LSRTM over elastic reverse time migration (RTM) and acoustic LSRTM. For our examples, the elastic LSRTM images have better resolution and a… Show more

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Cited by 118 publications
(30 citation statements)
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“…Most elastic LSRTM implementations use images based on model perturbations (Alves and Biondi, 2016;Feng and Schuster, 2017;Xu et al, 2016;Duan et al, 2017;Ren et al, 2017).…”
Section: Acknowledgmentsmentioning
confidence: 99%
See 1 more Smart Citation
“…Most elastic LSRTM implementations use images based on model perturbations (Alves and Biondi, 2016;Feng and Schuster, 2017;Xu et al, 2016;Duan et al, 2017;Ren et al, 2017).…”
Section: Acknowledgmentsmentioning
confidence: 99%
“…This technique exploits an objective function and its residual in the data domain, and separately updates the smooth and rough (i.e., image) parts of the earth model. Least-squares migration robustly computes the rough model (Alves and Biondi, 2016;Feng and Schuster, 2017;Duan et al, 2017;Ren et al, 2017), while optimization via adjoint-state method provides the smooth updates (Tarantola, 1988;Sava, 2014). Therefore, we can classify RWI as a mixed-domain (both data-and image-domain) wavefield tomography method.…”
Section: Introductionmentioning
confidence: 99%
“…The filter estimates the neardiagonal elements of the submatrices of the Hessian inverse for the different parameter classes. Our decoupled deblurring filter is used to improve the elastic migration image quality and speed up the convergence of elastic linearized inversion (Duan et al, 2016;Feng and Schuster, 2017;Ren et al, 2017). The results show that the filter not only balances the amplitude, increases the resolution, but also reduces the crosstalk artifacts in the elastic migration images.…”
Section: Introductionmentioning
confidence: 98%
“…Hu et al (2016) and Yang et al (2018b) show that LSM can also be effectively implemented using Gaussian beams. For imaging elastic waves, the existing elastic LSM (ELSM) methods are mainly implemented with the two-way wave propagator (Duan et al, 2017;Feng and Schuster, 2017). However, because the computational cost of one iteration of ELSM is twice that of conventional ERTM, the expense of all ELSM iterations is often prohibitively high in large-scale applications.…”
Section: Introductionmentioning
confidence: 99%