Elastic least-squares reverse time migration with velocities and density perturbation

Qu, Yingming; Li, Jinli; Huang, Jianping; Li, Zhenchun

doi:10.1093/gji/ggx468

Cited by 33 publications

(10 citation statements)

References 35 publications

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“…As discussed by H.‐W. Zhou et al (), this may be remedied by use of least squares RTM (e.g., Qu et al, ; Ren et al, ; Yao & Jacubowicz, ; Zeng et al, ; Zhang et al, ).…”

Section: Discussionmentioning

confidence: 99%

“…This arises because of a combination of incomplete data and the fact that an adjoint operator is an imperfect approximation to the inverse of the forward modeling operator (Claerbout, 1992). As discussed by H.-W. Zhou et al (2018), this may be remedied by use of least squares RTM (e.g., Qu et al, 2018;Ren et al, 2017;Yao & Jacubowicz, 2016;Zeng et al, 2014;Zhang et al, 2015).…”

Section: 1029/2018jb017089mentioning

confidence: 99%

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Surface Imaging Functions for Elastic Reverse Time Migration

Pollitz

2019

JGR Solid Earth

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Reverse time migration is often used to interpret acoustic or three‐component seismic recordings by creating an image of subsurface seismic reflectors. Here I describe elastic reverse time migration imaging functions that are cast as waveform misfit sensitivity kernels of contrasts in material parameters across hypothetical seismic discontinuities, that is, specular reflectors. The proposed “surface” imaging functions are theoretically applicable to either reflected or converted waves in order to estimate the location and reflectivity of these discontinuities. The surface imaging functions, as well as volumetric sensitivity kernels that target point diffractors, are tested on sets of synthetic surface array recordings that sample the 3‐D seismic wavefield on simple 2‐D structures generated using a 2.5‐D spectral element method. These tests illustrate that in contrast with the volumetric sensitivity kernels, the reflectivity is generally dominated by a high‐amplitude peak that coincides with input locations of discontinuities. Passive recordings of microseismicity, shot gathers, or a combination thereof can be potentially interpreted with the new surface imaging functions to yield useful reflectivity images.

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“…As discussed by H.‐W. Zhou et al (), this may be remedied by use of least squares RTM (e.g., Qu et al, ; Ren et al, ; Yao & Jacubowicz, ; Zeng et al, ; Zhang et al, ).…”

Section: Discussionmentioning

confidence: 99%

Section: 1029/2018jb017089mentioning

confidence: 99%

Surface Imaging Functions for Elastic Reverse Time Migration

Pollitz

2019

JGR Solid Earth

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“…The crosstalk artefacts created by the nonphysical wave modes can be avoided by separating the P‐ and S‐wave seismic data. The vector‐decomposed multicomponent seismic data approach (Li et al ., 2015, 2016b) is widely used in the wavefield‐separation‐based elastic least‐square reverse time migration and elastic FWI approaches to reduce the crosstalk artefacts (Ren and Liu, 2016; Gu et al ., 2017, 2018; Qu et al ., 2018; Yang et al ., 2019, 2020).…”

Section: Introductionmentioning

confidence: 99%

2D and 3D amplitude‐preserving elastic reverse time migration based on the vector‐decomposed P‐ and S‐wave records

Zhang

Gao

et al. 2020

Geophysical Prospecting

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The elastic reverse time migration approach based on the vector-wavefield decomposition generally uses the scalar product imaging condition to image the multicomponent seismic data. However, the resulting images contain the crosstalk artefacts and the polarity reversal problems, which are caused by the nonphysical wave modes and the angle-dependent reduction of image amplitudes, respectively. To overcome these two problems, we develop an amplitude-preserving elastic reverse time migration approach based on the vector-decomposed P-and S-wave seismic records. This approach includes two key points. The first is that we employ the vector-decomposed P-and S-wave multicomponent records to independently reconstruct the PP and PS reflection images to mitigate the crosstalk artefacts. The second is that we propose two schemes in addressing the issue of polarity reversal problem in the conventional PP image. One solution is to adopt the angle-dependent equation. Another one is to reconstruct an amplitude-preserving PP image with a separated scalar P-wave particle velocity, which has a clear physical meaning. Numerical examples using two-dimensional and three-dimensional models demonstrate that the proposed elastic reverse time migration approach can provide the images with better amplitude-preserving performance and fewer crosstalk artefacts, compared with the conventional elastic reverse time migration approach based on the scalar product imaging condition.

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“…Qu et al . () and Gu, Li and Han () introduced wavefield‐separation‐based elastic LSRTM methods to mitigate migration artefacts caused by the crosstalk among the different waves. Chen and Sacchi () implemented elastic LSRTM by linearized elastic full‐waveform inversion with pseudo‐Hessian preconditioning.…”

Section: Introductionmentioning

confidence: 99%

Imaging of elastic seismic data by least‐squares reverse time migration with weighted L2‐norm multiplicative and modified total‐variation regularizations

Ren

2019

Geophysical Prospecting

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Least‐squares reverse time migration has the potential to yield high‐quality images of the Earth. Compared with acoustic methods, elastic least‐squares reverse time migration can effectively address mode conversion and provide velocity/impendence and density perturbation models. However, elastic least‐squares reverse time migration is an ill‐posed problem and suffers from a lack of uniqueness; further, its solution is not stable. We develop two new elastic least‐squares reverse time migration methods based on weighted L2‐norm multiplicative and modified total‐variation regularizations. In the proposed methods, the original minimization problem is divided into two subproblems, and the images and auxiliary variables are updated alternatively. The method with modified total‐variation regularization solves the two subproblems, a Tikhonov regularization problem and an L2‐total‐variation regularization problem, via an efficient inversion workflow and the split‐Bregman iterative method, respectively. The method with multiplicative regularization updates the images and auxiliary variables by the efficient inversion workflow and nonlinear conjugate gradient methods in a nested fashion. We validate the proposed methods using synthetic and field seismic data. Numerical results demonstrate that the proposed methods with regularization improve the resolution and fidelity of the migration profiles and exhibit superior anti‐noise ability compared with the conventional method. Moreover, the modified‐total‐variation‐based method has marginally higher accuracy than the multiplicative‐regularization‐based method for noisy data. The computational cost of the proposed two methods is approximately the same as that of the conventional least‐squares reverse time migration method because no additional forward computation is required in the inversion of auxiliary variables.

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Elastic least-squares reverse time migration with velocities and density perturbation

Cited by 33 publications

References 35 publications

Surface Imaging Functions for Elastic Reverse Time Migration

Surface Imaging Functions for Elastic Reverse Time Migration

2D and 3D amplitude‐preserving elastic reverse time migration based on the vector‐decomposed P‐ and S‐wave records

Imaging of elastic seismic data by least‐squares reverse time migration with weighted L2‐norm multiplicative and modified total‐variation regularizations

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