Plane-wave domain least-squares reverse time migration with free-surface multiples

Free-surface multiples have been used in the reverse time migration (RTM) procedure to provide additional subsurface illumination. However, imaging multiple reflections with conventional RTM operators generates many crosstalk artifacts. Least-squares RTM (LSRTM) can be used to iteratively suppress crosstalk artifacts of multiples; however, the method is computationally intensive. By applying the linear Radon transformation to hundreds of shots of acquired data to produce dozens of plane-wave gathers, we have developed plane-wave domain LSRTM with free-surface multiples, which could efficiently provide images from the multiples with the crosstalk artifacts effectively suppressed. The proposed method has high computational efficiency when the dynamic plane-wave encoding scheme is used, in which only one or two plane-wave gathers of multiples are migrated at each iteration. We apply the method to numerical Pluto1.5 data and find that the proposed method can reduce most crosstalk artifacts and enhance spatial resolution, using even less computational time relative to RTM with multiples. Furthermore, joint imaging of primaries and multiples by plane-wave LSRTM can provide broader illumination and higher fold for the subsurface when compared with the imaging process with primaries only.

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Least-squares migration with primary- and multiple-guided weighting matrices

Geophysics ◽

10.1190/geo2018-0038.1 ◽

2019 ◽

Vol 84 (3) ◽

pp. S171-S185 ◽

Cited By ~ 1

Author(s):

Chuang Li ◽

Jianping Huang ◽

Zhenchun Li ◽

Han Yu ◽

Rongrong Wang

Keyword(s):

Free Surface ◽

Least Squares ◽

Seismic Data ◽

Synthetic Data ◽

Velocity Model ◽

Reverse Time ◽

Reverse Time Migration ◽

Multiple Reflections ◽

Time Migration ◽

Least Squares Migration

Least-squares migration (LSM) of seismic data is supposed to produce images of subsurface structures with better quality than standard migration if we have an accurate migration velocity model. However, LSM suffers from data mismatch problems and migration artifacts when noise pollutes the recorded profiles. This study has developed a reweighted least-squares reverse time migration (RWLSRTM) method to overcome the problems caused by such noise. We first verify that spiky noise and free-surface multiples lead to the mismatch problems and should be eliminated from the data residual. The primary- and multiple-guided weighting matrices are then derived for RWLSRTM to reduce the noise in the data residual. The weighting matrices impose constraints on the data residual such that spiky noise and free-surface multiple reflections are reduced whereas primary reflections are preserved. The weights for spiky noise and multiple reflections are controlled by a dynamic threshold parameter decreasing with iterations for better results. Finally, we use an iteratively reweighted least-squares algorithm to minimize the weighted data residual. We conduct numerical tests using the synthetic data and compared the results of this method with the results of standard LSRTM. The results suggest that RWLSRTM is more robust than standard LSRTM when the seismic data contain spiky noise and multiple reflections. Moreover, our method not only suppresses the migration artifacts, but it also accelerates the convergence.

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Fast least-squares reverse time migration of VSP free-surface multiples with dynamic phase-encoding schemes

Geophysics ◽

10.1190/geo2017-0419.1 ◽

2018 ◽

Vol 83 (4) ◽

pp. S321-S332 ◽

Cited By ~ 13

Author(s):

Xuejian Liu ◽

Yike Liu ◽

Majid Khan

Keyword(s):

Free Surface ◽

Least Squares ◽

Computational Cost ◽

Seismic Profile ◽

Reverse Time ◽

Reverse Time Migration ◽

Multiple Reflections ◽

Phase Encoding ◽

Time Migration ◽

Migration Method

For vertical seismic profile (VSP), free-surface multiples can provide much wider subsurface illumination when compared with primaries. However, migration of multiple reflections generates not only the desired image of reflection interfaces but also many crosstalk artifacts. Therefore, the least-squares reverse time migration method is used to image the VSP downgoing free-surface multiples (receiver-side ghosts) and iteratively suppress crosstalks, in which full downgoing data (including direct waves) and downgoing multiples are used as sources and observed data, respectively. To reduce the computational cost, we have developed the simultaneous imaging of different common-receiver gathers that are dynamically blended together with iterations through the altered realizations of the phase-encoding function. Relative to the popular encoding function with a combination of random time delays and polarities, only the random polarities can be applied for further increasing the computational efficiency. Synthetic experiments on Sigsbee2B and Pluto1.5 models indicate that the proposed method can effectively eliminate crosstalk artifacts and improve imaging resolution while calculated even more efficiently than reverse time migration of VSP ghosts.

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Plane-wave least-squares reverse time migration with a preconditioned stochastic conjugate gradient method

Geophysics ◽

10.1190/geo2017-0339.1 ◽

2018 ◽

Vol 83 (1) ◽

pp. S33-S46 ◽

Cited By ~ 14

Author(s):

Chuang Li ◽

Jianping Huang ◽

Zhenchun Li ◽

Rongrong Wang

Keyword(s):

Plane Wave ◽

Least Squares ◽

Conjugate Gradient ◽

Sampling Method ◽

Singular Spectrum Analysis ◽

Reverse Time ◽

Reverse Time Migration ◽

Numerical Tests ◽

Time Migration

This study derives a preconditioned stochastic conjugate gradient (CG) method that combines stochastic optimization with singular spectrum analysis (SSA) denoising to improve the efficiency and image quality of plane-wave least-squares reverse time migration (PLSRTM). This method reduces the computational costs of PLSRTM by applying a controlled group-sampling method to a sufficiently large number of plane-wave sections and accelerates the convergence using a hybrid of stochastic descent (SD) iteration and CG iteration. However, the group sampling also produces aliasing artifacts in the migration results. We use SSA denoising as a preconditioner to remove the artifacts. Moreover, we implement the preconditioning on the take-off angle-domain common-image gathers (CIGs) for better results. We conduct numerical tests using the Marmousi model and Sigsbee2A salt model and compare the results of this method with those of the SD method and the CG method. The results demonstrate that our method efficiently eliminates the artifacts and produces high-quality images and CIGs.

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Angle-domain common-image gathers from plane-wave least-squares reverse time migration

Geophysics ◽

10.1190/geo2020-0511.1 ◽

2021 ◽

pp. 1-60

Author(s):

Chuang Li ◽

Zhaoqi Gao ◽

Jinghuai Gao ◽

Feipeng Li ◽

Tao Yang

Keyword(s):

Inverse Problem ◽

Plane Wave ◽

Least Squares ◽

Migration Velocity ◽

Velocity Analysis ◽

Reverse Time ◽

Reverse Time Migration ◽

Time Migration ◽

Migration Velocity Analysis ◽

Amplitude Versus

Angle-domain common-image gathers (ADCIGs) that can be used for migration velocity analysis and amplitude versus angle analysis are important for seismic exploration. However, because of limited acquisition geometry and seismic frequency band, the ADCIGs extracted by reverse time migration (RTM) suffer from illumination gaps, migration artifacts, and low resolution. We have developed a reflection angle-domain pseudo-extended plane-wave least-squares RTM method for obtaining high-quality ADCIGs. We build the mapping relations between the ADCIGs and the plane-wave sections using an angle-domain pseudo-extended Born modeling operator and an adjoint operator, based on which we formulate the extraction of ADCIGs as an inverse problem. The inverse problem is iteratively solved by a preconditioned stochastic conjugate gradient method, allowing for reduction in computational cost by migrating only a subset instead of the whole dataset and improving image quality thanks to preconditioners. Numerical tests on synthetic and field data verify that the proposed method can compensate for illumination gaps, suppress migration artifacts, and improve resolution of the ADCIGs and the stacked images. Therefore, compared with RTM, the proposed method provides a more reliable input for migration velocity analysis and amplitude versus angle analysis. Moreover, it also provides much better stacked images for seismic interpretation.

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Plane-wave least-squares reverse time migration in complex VTI media

10.1190/segam2016-13863684.1 ◽

2016 ◽

Author(s):

Jinqiang Huang ◽

Daojun Si ◽

Zhenchun Li ◽

Jianping Huang

Keyword(s):

Plane Wave ◽

Least Squares ◽

Reverse Time ◽

Reverse Time Migration ◽

Time Migration ◽

Vti Media

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Periodic plane-wave least-squares reverse time migration for diffractions

Geophysics ◽

10.1190/geo2019-0211.1 ◽

2020 ◽

Vol 85 (4) ◽

pp. S185-S198

Author(s):

Chuang Li ◽

Jinghuai Gao ◽

Zhaoqi Gao ◽

Rongrong Wang ◽

Tao Yang

Keyword(s):

Inverse Problem ◽

Image Quality ◽

Plane Wave ◽

Least Squares ◽

Reverse Time ◽

Reverse Time Migration ◽

Time Migration ◽

Diffraction Imaging ◽

Periodic Plane

Diffraction imaging is important for high-resolution characterization of small subsurface heterogeneities. However, due to geometry limitations and noise distortion, conventional diffraction imaging methods may produce low-quality images. We have adopted a periodic plane-wave least-squares reverse time migration method for diffractions to improve the image quality of heterogeneities. The method reformulates diffraction imaging as an inverse problem using the Born modeling operator and its adjoint operator derived in the periodic plane-wave domain. The inverse problem is implemented for diffractions separated by a plane-wave destruction filter from the periodic plane-wave sections. Because the plane-wave destruction filter may fail to eliminate hyperbolic reflections and noise, we adopt a hyperbolic misfit function to minimize a weighted residual using an iteratively reweighted least-squares algorithm and thereby reduce residual reflections and noise. Synthetic and field data tests show that the adopted method can significantly improve the image quality of subsalt and deep heterogeneities. Compared with reverse time migration, it produces better images with fewer artifacts, higher resolution, and more balanced amplitude. Therefore, the adopted method can accurately characterize small heterogeneities and provide a reliable input for seismic interpretation in the prediction of hydrocarbon reservoirs.

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