Fast Plane-Wave Reverse Time Migration

Encoded reverse time migration with random plane-wave segments

10.3997/2214-4609.202112676 ◽

2021 ◽

Author(s):

C. Tang ◽

F. Liu ◽

F. Hao ◽

A. Yeh

Keyword(s):

Plane Wave ◽

Reverse Time ◽

Reverse Time Migration ◽

Time Migration

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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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Fast plane-wave reverse time migration

Geophysics ◽

10.1190/geo2017-0688.1 ◽

2018 ◽

Vol 83 (6) ◽

pp. S549-S556 ◽

Cited By ~ 1

Author(s):

Xiongwen Wang ◽

Xu Ji ◽

Hongwei Liu ◽

Yi Luo

Keyword(s):

Time Delay ◽

Plane Wave ◽

Green’S Function ◽

Green's Function ◽

Time Domain ◽

Reverse Time ◽

Reverse Time Migration ◽

Wave Source ◽

Computation Cost ◽

Time Migration

Plane-wave reverse time migration (RTM) could potentially provide quick subsurface images by migrating fewer plane-wave gathers than shot gathers. However, the time delay between the first and the last excitation sources in the plane-wave source largely increases the computation cost and decreases the practical value of this method. Although the time delay problem is easily overcome by periodical phase shifting in the frequency domain for one-way wave-equation migration, it remains a challenge for time-domain RTM. We have developed a novel method, referred as to fast plane-wave RTM (FP-RTM), to eliminate unnecessary computation burden and significantly reduce the computational cost. In the proposed FP-RTM, we assume that the Green’s function has finite-length support; thus, the plane-wave source function and its responding data can be wrapped periodically in the time domain. The wrapping length is the assumed total duration length of Green’s function. We also determine that only two period plane-wave source and data after the wrapping process are required for generating the outcome with adequate accuracy. Although the computation time for one plane-wave gather is twice as long as a normal shot gather migration, a large amount of computation cost is saved because the total number of plane-wave gathers to be migrated is usually much less than the total number of shot gathers. Our FP-RTM can be used to rapidly generate RTM images and plane-wave domain common-image gathers for velocity model building. The synthetic and field data examples are evaluated to validate the efficiency and accuracy of our method.

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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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Combining multidirectional source vector with antitruncation-artifact Fourier transform to calculate angle gathers from reverse time migration in two steps

Geophysics ◽

10.1190/geo2016-0408.1 ◽

2017 ◽

Vol 82 (5) ◽

pp. S359-S376 ◽

Cited By ~ 6

Author(s):

Chen Tang ◽

George A. McMechan

Keyword(s):

Fourier Transform ◽

Plane Wave ◽

Poynting Vector ◽

Reverse Time ◽

Reverse Time Migration ◽

Time Step ◽

Imaging Condition ◽

Time Migration ◽

Reflection Image ◽

Wave Decomposition

Because receiver wavefields reconstructed from observed data are not as stable as synthetic source wavefields, the source-propagation vector and the reflector normal have often been used to calculate angle-domain common-image gathers (ADCIGs) from reverse time migration. However, the existing data flows have three main limitations: (1) Calculating the propagation direction only at the wavefields with maximum amplitudes ignores multiarrivals; using the crosscorrelation imaging condition at each time step can include the multiarrivals but will result in backscattering artifacts. (2) Neither amplitude picking nor Poynting-vector calculations are accurate for overlapping wavefields. (3) Calculating the reflector normal in space is not accurate for a structurally complicated reflection image, and calculating it in the wavenumber ([Formula: see text]) domain may give Fourier truncation artifacts. We address these three limitations in an improved data flow with two steps: During imaging, we use a multidirectional Poynting vector (MPV) to calculate the propagation vectors of the source wavefield at each time step and output intermediate source-angle-domain CIGs (SACIGs). After imaging, we use an antitruncation-artifact Fourier transform (ATFT) to convert SACIGs to ADCIGs in the [Formula: see text]-domain. To achieve the new flow, another three innovative aspects are included. In the first step, we develop an angle-tapering scheme to remove the Fourier truncation artifacts during the wave decomposition (of MPV) while preserving the amplitudes, and we use a wavefield decomposition plus angle-filter imaging condition to remove the backscattering artifacts in the SACIGs. In the second step, we compare two algorithms to remove the Fourier truncation artifacts that are caused by the plane-wave assumption. One uses an antileakage FT (ALFT) in local windows; the other uses an antitruncation-artifact FT, which relaxes the plane-wave assumption and thus can be done for the global space. The second algorithm is preferred. Numerical tests indicate that this new flow (source-side MPV plus ATFT) gives high-quality ADCIGs.

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Data-driven synthesis of primary plane-wave responses

10.5194/egusphere-egu2020-8606 ◽

2020 ◽

Author(s):

Giovanni Angelo Meles ◽

Lele Zhang ◽

Jan Thorbecke ◽

Kees Wapenaar ◽

Evert Slob

Keyword(s):

Plane Wave ◽

Point Sources ◽

Data Driven ◽

Reverse Time ◽

Reverse Time Migration ◽

Wave Source ◽

Time Migration ◽

Source Data ◽

Marine Data ◽

Seismic Images

Seismic images provided by standard Reverse Time Migration are usually contaminated by artefacts associated with the migration of multiples.Multiples can corrupt seismic images by producing both false negatives, i.e. by destructively interfering with primaries, and false positives, i.e. by focusing energy at unphysical interfaces. Free-surface multiples particularly affect seismic images resulting from marine data, while internal multiples strongly contaminate both land and marine data. Multiple prediction / primary synthesis methods are usually designed to operate on point source gathers, and can therefore be computationally &#160;demanding when large problems, involving hundreds of gathers, are considered.In this contribution, a new scheme for fully data-driven retrieval of primary responses of plane-wave sources is presented. The proposed scheme, based on convolutions and cross-correlations of the reflection response with itself, &#160;extends a recently devised Marchenko point-sources primary retrieval method for to plane-wave source data. As a result, the presented algorithm allows fully data-driven synthesis of primary reflections associated with plane-wave source data. Once primary plane-wave responses are estimated, they are used for multiple-free imaging via standard reverse time migration. Numerical tests of increasing complexity demonstrate the potential of the proposed algorithm to produce multiple-free images only involving the migration of few datasets.The plane-wave source primary synthesis algorithm discussed in this contribution could then be used as an initial and unexpensive processing step, potentially guiding more expensive target imaging techniques. Moreover, the method could be applied to large 3D problems for which standard methods are prohibitively expensive from a computational point of view.

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