Reverse time migration of phase encoded all-order multiples

Geophysics ◽  
2021 ◽  
pp. 1-42
Author(s):  
Yike Liu ◽  
Yanbao Zhang ◽  
Yingcai Zheng
Keyword(s):  
Virtual Source ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Phase Encoding ◽  
Seismic Migration ◽  
Computational Costs ◽  
Time Migration ◽  
Source Data ◽  
Decomposition Strategies

Multiples follow long paths and carry more information on the subsurface than primary reflections, making them particularly useful for imaging. However, seismic migration using multiples can generate crosstalk artifacts in the resulting images because multiples of different orders interfere with each others, and crosstalk artifacts greatly degrade the quality of an image. We propose to form a supergather by applying phase-encoding functions to image multiples and stacking several encoded controlled-order multiples. The multiples are separated into different orders using multiple decomposition strategies. The method is referred to as the phase-encoded migration of all-order multiples (PEM). The new migration can be performed by applying only two finite-difference solutions to the wave equation. The solutions include backward-extrapolating the blended virtual receiver data and forward-propagating the summed virtual source data. The proposed approach can significantly attenuate crosstalk artifacts and also significantly reduce computational costs. Numerical examples demonstrate that the PEM can remove relatively strong crosstalk artifacts generated by multiples and is a promising approach for imaging subsurface targets.

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

Geophysics ◽  
2018 ◽  
Vol 83 (1) ◽  
pp. S33-S46 ◽  
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.

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

Geophysics ◽  
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.

An efficient vector elastic reverse time migration method in the hybrid time and frequency domain for anisotropic media

Geophysics ◽  
2019 ◽  
Vol 84 (6) ◽  
pp. S511-S522 ◽  
Author(s):  
Kai Gao ◽  
Lianjie Huang
Keyword(s):  
Frequency Domain ◽  
Anisotropic Media ◽  
Reverse Time ◽  
Computationally Efficient ◽  
Reverse Time Migration ◽  
Computational Costs ◽  
Time Migration ◽  
Migration Imaging ◽  
Efficient Vector ◽  
Wave Migration

Vector elastic reverse time migration (ERTM) produces subsurface elastic images with correct polarities using multicomponent seismic data. However, the decomposition of elastic wavefields into vector P- and S-wavefields is computationally expensive, particularly in heterogeneous and complex anisotropic media. We have developed a computationally efficient vector ERTM method in the hybrid time and frequency domain by combining three existing techniques. Rather than decomposing elastic wavefields into vector qP- and qS-wavefields during time-domain wavefield propagation, we conduct the wavefield decomposition in the frequency domain for several selected frequencies. In general, the number of selected frequencies needed for migration imaging is much smaller than the number of time steps during forward and backward wavefield propagation, leading to greatly reduced computational costs associated with the qP-/qS-wavefield vector separation in complex heterogeneous anisotropic media. We further combine an implicit directional wavefield separation into the vector ERTM to enhance the image quality. The numerical results demonstrate that our method produces high-quality elastic-wave migration images with notably reduced computational costs compared to the conventional vector ERTM method.

Data-driven synthesis of primary plane-wave responses

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

<p>Seismic images provided by standard Reverse Time Migration are usually contaminated by artefacts associated with the migration of multiples.</p><p>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  demanding when large problems, involving hundreds of gathers, are considered.</p><p>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,  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.</p><p>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.</p>

Five ways to avoid storing source wavefield snapshots in 2D elastic prestack reverse time migration

Geophysics ◽  
2015 ◽  
Vol 80 (1) ◽  
pp. S1-S18 ◽  
Author(s):  
Bao D. Nguyen ◽  
George A. McMechan
Keyword(s):  
Random Access ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Access Memory ◽  
Additional Source ◽  
Time Migration ◽  
Elastic Data ◽  
The Cost ◽  
Imaging Conditions

Five alternative algorithms were evaluated to circumvent the excessive storage requirement imposed by saving source wavefield snapshots used for the crosscorrelation image condition in 2D prestack elastic reverse time migration. We compared the algorithms on the basis of their ability, either to accurately reconstruct (not save) the source wavefield or to use an alternate image condition so that neither saving nor reconstruction of full wavefields was involved. The comparisons were facilitated by using the same (velocity-stress) extrapolator in all the algorithms, and running them all on the same hardware. We assumed that there was enough memory in a node to do an extrapolation, and that all input data were stored on disk rather than residing in random-access memory. This should provide a fair and balanced comparison. Reconstruction of the source wavefield from boundary and/or initial values reduced the required storage to a very small fraction of that needed to store source wavefield snapshots for conventional crosscorrelation, at the cost of adding an additional source extrapolation. Reverse time checkpointing avoided recursive forward recomputation. Two nonreconstructive imaging conditions do not require full snapshot storage or an additional extrapolation. Time-binning the imaging criteria removed the need for image time searching or sorting. Numerical examples using elastic data from the Marmousi2 model showed that the quality of the elastic prestack PP and PS images produced by the cost-optimized alternative algorithms were (virtually) identical to the higher cost images produced by traditional crosscorrelation.

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