3D angle decomposition for elastic reverse time migration

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. S377-S389
Author(s):  
Yuting Duan ◽  
Paul Sava
Keyword(s):  
Field Data ◽  
Time Lag ◽  
Image Point ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Converted Wave ◽  
The Third ◽  
Time Migration ◽  
Straight Lines ◽  
2D And 3D

We have developed three approaches for 3D angle decomposition using elastic reverse time migration. The first approach uses time- and space-lag common-image point gathers computed from elastic wavefields. This method facilitates computing angle gathers at sparse and possibly irregularly distributed points in the image. The second approach transforms extended time-lag images to the angle domain using slant stacks along 4D surfaces, instead of using slant stacks along 2D straight lines. The third approach transforms space-lag common-image gathers to the angle domain. The three proposed methods solve a system of equations that handles dipping reflectors, and they yield angle gathers that are more accurate compared with those obtained via alternative existing methods. We have developed our methods using 2D and 3D synthetic and field data examples and found that they provide accurate opening and azimuth angles and they can handle steeply dipping reflectors and converted wave modes.

Automatic velocity analysis with reverse-time migration

Geophysics ◽  
2013 ◽  
Vol 78 (4) ◽  
pp. S179-S192 ◽  
Author(s):  
Wiktor Waldemar Weibull ◽  
Børge Arntsen
Keyword(s):  
Field Data ◽  
Similarity Index ◽  
Optimization Procedure ◽  
Image Point ◽  
Frequency Noise ◽  
Velocity Analysis ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Migration ◽  
Resultant Velocity

We apply a method to automatically estimate the background velocities using reverse-time migration. The method uses a combination of differential semblance and similarity-index (a.k.a., “semblance” or “stacking-power”) to measure the focusing error in imaging and a nonlinear optimization procedure to obtain the background velocities. A challenge in this procedure is that, for media consisting of complex and strongly refracting velocities, artifacts in the reverse-time migrated image (low-frequency noise) can cause the velocity analysis to diverge. We successfully overcome this issue by applying a simple vertical derivative filter to the image that is input to velocity analysis. The resultant velocity analysis method is tested in two 2D synthetic examples and one 2D field data example. Due to the assumptions inherent to prestack depth migration, the data that are input to velocity analysis must be singly scattered. To apply the method to multiple-rich data, we propose an image-based demultiple method. The method consists of muting events in the subsurface offset common image point gathers constructed with reverse-time migration, and remodeling the data using a kinematic demigration. A field data example shows how the image-based demultiple of the data helps to improve the velocity analysis in the presence of multiple scattering.

Vector-based elastic reverse time migration based on scalar imaging condition

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. S111-S127 ◽  
Author(s):  
Qizhen Du ◽  
ChengFeng Guo ◽  
Qiang Zhao ◽  
Xufei Gong ◽  
Chengxiang Wang ◽  
...  
Keyword(s):  
Alternative Methods ◽  
Polarity Reversal ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
S Wave ◽  
Converted Wave ◽  
Imaging Condition ◽  
Time Migration ◽  
Wavefield Separation ◽  
Wave Modes

The scalar images (PP, PS, SP, and SS) of elastic reverse time migration (ERTM) can be generated by applying an imaging condition as crosscorrelation of pure wave modes. In conventional ERTM, Helmholtz decomposition is commonly applied in wavefield separation, which leads to a polarity reversal problem in converted-wave images because of the opposite polarity distributions of the S-wavefields. Polarity reversal of the converted-wave image will cause destructive interference when stacking over multiple shots. Besides, in the 3D case, the curl calculation generates a vector S-wave, which makes it impossible to produce scalar PS, SP, and SS images with the crosscorrelation imaging condition. We evaluate a vector-based ERTM (VB-ERTM) method to address these problems. In VB-ERTM, an amplitude-preserved wavefield separation method based on decoupled elastic wave equation is exploited to obtain the pure wave modes. The output separated wavefields are both vectorial. To obtain the scalar images, the scalar imaging condition in which the scalar product of two vector wavefields with source-normalized illumination is exploited to produce scalar images instead of correlating Cartesian components or magnitude of the vector P- and S-wave modes. Compared with alternative methods for correcting the polarity reversal of PS and SP images, our ERTM solution is more stable and simple. Besides these four scalar images, the VB-ERTM method generates another PP-mode image by using the auxiliary stress wavefields. Several 2D and 3D numerical examples are evaluated to demonstrate the potential of our ERTM method.

Improving input/output performance in 2D and 3D angle-domain common-image gathers from reverse time migration

Geophysics ◽  
2015 ◽  
Vol 80 (2) ◽  
pp. S65-S77 ◽  
Author(s):  
Hu Jin ◽  
George A. McMechan ◽  
Bao Nguyen
Keyword(s):  
Velocity Model ◽  
Normal Direction ◽  
Propagation Direction ◽  
Input Output ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Step ◽  
Phase Gradient ◽  
Time Migration ◽  
2D And 3D

We have developed a new method of extracting angle-domain common-image gathers (ADCIGs) from prestack reverse time migration (RTM) that has minimal intermediate storage requirements. To include multipathing, we applied an imaging condition for prestack RTM that uses multiple excitation image times. Instead of saving the full-source snapshots at all time steps, we picked and saved only a few of the highest amplitude arrivals, and their corresponding excitation times, of the source wavefield at each grid point, and we crosscorrelated with the receiver wavefield. When extracting the ADCIGs from RTM, we calculated the source propagation direction from the gradient of the excitation times. The result was that the source time snapshots do not have to be saved or reconstructed during RTM or while extracting ADCIGs. We calculated the receiver propagation direction from Poynting vectors during the receiver extrapolation at each time step and the reflector normal direction by the phase-gradient method. With a new strategy that uses three direction vectors (the source and receiver propagation directions as well as the reflector normal direction), we provided more reliable ADCIGs that are free of low-wavenumber artifacts than any two of them do separately, when the migration velocity model was near to the correct velocity model. The 2D and 3D synthetic tests demonstrated the successful application of the new algorithms with acceptable accuracy, improved storage efficiency, and without an input/output bottleneck.

Multicomponent and source-free converted-wave reverse time migration for VSP

2018 ◽  
Author(s):  
Yue Du ◽  
Yunyue Elita Li ◽  
Jizhong Yang ◽  
Arthur Cheng ◽  
Xinding Fang
Keyword(s):  
Reverse Time ◽  
Reverse Time Migration ◽  
Converted Wave ◽  
Time Migration

scholarly journals Converted-wave seismic imaging: Amplitude-balancing source-independent imaging conditions

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. S99-S109 ◽  
Author(s):  
Andrey H. Shabelansky ◽  
Alison Malcolm ◽  
Michael Fehler
Keyword(s):  
Wave Speed ◽  
Attractive Alternative ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Converted Wave ◽  
Time Migration ◽  
Wave Imaging ◽  
Conversion Coefficients ◽  
The Relationship ◽  
Imaging Conditions

We have developed crosscorrelational and deconvolutional forms of a source-independent converted-wave imaging condition (SICW-IC) and show the relationship between them using a concept of conversion ratio coefficient, a concept that we developed through reflection, transmission, and conversion coefficients. We applied the SICW-ICs to a two half-space model and the synthetic Marmousi I and II models and show the sensitivity of the SICW-ICs to incorrect wave speed models. We also compare the SICW-ICs and source-dependent elastic reverse time migration. The results of SICW-ICs highlight the improvements in spatial resolution and amplitude balancing with the deconvolutional forms. This is an attractive alternative to active and passive source elastic imaging.

Reverse time migration for microseismic sources using the geometric mean as an imaging condition

Geophysics ◽  
2016 ◽  
Vol 81 (2) ◽  
pp. KS51-KS60 ◽  
Author(s):  
Nori Nakata ◽  
Gregory C. Beroza
Keyword(s):  
Time Reversal ◽  
Geometric Mean ◽  
Time Lag ◽  
Computational Cost ◽  
Velocity Model ◽  
Seismic Sources ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Imaging Condition ◽  
Time Migration

Time reversal is a powerful tool used to image directly the location and mechanism of passive seismic sources. This technique assumes seismic velocities in the medium and propagates time-reversed observations of ground motion at each receiver location. Assuming an accurate velocity model and adequate array aperture, the waves will focus at the source location. Because we do not know the location and the origin time a priori, we need to scan the entire 4D image (3D in space and 1D in time) to localize the source, which makes time-reversal imaging computationally demanding. We have developed a new approach of time-reversal imaging that reduces the computational cost and the scanning dimensions from 4D to 3D (no time) and increases the spatial resolution of the source image. We first individually extrapolate wavefields at each receiver, and then we crosscorrelate these wavefields (the product in the frequency domain: geometric mean). This crosscorrelation creates another imaging condition, and focusing of the seismic wavefields occurs at the zero time lag of the correlation provided the velocity model is sufficiently accurate. Due to the analogy to the active-shot reverse time migration (RTM), we refer to this technique as the geometric-mean RTM or GmRTM. In addition to reducing the dimension from 4D to 3D compared with conventional time-reversal imaging, the crosscorrelation effectively suppresses the side lobes and yields a spatially high-resolution image of seismic sources. The GmRTM is robust for random and coherent noise because crosscorrelation enhances signal and suppresses noise. An added benefit is that, in contrast to conventional time-reversal imaging, GmRTM has the potential to be used to retrieve velocity information by analyzing time and/or space lags of crosscorrelation, which is similar to what is done in active-source imaging.

Improved subsalt images with least-squares reverse time migration

2017 ◽  
Vol 5 (3) ◽  
pp. SN25-SN32 ◽  
Author(s):  
Ping Wang ◽  
Shouting Huang ◽  
Ming Wang
Keyword(s):  
Least Squares ◽  
Field Data ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Lateral Velocity ◽  
Image Domain ◽  
Time Migration ◽  
Iterative Inversion ◽  
Velocity Variations ◽  
Subsalt Imaging

Complex overburdens often distort reservoir images in terms of structural positioning, stratigraphic resolution, and amplitude fidelity. One prime example of a complex overburden is in the deepwater Gulf of Mexico, where thick and irregular layers of remobilized (i.e., allochthonous) salt are situated above prospective reservoir intervals. The highly variant salt layers create large lateral velocity variations that distort wave propagation and the illumination of deeper reservoir targets. In subsalt imaging, tools such as reflection tomography, full-waveform inversion, and detailed salt interpretation are needed to derive a high-resolution velocity model that captures the lateral velocity variations. Once a velocity field is obtained, reverse time migration (RTM) can be applied to restore structural positioning of events below and around the salt. However, RTM by nature is unable to fully recover the reflectivity for desired amplitudes and resolution. This shortcoming is well-recognized by the imaging community, and it has propelled the emergence of least-squares RTM (LSRTM) in recent years. We have investigated how current LSRTM methods perform on subsalt images. First, we compared the formulation of data-domain versus image-domain least-squares migration, as well as methods using single-iteration approximation versus iterative inversion. Then, we examined the resulting subsalt images of several LSRTM methods applied on the synthetic and field data. Among our tests, we found that image-domain single-iteration LSRTM methods, including an extension of an approximate inverse Hessian method in the curvelet domain, not only compensated for amplitude loss due to poor illumination caused by complex salt bodies, but it also produced subsalt images with fewer migration artifacts in the field data. In contrast, an iterative inversion method showed its potential for broadening the bandwidth in the subsalt, but it was less effective in reducing migration artifacts and noise. Based on our understanding, we evaluated the current state of LSRTM for subsalt imaging.

Anisotropic migration velocity analysis using reverse-time migration

Geophysics ◽  
2014 ◽  
Vol 79 (1) ◽  
pp. R13-R25 ◽  
Author(s):  
Wiktor Waldemar Weibull ◽  
Børge Arntsen
Keyword(s):  
Wave Equation ◽  
Seismic Anisotropy ◽  
Migration Velocity ◽  
Image Point ◽  
Velocity Analysis ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Migration ◽  
Migration Velocity Analysis ◽  
Isotropic Media

Seismic anisotropy, if not accounted for, can cause significant mispositioning of the reflectors in depth-migrated images. Accounting for anisotropy in depth migration requires velocity analysis tools that can estimate the anisotropic background velocity field. We extended wave equation migration velocity analysis to deal with 2D tilted transverse isotropic media. The velocities were obtained automatically by nonlinear optimization of the focusing and stack power of common-image point gathers constructed using an extended imaging condition. We used the elastic two-way wave equation to reconstruct the wavefields needed for the image and gradient computations. This led to an anisotropic migration velocity analysis algorithm based on reverse-time migration. We illustrated the method with synthetic and field data examples based on marine surface seismic acquisition. The results showed that the method significantly improves the quality of the depth-migrated image. However, as is common in the case of velocity analysis using surface seismic data, the estimation of anisotropic parameters seems to be strongly nonunique.

An application of vector wavefield decomposition to 3D elastic reverse time migration and field data test

2019 ◽  
Vol 131 ◽  
pp. 112-131 ◽  
Author(s):  
Bingluo Gu ◽  
Zhiming Ren ◽  
Qingqing Li ◽  
Jianguang Han ◽  
Zhenchun Li
Keyword(s):  
Field Data ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Migration ◽  
Wavefield Decomposition
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