Eliminating artifacts in migration of surface-related multiples: An application to marine data

2016 ◽  
Vol 4 (4) ◽  
pp. SQ51-SQ57 ◽  
Author(s):  
Yikang Zheng ◽  
Yibo Wang ◽  
Xu Chang
Keyword(s):  
Radon Transform ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Seismic Events ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Migration ◽  
Valuable Complement ◽  
Marine Data ◽  
The One

Migration of multiples can use surface-related multiples to provide extra illumination of the subsurface; however, the migrated images usually contain many migration artifacts. We have developed an efficient workflow to eliminate the artifacts in migration of surface-related multiples and applied it to marine data. Our workflow was based on the criterion that true seismic events in angle-domain common-image gathers (ADCIGs) should be flat. The ADCIGs were obtained via the one-way wave-equation migration and then processed by high-resolution parabolic Radon transform to separate the artifacts. Using the adjoint Radon transform, the filtered ADCIGs can be stacked to get the final image with a high signal-to-noise ratio. We also discovered that the ADCIGs can be extracted from Fourier finite-difference migration more efficiently than by reverse time migration. In the application to marine data, most noise generated by the crosscorrelation of undesired seismic events was suppressed. This shows that the final images can be a valuable complement to conventional migration using primaries only.

scholarly journals Least-squares reverse time migration with local Radon-based preconditioning

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. S75-S84 ◽  
Author(s):  
Gaurav Dutta ◽  
Matteo Giboli ◽  
Cyril Agut ◽  
Paul Williamson ◽  
Gerard T. Schuster
Keyword(s):  
Least Squares ◽  
Radon Transform ◽  
Field Data ◽  
Signal To Noise Ratio ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Inverse Mapping ◽  
Time Migration ◽  
Discrete Radon Transform ◽  
L2 Norm

Least-squares migration (LSM) can produce images with better balanced amplitudes and fewer artifacts than standard migration. The conventional objective function used for LSM minimizes the L2-norm of the data residual between the predicted and the observed data. However, for field-data applications in which the recorded data are noisy and undersampled, the conventional formulation of LSM fails to provide the desired uplift in the quality of the inverted image. We have developed a least-squares reverse time migration (LSRTM) method using local Radon-based preconditioning to overcome the low signal-to-noise ratio (S/N) problem of noisy or severely undersampled data. A high-resolution local Radon transform of the reflectivity is used, and sparseness constraints are imposed on the inverted reflectivity in the local Radon domain. The sparseness constraint is that the inverted reflectivity is sparse in the Radon domain and each location of the subsurface is represented by a limited number of geologic dips. The forward and the inverse mapping of the reflectivity to the local Radon domain and vice versa is done through 3D Fourier-based discrete Radon transform operators. The weights for the preconditioning are chosen to be varying locally based on the relative amplitudes of the local dips or assigned using quantile measures. Numerical tests on synthetic and field data validate the effectiveness of our approach in producing images with good S/N and fewer aliasing artifacts when compared with standard RTM or standard LSRTM.

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>

Full Wavefield Least-Squares Reverse Time Migration

Geophysics ◽  
2021 ◽  
pp. 1-48
Author(s):  
Mikhail Davydenko ◽  
Eric Verschuur
Keyword(s):  
Wave Equation ◽  
Least Squares ◽  
Input Data ◽  
Waveform Inversion ◽  
Secondary Source ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Migration ◽  
Internal Multiples ◽  
The One

Waveform inversion based on Least-Squares Reverse Time Migration (LSRTM) usually involves Born modelling, which models the primary-only data. As a result the inversion process handles only primaries and corresponding multiple elimination pre-processing of the input data is required prior to imaging and inversion. Otherwise, multiples left in the input data are mapped as false reflectors, also known as crosstalk, in the final image. At the same time the developed Full Wavefield Migration (FWM) methodology can handle internal multiples in an inversion-based imaging process. However, because it is based on the framework of the one-way wave equation, it cannot image dips close to and beyond 90 degrees. Therefore, we aim at upgrading LSRTM framework by bringing functionality of FWM to handle internal multiples. We have discovered that the secondary source term, used in the original formulation of FWM to define a wavefield relationship that allows to model multiple scattering via reflectivity, can be injected into a pressure component when simulating the two-way wave equation using finite-difference modelling. We use this modified forward model for estimating the reflectivity model with automatic crosstalk supression and validate the method on both synthetic and field data containing visible internal multiples.

scholarly journals Least-squares reverse time migration of marine data with frequency-selection encoding

Geophysics ◽  
2013 ◽  
Vol 78 (4) ◽  
pp. S233-S242 ◽  
Author(s):  
Wei Dai ◽  
Yunsong Huang ◽  
Gerard T. Schuster
Keyword(s):  
Least Squares ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Data Set ◽  
Frequency Selection ◽  
Time Migration ◽  
Order Of Magnitude ◽  
Marine Data ◽  
And Migration ◽  
Encoding Method

The phase-encoding technique can sometimes increase the efficiency of the least-squares reverse time migration (LSRTM) by more than one order of magnitude. However, traditional random encoding functions require all the encoded shots to share the same receiver locations, thus limiting the usage to seismic surveys with a fixed spread geometry. We implement a frequency-selection encoding strategy that accommodates data with a marine streamer geometry. The encoding functions are delta functions in the frequency domain, so that all the encoded shots have unique nonoverlapping frequency content, and the receivers can distinguish the wavefield from each shot with a unique frequency band. Because the encoding functions are orthogonal to each other, there will be no crosstalk between different shots during modeling and migration. With the frequency-selection encoding method, the computational efficiency of LSRTM is increased so that its cost is comparable to conventional RTM for the Marmousi2 model and a marine data set recorded in the Gulf of Mexico. With more iterations, the LSRTM image quality is further improved by suppressing migration artifacts, balancing reflector amplitudes, and enhancing the spatial resolution. We conclude that LSRTM with frequency-selection is an efficient migration method that can sometimes produce more focused images than conventional RTM.

Least-squares reverse time migration of multiples in viscoacoustic media

Geophysics ◽  
2020 ◽  
Vol 85 (5) ◽  
pp. S285-S297
Author(s):  
Zhina Li ◽  
Zhenchun Li ◽  
Qingqing Li ◽  
Qingyang Li ◽  
Miaomiao Sun ◽  
...  
Keyword(s):  
Least Squares ◽  
Signal To Noise Ratio ◽  
Real Data ◽  
Velocity Model ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Migration ◽  
Q Model ◽  
Standard Linear Solid ◽  
Standard Linear

The migration of multiples can provide complementary information about the subsurface, but crosstalk artifacts caused by the interference between different-order multiples reduce its reliability. To mitigate the crosstalk artifacts, least-squares reverse time migration (LSRTM) of multiples is suggested by some researchers. Multiples are more affected by attenuation than primaries because of the longer travel path. To avoid incorrect waveform matching during the inversion, we propose to include viscosity in the LSRTM implementation. A method of LSRTM of multiples is introduced based on a viscoacoustic wave equation, which is derived from the generalized standard linear solid model. The merit of the proposed method is that it not only compensates for the amplitude loss and phase change, which cannot be achieved by traditional RTM and LSRTM of multiples, but it also provides more information about the subsurface with fewer crosstalk artifacts by using multiples compared with the viscoacoustic LSRTM of primaries. Tests on sensitivity to the errors in the velocity model, the Q model, and the separated multiples reveal that accurate models and input multiples are vital to the image quality. Numerical tests on synthetic models and real data demonstrate the advantages of our approach in improving the quality of the image in terms of amplitude balancing and signal-to-noise ratio.

Reverse time migration of multiples: Eliminating migration artifacts in angle domain common image gathers

Geophysics ◽  
2014 ◽  
Vol 79 (6) ◽  
pp. S263-S270 ◽  
Author(s):  
Yibo Wang ◽  
Yikang Zheng ◽  
Lele Zhang ◽  
Xu Chang ◽  
Zhenxing Yao
Keyword(s):  
Free Surface ◽  
Radon Transform ◽  
Synthetic Data ◽  
Velocity Model ◽  
Migration Velocity ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Data Set ◽  
Time Migration ◽  
Nonzero Curvature

Free-surface-related multiples are usually regarded as noise in conventional seismic processing. However, they can provide extra illumination of the subsurface and thus have been used in migration procedures, e.g., in one- and two-way wave-equation migrations. The disadvantage of the migration of multiples is the migration artifacts generated by the crosscorrelation of different seismic events, e.g., primaries and second-order free-surface-related multiples, so the effective elimination of migration artifacts is crucial for migration of multiples. The angle domain common image gather (ADCIG) is a suitable domain for testing the correctness of a migration velocity model. When the migration velocity model is correct, all the events in ADCIGs should be flat, and this provides a criterion for removing the migration artifacts. Our approach first obtains ADCIGs during reverse time migration and then applies a high-resolution parabolic Radon transform to all ADCIGs. By doing so, most migration artifacts will reside in the nonzero curvature regions in the Radon domain, and then a muting procedure can be implemented to remove the data components outside the vicinity of zero curvature. After the application of an adjoint Radon transform, the filtered ADCIGs are obtained and the final denoised migration result is generated by stacking all filtered ADCIGs. A three-flat-layer velocity model and the Marmousi synthetic data set are used for numerical experiments. The numerical results revealed that the proposed approach can eliminate most artifacts generated by migration of multiples when the migration velocity model is correct.

3D angle gathers with plane-wave reverse-time migration

Geophysics ◽  
2013 ◽  
Vol 78 (2) ◽  
pp. S117-S123 ◽  
Author(s):  
Bing Tang ◽  
Sheng Xu ◽  
Yu Zhang
Keyword(s):  
Plane Wave ◽  
Low Cost ◽  
Seismic Events ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Amplitude Analysis ◽  
Time Migration ◽  
Shallow Seismic ◽  
Small Incidence ◽  
Promising Solution

Angle domain common image gathers (ADCIGs) from reverse-time migration (RTM) provide new tools for imaging complex geologic structures, such as salt flank or subsalt areas, characterized by multiarrivals. Compared with common image gathers from Kirchoff or Beam migration, the ADCIGs from RTM have the advantage of relying on wave propagation, providing a more reliable input for tomography or amplitude analysis. In practice however, most current wide azimuth surveys (e.g., deep-water regions of the Gulf of Mexico) are acquired with coarsely sampled shot and receiver locations on the surface, which leads to severe angular undersampling. This phenomenon is frequently observed on shallow seismic events in high-resolution 3D ADCIGs from common-shot RTM. In addition, because small offsets are frequently not recorded, seismic events are missing at small incidence angles in angle gathers. We have made a detailed study of the angular sampling issue in 3D angle gathers. We then used plane-wave RTM to generate 3D angle gathers. Plane-wave RTM, with its low-cost and automatic angular interpolation, is a promising solution for improving the quality of 3D angle gathers.

Two methods for computing the imaging condition for common‐shot prestack migration

Geophysics ◽  
1991 ◽  
Vol 56 (3) ◽  
pp. 378-381 ◽  
Author(s):  
D. Loewenthal ◽  
Liang‐zie Hu
Keyword(s):  
Seismic Data ◽  
Grid Point ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Imaging Condition ◽  
Prestack Migration ◽  
Time Zero ◽  
Time Migration ◽  
Excitation Time ◽  
The One

This note addresses two methods of computing the imaging condition for prestack migration of common‐shot seismic data; our work is based on the ideas from reverse‐time migration for both poststack (Loewenthal and Mufti, 1983; McMechan, 1983) and prestack data (Chang and McMechan, 1986). In reverse‐time migration of poststack data, the whole stacked section is backward‐extrapolated in time, with half of the medium velocity to time zero. All exploding reflectors are imaged at once at time zero. The time zero is referred to as the imaging condition. In prestack migration, the imaging condition is more involved. Each spatial grid point (treated as a point diffractor) has a different excitation time, which is equal to the one‐way traveltime from the source to that grid point. Each point diffractor is imaged separately at its excitation (the “imaging time”).

Automatic waveform-based source-location imaging using deep learning extracted microseismic signals

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. KS171-KS183 ◽  
Author(s):  
Omar M. Saad ◽  
Yangkang Chen
Keyword(s):  
Clustering Algorithm ◽  
Signal To Noise Ratio ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Frequency ◽  
Time Migration ◽  
Frequency Representation ◽  
Convolutional Autoencoder ◽  
Migration Method

We have used an automatic unsupervised technique to extract waveform signals from continuous microseismic data. First, the time-frequency representation (scalogram) is obtained for the input microseismic trace. Second, the convolutional autoencoder (CAE) is used to extract the significant scalogram features related to the waveform signals and discard the rest. Third, the extracted features from the CAE encoder are considered as the input for the k-means clustering algorithm, in which the input samples are classified into waveform and nonwaveform components. The proposed algorithm is evaluated using several synthetic and field examples. We find that the proposed algorithm successfully extracts the waveform signals even in a noisy environment with a signal-to-noise-ratio as low as −10 dB. We compared the proposed algorithm to benchmark algorithms, for example, simple k-means and short-term and long-term average ratio methods, and find that the proposed algorithm performs best. We find that the detected waveform signals can enhance the resolution of microseismic imaging using a waveform-based reverse time migration method.

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