Separation of signal and coherent noise by migration filtering

Németh, Tamás; Sun, Huiping; Schuster, Gerard T.

doi:10.1190/1.1444753

Cited by 29 publications

(11 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, it is worth noting that for seismic processing tasks several approaches exist that use a specific operator and its adjoint, particularly for data interpolation (Berkhout & Verschuur, 2006;Trad et al, 2002;van Groenestijn & Verschuur, 2009), for multiple prediction (Pica et al, 2005;van Dedem & Verschuur, 2005) and for signal/noise separation (Nemeth et al, 2000). Moreover, we refer to Fomel (2003a) for other applications (stacking, redatuming, offset continuation), for which a technique is proposed to obtain a unitary modeling operator in the context of high frequency approximation.…”

Section: Discussionmentioning

confidence: 99%

Coupling Modeling and Migration for Seismic Imaging

Chauris¹,

Donno²

2012

Seismic Waves - Research and Analysis

View full text Add to dashboard Cite

Section: Discussionmentioning

confidence: 99%

Coupling Modeling and Migration for Seismic Imaging

Chauris¹,

Donno²

2012

Seismic Waves - Research and Analysis

View full text Add to dashboard Cite

“…One possible solution is to filter different order multiples and then migrate a specific order of multiple. Other possible solutions include least squares migration of all events (Brown and Guitton 2005), least squares migration filtering (Nemeth et al . 2000; Yu and Wang 1999) or deconvolution (Calvert et al .…”

Section: Discussionmentioning

confidence: 99%

Migration methods for imaging different‐order multiples

Jiang

Sheng

et al. 2007

Geophysical Prospecting

Self Cite

View full text Add to dashboard Cite

A B S T R A C TMultiples contain valuable information about the subsurface, and if properly migrated can provide a wider illumination of the subsurface compared to imaging with VSP primary reflections. In this paper we review three different methods for migrating multiples. The first method is model-based, and it is more sensitive to velocity errors than primary migration; the second method uses a semi-natural Green's function for migrating multiples, where part of the traveltimes are computed from the velocity model, and part of the traveltimes (i.e., natural traveltimes) are picked from the data to construct the imaging condition for multiples; the third method uses cross-correlation of traces. The last two methods are preferred in the sense that they are significantly less sensitive to velocity errors and statics because they use "natural data" to construct part of the migration imaging conditions. Compared with the interferometric (i.e., crosscorrelation) imaging method the semi-natural Green's function method is more computationally efficient and is sometimes less prone to migration artifacts.Numerical tests with 2-D and 3-D VSP data show that a wider subsurface coverage, higher-fold and more balanced illumination of the subsurface can be achieved with multiple migration compared with migration of primary reflections only. However, there can be strong interference from multiples with different orders or primaries when multiples of high order are migrated. One possible solution is to filter primaries and different orders of multiples before migration, and another possible solution is least squares migration of all events. A limitation of multiple migration is encountered for subsalt imaging. Here, the multiples must pass through the salt body more than twice, which amplifies the distortion of the image.

show abstract

“…To suppress these artifacts, we apply LSM to the data. Similar to standard LSM, crosstalk artifacts in model space (Nemeth and Schuster, 1997;Nemeth et al, 2000) will produce unexplainable artifacts in the forward modeled traces that increase the data residuals, and so increase the value of the misfit function. To remedy this problem, an iterative optimization procedure seeks a reflectivity model that minimizes these reflectivity artifacts.…”

Section: Rtm Of Multiplesmentioning

confidence: 97%

“…An advantage of interferometric redatuming is that it can be computed in a least squares sense to mitigate artifacts due to gaps in the receiver coverage (Wapenaar et al, 2011). There is another opportunity to reduce artifacts, and this is with the LSM algorithm that has been shown (Nemeth and Schuster, 1997;Nemeth et al, 2000) to reduce artifacts due to aliased data and gaps in the recording geometry. Finally, because the multiples are interferometrically transformed into virtual primaries, migration of these virtual primaries is no more sensitive to velocity errors than standard migration of primaries.…”

Section: Rtm Of Multiplesmentioning

confidence: 97%

“…If the primary reflections have a significantly smaller moveout than the multiple reflections, the data transformed into the parabolic (Hampson, 1986) or hyperbolic Radon domains (Foster and Mosher, 1992) can be used to mute out the multiples. Another demultiple method is the model-based attenuation of multiples (Liu, 1996;Nemeth and Schuster, 1997;Nemeth et al, 2000;Yu, 2004;Brown and Guitton, 2005). This method exploits the spatial predictability of noise and signal with least-squares migration (LSM) filtering.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Least-squares reverse time migration of multiples

2014

Self Cite

View full text Add to dashboard Cite

The theory of least-squares reverse time migration of multiples (RTMM) is presented. In this method, least squares migration (LSM) is used to image free-surface multiples where the recorded traces are used as the time histories of the virtual sources at the hydrophones and the surface-related multiples are the observed data. For a single source, the entire free-surface becomes an extended virtual source where the downgoing freesurface multiples more fully illuminate the subsurface compared to the primaries. Since each recorded trace is treated as the time history of a virtual source, knowledge of the source wavelet is not required and the ringy time series for each source is automatically deconvolved. If the multiples can be perfectly separated from the primaries, numerical tests on synthetic data for the Sigsbee2B and Marmousi2 models show that leastsquares reverse time migration of multiples (LSRTMM) can significantly improve the image quality compared to RTMM or standard reverse time migration (RTM) of primaries. However, if there is imperfect separation and the multiples are strongly interfering with the primaries then LSRTMM images show no significant advantage over the primary migration images.In some cases, they can be of worse quality. Applying LSRTMM to Gulf of Mexico data shows higher signal-to-noise imaging of the salt bottom and top compared to standard RTM images. This is likely attributed to the fact that the target body is just below the sea bed so that the deep water multiples do not have strong interference with the primaries. Migrating a sparsely sampled version of the Marmousi2 ocean bottom seismic data shows that LSM of primaries and LSRTMM provides significantly better imaging than standard RTM.A potential liability of LSRTMM is that multiples require several round trips between the reflector and the free surface, so that high frequencies in the multiples suffer greater attenuation compared to the primary reflections. This can lead to lower resolution in the migration image compared to that computed from primaries. Another liability is that the multiple migration image is more down-dip limited than the standard primaries migration image. Finally, if the surface-related multiple elimination method is imperfect and there are strong multiples interfering with the primaries, then the resulting LSRTMM image can be significantly degraded. We conclude that LSRTMM can be a useful complement, not a replacement, for RTM of primary reflections.

show abstract

Separation of signal and coherent noise by migration filtering

Cited by 29 publications

References 11 publications

Coupling Modeling and Migration for Seismic Imaging

Coupling Modeling and Migration for Seismic Imaging

Migration methods for imaging different‐order multiples

Least-squares reverse time migration of multiples

Contact Info

Product

Resources

About