Dual-sensor Enhanced 3D Surface-related Multiple Elimination

Author(s):  
R. F. Hegge ◽  
P. Aaron ◽  
S. Barnes ◽  
R. van Borselen
Geophysics ◽  
2007 ◽  
Vol 72 (5) ◽  
pp. SM241-SM250 ◽  
Author(s):  
Bruce J. VerWest ◽  
Dechun Lin

Wide-azimuth towed streamer (WATS) acquisition improves the subsalt seismic image by suppressing multiples, improves the results of 3D surface-related-multiple elimination (SRME) processing, and provides more uniform seismic illumination of subsalt targets. A simple model shows that the additional suppression of multiples in the case of WATS acquisition is the result of a natural weighting of the traces going into the stack due to the areal nature of the acquisition. This simple model also shows that the extent of the additional multiple suppression is strongly dependent on the acquisition effort. A sparse acquisition effort will result in little additional multiple suppression. The use of 3D SRME processing is shown to be more accurate in predicting multiples, given input data with multiple azimuths, compared to making similar predictions from narrow-azimuth data. Three-dimensional SRME has the potential to reduce the residual multiples to the same extent as WATS acquisition with a higher acquisition effort. A complex model demonstrates that WATS acquisition does reduce the multiple-generated noise in subsalt images, but 3D SRME processing further reduces the residual multiple noise. The use of 3D SRME may reduce the multiples more than that achieved by increasing the cable half-aperture in the WATS acquisition effort. Finally, ray trace modeling is used to investigate the effect of WATS acquisition on subsurface illumination for subsalt imaging. We show that narrow-azimuth acquisition produces irregularities in subsalt illumination perpendicular to the acquisition direction which are a potential cause of migration noise. WATS acquisition results in higher and more uniform subsalt illumination and, hence, improves the subsalt image by reducing subsalt migration noise.


2005 ◽  
Vol 24 (3) ◽  
pp. 260-268 ◽  
Author(s):  
R. G. van Borselen ◽  
M. A. Schonewille ◽  
R. F. Hegge

Geophysics ◽  
2010 ◽  
Vol 75 (5) ◽  
pp. 75A245-75A261 ◽  
Author(s):  
Bill Dragoset ◽  
Eric Verschuur ◽  
Ian Moore ◽  
Richard Bisley

Surface-related multiple elimination (SRME) is an algorithm that predicts all surface multiples by a convolutional process applied to seismic field data. Only minimal preprocessing is required. Once predicted, the multiples are removed from the data by adaptive subtraction. Unlike other methods of multiple attenuation, SRME does not rely on assumptions or knowledge about the subsurface, nor does it use event properties to discriminate between multiples and primaries. In exchange for this “freedom from the subsurface,” SRME requires knowledge of the acquisition wavelet and a dense spatial distribution of sources and receivers. Although a 2D version of SRME sometimes suffices, most field data sets require 3D SRME for accurate multiple prediction. All implementations of 3D SRME face a serious challenge: The sparse spatial distribution of sources and receivers available in typical seismic field data sets does not conform to the algorithmic requirements. There are several approaches to implementing 3D SRME that address the data sparseness problem. Among those approaches are pre-SRME data interpolation, on-the-fly data interpolation, zero-azimuth SRME, and true-azimuth SRME. Field data examples confirm that (1) multiples predicted using true-azimuth 3D SRME are more accurate than those using zero-azimuth 3D SRME and (2) on-the-fly interpolation produces excellent results.


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