Leveraging the Value of Multi-azimuth (MAZ) Seismic through MAZ-stack

Manning, Ted; Page, Chris; Hall, Stephen A.; Keggin, J.; Barley, Brian; Rietveld, W.; Frømyr, Eivind; Borselen, Roald van

doi:10.3997/2214-4609.20147722

Cited by 7 publications

(7 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many such image conditioning and enhancement algorithms and methods have been shown to be highly effective at suppressing random noise by coherency or crosscorrelation-weighted stack (Liu et al 2009;Zamboni et al 2012), and improving signal stacking power by selective stacking (Xu et al 2011) or by residual moveout correction of gathers (Manning et al 2006). Combinations of different methods have also yielded impressive enhancement results (Manning et al 2008). However, they still seem inadequate for fully addressing the unique subsalt image conditioning and enhancement challenge.…”

Section: Methodsmentioning

confidence: 99%

Improving Subsalt Imaging by Image Conditioning and Enhancement with RTM Vector Image Partitions - A GoM Case Study

Zhao¹,

Zdraveva²,

González³

et al. 2014

Proceedings

View full text Add to dashboard Cite

SUMMARYSubsalt imaging remains challenging despite a growing need for more accurate subsalt characterization. Long offsets, wide-azimuth (WAZ), and full-azimuth (FAZ) acquisition technologies have provided stepchange improvements in illumination, multiple attenuation and signal-to-noise ratio. Recently developed more advanced anisotropic velocity model building techniques, have also greatly enhanced our ability to build accurate salt models and reduce velocity error. Reverse-time Migration (RTM) has become the preferred imaging algorithm due to its superior tolerance for complex salt geometry compared with traditional ray-based Kirchhoff migration. However, even with these developments, subsalt imaging still remains a significant challenge. Recently, Vector Image Partitions (VIPs) from RTM have proven valuable for enhancing the image of challenging subsalt structures. In this paper, we present a new method for optimizing the final migrated image through enhancement of the consistent signal and suppression of noise among VIPs. We demonstrate the effectiveness of this method with a case study from the Gulf of Mexico. The result shows great improvements in the subsalt image quality in terms of signal to noise ratio, reflector continuity, and wavelet consistency along reflectors.

show abstract

Section: Methodsmentioning

confidence: 99%

Improving Subsalt Imaging by Image Conditioning and Enhancement with RTM Vector Image Partitions - A GoM Case Study

Zhao¹,

Zdraveva²,

González³

et al. 2014

Proceedings

View full text Add to dashboard Cite

show abstract

“…Ongoing research (Manning et al, 2008) is developing methods to build a suite of attributes for each azimuth cube that can be used to reliably discriminate between "good" and "bad" data samples. This is in fact a double-edged sword.…”

Section: Target Illuminationmentioning

confidence: 99%

An overview of seismic azimuth for towed streamers

Long

2010

The Leading Edge

View full text Add to dashboard Cite

Conventional 3D streamer seismic processing generally ignores any azimuth component in the data. We are used to the convenience of acquiring overlapping shot gathers in straight lines, as we can sort the data into common midpoint gathers, and then exploit the power of stack in processing to attenuate random noise. The higher the fold, the more random noise we attenuate. Conventional 3D surveys are acquired using “swath”or “racetrack” vessel shooting, wherein the survey has a single line orientation (or “survey azimuth”), and a long, narrow spread of streamers are towed by a single vessel. Apart from the front of the streamers (short source-receiver offsets), most source-receiver combinations have a relatively common azimuth (the angle between their particular vector and the survey orientation, Figure 1). Thus, the subsurface geology is illuminated only from one particular shooting direction. We assume that most coherent noise types are well behaved and we can remove them in processing. We assume that the target illumination is acceptably uniform, and we can produce clean seismic images. Most of the time these assumptions are in the ballpark of truth and our resultant seismic data allow us to achieve our exploration and appraisal objectives.

show abstract

“…In addition to improved illumination, marine seismic data acquired with more azimuths can benefit from just stacking the data with higher fold to enhance signal-to-noise (S/N) ratio and multiple attenuation (Keggin et al, 2006). Nevertheless, to maximise the benefits of MAZ data, conventional stacking methods may not be effective because, as mentioned by Manning et al (2008), in the presence of strong noise it is better to exclude noisy samples rather than including in the stack. Moreover, since stacking requires events to be flat across offset in the common image gathers (CIGs), it is important to obtain an accurate velocity model.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we describe a processing workflow for optimally stacking MAZ data by taking into account the inaccuracy of velocity model that is manifested as time statics in the image gathers. We also present a way of preserving the AVO behaviour in the gathers that is not explicitly mentioned in the work of Manning et al . (2008).…”

Section: Introductionmentioning

confidence: 99%