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Explore the azimuths

We should process 3D seismic using 3D concepts. This means accounting for and using azimuthal variations in the seismic response (e.g. Gray et al. 2009). Recent results from azimuthal AVO analysis (e.g. Gray and Todorovic-Marinic 2004) and shear-wave birefringence (Bale 2009) have shown that there is significant variation in azimuthal properties over small areas. The implication is that local structural effects, like faults and anticlines, dominate over regional tectonic stresses in azimuthal seismic responses. It is possible that processing algorithms that remove average properties, like surface-consistent methods, may dampen regional effects relative to local effects, but as far as I am aware this concept remains untested at this time. Regardless, there is an imprint of local structural effects on the azimuthal properties, probably caused by the opening and closing of pre-existing fractures in the rock by these local structures.

The largest azimuthal effects come from the near-surface. Examination of residual azimuthal NMO above the oil sands of Alberta have revealed up to 15 ms of residual moveout at depths of less than 200 m (e.g. Gray 2011) and more than 20 ms of birefringence at similar depths (Whale et al. 2009). There is currently some discussion as to why this apparent anisotropy is observed so shallow in the section. Various explanations include stress, fractures, heterogeneity along different azimuthal ray paths, surface topography, and so on. Regardless of their source, these effects propagate all the way down through the data and affect the ability to properly process the data and estimate amplitude attributes.

Azimuthal effects are not restricted to land data. Significant azimuthal effects have been observed in narrow-azimuth towed-streamer seismic data (e.g. Wombell et al. 2006). Application of azimuthal NMO to this seismic volume results in much better offset stacks and significant reduction of striping in timeslices.

The above discussion focuses on the use of azimuthal — that is, 3D — NMO to improve the processing of 3D seismic volumes. This tool is readily available and relatively easy to use. There are other applications where the use of 3D azimuthal concepts and the understanding that properties do vary with azimuth should help to improve the seismic image: 

  • Azimuthal migration (Gray and Wang 2009) with azimuthal velocities (e.g. Calvert et al. 2008);

  • Incorporating local azimuthal variations into surface-consistent algorithms such as deconvolution, scaling, and statics;

  • Amplitude inversion for elastic properties (e.g. Downton and Roure 2010), noise attenuation, etc. 


Bale, R (2009). Shear wave splitting applications for fracture analysis and improved imaging: some onshore examples, First Break 27 (9), 73–83, DOI 10.1190/1.9781560803362.appk.

Calvert, A, E Jenner, R Jefferson, R Bloor, N Adams, R Ramkhelawan, and C St. Clair (2008). Preserving azimuthal velocity information: Experiences with cross-spread noise attenuation and offset vector tile preSTM, SEG Expanded Abstracts 27, 207–211, DOI 10.1190/1.3054789.

Downton, J and B Roure (2010). Azimuthal simultaneous elastic inversion for fracture detection, SEG Expanded Abstracts, 29, 263–267, DOI 10.1190/1.3513389.

Gray, D and D Todorovic-Marinic (2004). Fracture detection using 3D azimuthal AVO. CSEG Recorder 29 (10).

Gray, D, D Schmidt, N Nagarajappa, C Ursenbach, and J Downton (2009). An azimuthal-AVO-compliant 3D land seismic processing flow. CSPG–CSEG–CWLS Expanded Abstracts.

Gray, D and S Wang (2009). Towards an optimal work flow for azimuthal AVO. CSPG–CSEG–CWLS Expanded Abstracts.

Gray, D (2011). Oil sands: not your average seismic data. CSPG–CSEG–CWLS Expanded Abstracts.

Whale, R, R Bale, K Poplavskii, K Douglas, X Li, and C Slind (2009). Estimating and compensating for anisotropy observed in PS data for a heavy oil reservoir. SEG Expanded Abstracts 28, 1212–16. DOI: 10.1190/1.3255070.

Wombell, R (2006). Characteristics of azimuthal anisotropy in narrow azimuth marine streamer data. EAGE Expanded Abstracts 68. DOI: 10.3997/2214-4609.201402127.

As easy as 1D, 2D, 3D

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