Dense volumetric observation for 3D high resolution tomographic model building

Volker Dirks; Francois Audebert; Bin Wang; Nicolas Chazalnoel; Duryodhan Epili; Pierre Plasterie; Dan Wheaton; Patrice Guillaume

doi:10.1071/ASEG2006ab138

ISSN: 2202-0586
E-ISSN:

oa Dense volumetric observation for 3D high resolution tomographic model building
Authors Volker Dirks^a, Francois Audebert^b, Bin Wang^c, Nicolas Chazalnoel^d, Duryodhan Epili^e, Pierre Plasterie^f, Dan Wheaton^g and Patrice Guillaume^h
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^a CGG Americas Inc., [email protected], 16430 Park Ten Place Houston, 77084, US ^b CGG Americas Inc., [email protected], 16430 Park Ten Place Houston, 77084, US ^c CGG Americas Inc., [email protected] ^d CGG Americas Inc., [email protected] ^e CGG Americas Inc., [email protected] ^f CGG Australia Pty Ltd, . [email protected], 2 Ord Street West Perth, WA, 6005 ^g CGG Americas Inc., [email protected] ^h CGG France, [email protected], 1 Rue Leon Migaux 91341 Massy CEDEX, France
Publisher: Australian Society of Exploration Geophysicists
Source: ASEG Extended Abstracts, Volume 2006, Issue ASEG2006 - 18th Geophysical Conference, Dec 2006, p. 1 - 5
DOI: https://doi.org/10.1071/ASEG2006ab138
- Published online: 01 Dec 2006

Abstract

As survey sizes are steadily increasing, 3D tomography as the key component of today’s velocity model building workflows has to be performed on large data volumes within acceptable turnaround times. To provide high-resolution velocity models, dense volumetric picking is required. This leads to even larger data volumes. It is therefore paramount to automate as many processing steps as possible to free the time of the geophysicist for the necessary QC. In this paper we present a modified workflow for high-resolution 3D tomography addressing the need for process automation. We are putting the emphasis of this paper on data preparation and the quality control of the inversion phase. The presented workflow allows performance of high-resolution tomography work on large data volumes over a significantly reduced cycle time.

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References

Wang, B., Pann, K. and Meek, R. A., 1995, Macro velocity model estimation through model-based globally-optimized residual-curvature analysis, 65th Ann. Internat. Mtg: Soc. of Expl. Geophys., 1084-1087.
Guillaume, P., Chazalnoel, N., Talaalout, A., Zhang, X., Epili, D. and Dirks, V., 2003, 3D finite-offset depth tomography model building: Green Canyon, Gulf of Mexico, 73rd Ann. Internat Mtg.: Soc. of Expl. Geophys., 438-441.
Guillaume, P., Audebert, F., Berthet, P., David, B., Herrenschmidt, A. and Zhang, X., 2001, 3D finite-offset tomographic inversion or CRP-scan data, with or without anisotropy, 71st Ann. Internat. Mtg: Soc. of Expl. Geophys., 718-721.
Hoeber, H., Coleou, T., Le Meur, D., Angerer, E., Lanfranchi, P. and Lecerf, D., 2003, On the use of geostatistical filtering techniques in seismic processing, 73rd Ann. Internat. Mtg.: Soc. of Expl. Geophys., 2024-2027.

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Article Type: Research Article

Keyword(s): Depth imaging; Pre-stack depth migration; Tomography

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oa Dense volumetric observation for 3D high resolution tomographic model building

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