Data Driven Velocity Model Building - An Application to Egypt Nile Delta

Tanis, Mehmet C.; Summers, Tim; Cook, Peter; Keggin, J.

doi:10.3997/2214-4609.20147613

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“…To date, standard reflection tomography on conventional streamer data has failed to build a detailed velocity model in this area. A recent attempt to model the complex Messinian layers has been to estimate the anhydrite distribution from an initial depth migration stack converted to impedance, and then to update the model with representative interval velocities at these locations (Tanis et al, 2008). Results show that a detailed model can be built which helps heal the image continuity below anhydrite in some areas (where PreSTM usually fails).…”

Section: Introductionmentioning

confidence: 99%

Detailed Velocity Model of the Nile Delta Using Multi-azimuth (MAZ), Multi-Parameter Reflection Tomography

Baptiste¹,

Manning²

2009

Proceedings

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SUMMARYIn the Nile Delta, a complex and dipping water bottom, shallow gas filled channel systems and the evaporitic Messinian interval have prevented the creation of an accurate velocity model in depth using conventional 3D data. By designing a workflow that combines the Multi-Azimuth data in a multiparameter reflection tomography approach, we have built a detailed velocity model that shows variations that correspond very well to the geology interpreted from the seismic, and which yields improved images at depth. SummaryBuilding a detailed velocity model is always a major challenge in seismic data processing. In the Nile Delta, a complex and dipping water bottom, shallow gas filled channel systems and the evaporitic Messinian interval have prevented the creation of an accurate velocity model in depth using conventional 3D data. Can we take advantage of the recently acquired Multi-Azimuth (MAZ) seismic to build a detailed velocity model? We know from theory and case histories that Multi-Azimuth data will give us improved signal to noise, improved multiple attenuation, and improved illumination. By designing a workflow that combines the Multi-Azimuth data in a multi-parameter reflection tomography approach, we have built a detailed velocity model that shows variations that correspond very well to the geology interpreted from the seismic, and which yields improved images at depth.Background

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Section: Introductionmentioning

confidence: 99%