Velocity model building methodology and PSDM in deep water Gulf of Mexico: A case history

2003 ◽  
Author(s):  
Kamal Siddiqui ◽  
Steve Clark ◽  
Duryodhan Epili ◽  
Nicolas Chazalnoel ◽  
Lynn Anderson
Keyword(s):  
Gulf Of Mexico ◽  
Deep Water ◽  
Case History ◽  
Model Building ◽  
Velocity Model ◽  
Velocity Model Building

No-compromise marine seismic: A full-azimuth survey design for total-wavefield velocity model building and imaging in the deep-water Gulf of Mexico

2014 ◽  
Author(s):  
Andrew Long* ◽  
Steve Campbell ◽  
Steven Fishburn ◽  
Sverre Brandsberg-Dahl ◽  
Nizar Chemingui ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Deep Water ◽  
Model Building ◽  
Survey Design ◽  
Velocity Model ◽  
Velocity Model Building ◽  
Marine Seismic

Velocity model building using basin modeling and rock physics, with examples from Campeche deep-water Gulf of Mexico

2019 ◽  
Author(s):  
Jianchun Dai ◽  
Dawn Jantz ◽  
Zengbao Chen ◽  
Claire Jacob ◽  
Daniel Smith ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Deep Water ◽  
Model Building ◽  
Rock Physics ◽  
Velocity Model ◽  
Basin Modeling ◽  
Velocity Model Building

Detailed velocity model building in a carbonate karst zone and improving sub‐karst images in the Gulf of Mexico

2011 ◽  
Author(s):  
Jun Cai ◽  
Hao Xun ◽  
Li Li ◽  
Yang He ◽  
Zhiming Li ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Model Building ◽  
Velocity Model ◽  
Velocity Model Building

WAZ OBC data velocity model building using FWI: New technologies to resolve imaging challenges, Gulf of Mexico shelf, Bay Marchand Field

2016 ◽  
Author(s):  
Nathaniel Cockrell ◽  
Khaled Abdelaziz ◽  
Kun Jiao ◽  
Adrian Montgomery ◽  
David Dangle ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Model Building ◽  
New Technologies ◽  
Velocity Model ◽  
Velocity Model Building

Velocity model‐building in complex tectonics: A strategy, a case history and related issues

2001 ◽  
Author(s):  
P. Sexton ◽  
P. Williamson ◽  
C. Hanitzsch
Keyword(s):  
Case History ◽  
Model Building ◽  
Velocity Model ◽  
Velocity Model Building

Velocity model building with long-offset and full-azimuth data: A case history for full-waveform inversion

2013 ◽  
Author(s):  
Wei Huang ◽  
Hongda Ma ◽  
Denes Vigh ◽  
Jerry Kapoor ◽  
Kun Jiao ◽  
...  
Keyword(s):  
Case History ◽  
Model Building ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Velocity Model Building ◽  
Long Offset

The Wolfspar experience with low-frequency seismic source field data: Motivation, processing, and implications

2022 ◽  
Vol 41 (1) ◽  
pp. 9-18
Author(s):  
Andrew Brenders ◽  
Joe Dellinger ◽  
Imtiaz Ahmed ◽  
Esteban Díaz ◽  
Mariana Gherasim ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Seismic Data ◽  
Field Data ◽  
Model Building ◽  
Low Frequency ◽  
Seismic Source ◽  
Velocity Model ◽  
Seismic Sources ◽  
Velocity Model Building ◽  
Air Gun

The promise of fully automatic full-waveform inversion (FWI) — a (seismic) data-driven velocity model building process — has proven elusive in complex geologic settings, with impactful examples using field data unavailable until recently. In 2015, success with FWI at the Atlantis Field in the U.S. Gulf of Mexico demonstrated that semiautomatic velocity model building is possible, but it also raised the question of what more might be possible if seismic data tailor-made for FWI were available (e.g., with increased source-receiver offsets and bespoke low-frequency seismic sources). Motivated by the initial value case for FWI in settings such as the Gulf of Mexico, beginning in 2007 and continuing into 2021 BP designed, built, and field tested Wolfspar, an ultralow-frequency seismic source designed to produce seismic data tailor-made for FWI. A 3D field trial of Wolfspar was conducted over the Mad Dog Field in the Gulf of Mexico in 2017–2018. Low-frequency source (LFS) data were shot on a sparse grid (280 m inline, 2 to 4 km crossline) and recorded into ocean-bottom nodes simultaneously with air gun sources shooting on a conventional dense grid (50 m inline, 50 m crossline). Using the LFS data with FWI to improve the velocity model for imaging produced only incremental uplift in the subsalt image of the reservoir, albeit with image improvements at depths greater than 25,000 ft (approximately 7620 m). To better understand this, reprocessing and further analyses were conducted. We found that (1) the LFS achieved its design signal-to-noise ratio (S/N) goals over its frequency range; (2) the wave-extrapolation and imaging operators built into FWI and migration are very effective at suppressing low-frequency noise, so that densely sampled air gun data with a low S/N can still produce useable model updates with low frequencies; and (3) data density becomes less important at wider offsets. These results may have significant implications for future acquisition designs with low-frequency seismic sources going forward.

Resolving near-seabed velocity anomalies: Deep water offshore eastern India

Geophysics ◽  
2008 ◽  
Vol 73 (5) ◽  
pp. VE235-VE241 ◽  
Author(s):  
Juergen Fruehn ◽  
Ian F. Jones ◽  
Victoria Valler ◽  
Pranaya Sangvai ◽  
Ajoy Biswal ◽  
...  
Keyword(s):  
Velocity Field ◽  
Deep Water ◽  
Model Building ◽  
Velocity Model ◽  
Narrow Channel ◽  
Small Scale ◽  
Low Velocity ◽  
Near Surface ◽  
Velocity Model Building ◽  
Velocity Anomalies

Imaging in deep-water environments poses a specific set of challenges, both in data preconditioning and velocity model building. These challenges include scattered, complex 3D multiples, aliased noise, and low-velocity shallow anomalies associated with channel fills and gas hydrates. We describe an approach to tackling such problems for data from deep water off the east coast of India, concentrating our attention on iterative velocity model building, and more specifically the resolution of near-surface and other velocity anomalies. In the region under investigation, the velocity field is complicated by narrow buried canyons ([Formula: see text] wide) filled with low-velocity sediments, which give rise to severe pull-down effects; possible free-gas accumulation below an extensive gas-hydrate cap, causing dimming of the image below (perhaps as a result of absorption); and thin-channel bodies with low-velocity fill. Hybrid gridded tomography using a conjugate gradient solver (with [Formula: see text] vertical cell size) was applied to resolve small-scale velocity anomalies (with thicknesses of about [Formula: see text]). Manual picking of narrow-channel features was used to define bodies too small for the tomography to resolve. Prestack depth migration, using a velocity model built with a combination of these techniques, could resolve pull-down and other image distortion effects in the final image. The resulting velocity field shows high-resolution detail useful in identifying anomalous geobodies of potential exploration interest.

Anisotropic velocity model building using rock physics: Comparison of compaction trends and check‐shot‐derived anisotropy in the Gulf of Mexico

2011 ◽  
Author(s):  
Ran Bachrach ◽  
Yangjun (Kevin) Liu ◽  
Marta Woodward ◽  
Olga Zradrova ◽  
Yi Yang ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Model Building ◽  
Rock Physics ◽  
Velocity Model ◽  
Velocity Model Building
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