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 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

Data-driven tomographic velocity analysis in tilted transversely isotropic media: A 3D case history from the Canadian Foothills

Geophysics ◽  
2008 ◽  
Vol 73 (5) ◽  
pp. VE261-VE268 ◽  
Author(s):  
Sylvestre Charles ◽  
David R. Mitchell ◽  
Rob A. Holt ◽  
Jiwu Lin ◽  
John Mathewson
Keyword(s):  
Case History ◽  
Model Building ◽  
Velocity Model ◽  
Data Driven ◽  
Surface Velocity ◽  
Near Surface ◽  
Model Driven ◽  
Velocity Model Building ◽  
Data Driven Approach ◽  
Anisotropy Model

We evaluated how velocity and anisotropy model-building strategies affect seismic imaging in the Canadian Foothills Thrust Belt by comparing the results of a model-driven approach with those of a data-driven approach. Two independently run Kirchhoff prestack depth-imaging projects were initiated using different static corrections for near-surface weathering layers and using different velocity and anisotropy model-building strategies. We observed that an isotropic data-driven reflection tomography velocity model-building approach resulted in a significantly better stack image than did a highly interpretive anisotropic model-driven velocity model-building approach. By carefully introducing anisotropy into the former, data-driven approach, we achieved significant improvements in positioning, including more accurate depth ties between the seismic image and well tops and better definition of structural geometries. The differences in the imaging observed at the various stages of this case history illustrate the sensitivity of the final depth images to the treatment of the near-surface velocity field, the macrointerval velocity model-building technique, and the choices of [Formula: see text] and [Formula: see text], which are the Thomsen anisotropy parameters for tilted transverse isotropy. The data-driven approach successfully challenged the historical idea that we must perform a geologic interpretation of the seismic data to derive an accurate depth velocity model in a complex geologic setting.

Velocity model building using transfer learning

2021 ◽  
Author(s):  
Jérome Simon ◽  
Gabriel Fabien-Ouellet ◽  
Erwan Gloaguen ◽  
Ishan Khurjekar ◽  
Mauricio Araya-Polo
Keyword(s):  
Transfer Learning ◽  
Model Building ◽  
Velocity Model ◽  
Velocity Model Building
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