1 / 17

3D OBS->OBS Interferometry

3D OBS->OBS Interferometry. Sherif Hanafy February 2009. Outline. Problem: Missing and sparse traces Theory: Interferometric interpolation and extrapolation Numerical results: SEG/EAGE model Conclusions and future work. Outline. Problem: Missing and sparse traces

latham
Télécharger la présentation

3D OBS->OBS Interferometry

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. 3D OBS->OBS Interferometry Sherif Hanafy February 2009

  2. Outline • Problem: Missing and sparse traces • Theory: Interferometric interpolation and extrapolation • Numerical results: • SEG/EAGE model • Conclusions and future work

  3. Outline • Problem: Missing and sparse traces • Theory: Interferometric interpolation and extrapolation • Numerical results: • SEG/EAGE model • Conclusions and future work

  4. Water Water Problem In marine surveys, receiver interval could be large (especially in cross line direction) Solution: Use interferometric interpolation

  5. Outline • Problem: Missing and sparse traces • Theory: Interferometric interpolation and extrapolation • Numerical results: • SEG/EAGE model • Conclusions and future work

  6. SSP SSP SSP Ocean Surface Ocean Surface Ocean Surface x x B B A A Sea bed Sea bed x B A Sea bed Reflectors Reflectors G(x|B) Model based data G(x|A) Natural Green’s function G(B|A) Interpolated data Theory Virtual receiver Virtual source

  7. 0 Ocean Surface 0 Sea bed Time (s) x 0 Time (s) 3.0 0 X (km) 4.5 Time (s) 3.0 0 X (km) 4.5 3.0 0 X (km) 4.5 Workflow Input Data G(x|B) Input Field Data G(x|A) Water Layer Thickness Generate GF for Water Multiples Unfiltered Virtual Interpolate/Extrapolate Missing Data Filtered Virtual Get Virtual CSG G(B|A) Matching Filter N Max. Itr (MF) Y N Max Iter Intr/Extr Y Final CSG

  8. Outline • Problem: Missing and sparse traces • Theory: Interferometric interpolation and extrapolation • Numerical results: • SEG/EAGE model • Conclusions and future work

  9. 1500 Velocity (m/s) 4500 SEG/EAGE Velocity Model

  10. Sparse geometry Dense geometry Acquisition Parameters • Goal • 22 Streamers • Crossline offset is 10 m • Inline offset is 4 m • 508 receivers/streamer • Total number of receivers 11176 • Input • 8 Streamers • Crossline offset is 30 m • Inline offset is 12 m • 170 receivers/streamer • Total number of receivers 1360

  11. 0 Time (s) 1 2 8 1 2 Streamer Scale 0 2 km SEG/EAGE Model – Input Data

  12. 0 Time (s) 1 2 1’ 2’ 8 1 1’ 2’ 2 Streamer Scale 0 2 km SEG/EAGE Model – Virtual Data

  13. 0 Time (s) 8 1 2 3 4 Streamer Scale 0 2 km SEG/EAGE Model – Real Data

  14. Outline • Problem: Missing and sparse traces • Theory: Interferometric interpolation and extrapolation • Numerical results: • SEG/EAGE model • Conclusions and future work

  15. Conclusions • 3D marine SSP data can be interpolated with interferometry. • Proposed approach is successfully tested on a synthetic model. • Number of receivers can be increased 8 to 10 times by interferometry.

  16. Future Work • Extrapolation of the data • Test on field data, we need field data to complete this part

  17. Acknowledgement We would like to thank the UTAM 2008 sponsors for their support. Thank You

More Related