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R Gerhard Pratt and Drew Brenders (formerly Queen’s University)

Frequency Domain Waveform Tomography Using Refracted Arrivals (2D Velocity Benchmark – Blind Test – EAGE 2004). R Gerhard Pratt and Drew Brenders (formerly Queen’s University). Traveltime Tomography Image. Processing: Traveltime tomography (FAST). Final Waveform Tomography Image.

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R Gerhard Pratt and Drew Brenders (formerly Queen’s University)

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  1. Frequency Domain Waveform Tomography Using Refracted Arrivals (2D Velocity Benchmark – Blind Test – EAGE 2004) R Gerhard Pratt and Drew Brenders (formerly Queen’s University)

  2. Traveltime Tomography Image

  3. Processing: Traveltime tomography (FAST)

  4. Final Waveform Tomography Image Total number of shots: 167 (every 400 m) Total number of receiver locations: 823 (every 100 m) Maximum offset: 15,000 m Minimum offset: 2,000 m Frequency range: 1 – 7.5 Hz Modelling grid: 1668 x 241 (50 m interval)

  5. Velocity Profiles

  6. Preprocessing: Original data

  7. Preprocessing: Reduced, picked data

  8. Preprocessing: Filtered data (7.5 Hz)

  9. Preprocessing: Windowed data (3 sec)

  10. Processing: Source estimate

  11. Processing: Model data in traveltime tomogram

  12. Processing: Model data in final result

  13. Processing: Final windowed “real” data

  14. Final Waveform Tomography Image Total number of shots: 167 (every 400 m) Total number of receiver locations: 823 (every 100 m) Maximum offset: 15,000 m Minimum offset: 2,000 m Frequency range: 1 – 7.5 Hz Modelling grid: 1668 x 241 (50 m interval)

  15. Final Waveform Tomography Image Top: original imageBottom: removal of low wavenumbers

  16. Exact model

  17. Waveform Tomography

  18. Conclusions • Waveform tomography using refracted arrivals is very effective • Low frequencies and large offsets are critical • Larger offsets (eg OBS data) would allow the entire target to be imaged • Sparse source and receiver coverage is sufficient

  19. Challenges 1/3 Salt 1 - Shot migration no SRME complex overhangs rugose top salt sediment inclusion overpressure zones Complex/broken reflectivity

  20. Challenges 2/3 Salt 2 - Shot migration no SRME multiples shallow HV anomaly channels steep dips poorly imaged flanks

  21. Challenges 3/3 Extra salt - Shot migration with SRME shallow gas mud volcano shallow LV anomalies HV anomalies on structure flanks

  22. Exact density model

  23. Exact model

  24. Queen’s University

  25. Queen’s University: strengths + • Good long & short wavelength updates in the shallow section. • Impressive resolution for some shallow anomalies. • Good image of the top salt without interpretation. • Good delineation of the overhangs without interpretation. • See glimpses of the base salt.

  26. Queen’s University : weaknesses - • Deep part of the model not estimated. • Variable velocity in salt. • Too high frequency. Regularization/smoothing issues? • Imaging issues with several targets, even shallow.

  27. Ranking Quality of salt and sub-salt model building Tier 3 Tier 2 Tier 1 D B H Tier 1 F Accuracy of extra-salt sediment update J I C A Tier 2 K E L Tier 3

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