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4C Mahogony Data Processing and Imaging by LSMF Method

4C Mahogony Data Processing and Imaging by LSMF Method. Jianhua Yu and Yue Wang. Outline. Motivation and Objective LSMF Method Examples Graben Model Mahogany Field Data Summary. Outline. Motivation and Objective LSMF Method Examples Graben Model Mahogany Field Data

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4C Mahogony Data Processing and Imaging by LSMF Method

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  1. 4C Mahogony Data Processing and Imaging by LSMF Method Jianhua Yu and Yue Wang

  2. Outline • Motivation and Objective • LSMF Method • ExamplesGraben Model Mahogany Field Data • Summary

  3. Outline • Motivation and Objective • LSMF Method • ExamplesGraben Model Mahogany Field Data • Summary

  4. Geological Objectives • Image Complex Structure • Detect Gas Reservoir OverSalt

  5. Problems • P-SV Conversion at Reflector? • How to Get“Pure”P-P and P-SV • Strong Guided Waves

  6. Use only wave moveout Near offset distortion Strong guided waves Problems for F-K

  7. P-P P-SV P-P and P-SV Waves Source Point Scatterer

  8. Least Squares Migration Filtering Moveout Particle Motion Direction Time + offset Separation

  9. Objective Separate P-P & P-S Suppress Guide Waves Improve Migration Image

  10. Outline • Motivation and Objective • LSMF Method • ExamplesGraben Model Mahogany Field Data • Summary

  11. Lpp mpp Modeling Operator Reflectivty Lp-s mp-s LSMF Method = > Dpp + Dp-s Observed data P-P wave Time P-S wave Offset

  12. P-P wave Time Time P-S wave Offset Offset LSMF Method dp-s = Lp-smp-s dpp = Lppmpp

  13. LSMF Method Conjugate Gradient Method: where

  14. LSMF Method Operators are constructed based on moveout and particle-motion direction The migration operators are the transposes of the modeling operators

  15. Outline • Motivation and Objective • LSMF Method • ExamplesGraben Model Mahogany Field Data • Summary

  16. Examples • Graben Model • Mahogony Field Data

  17. Graben Velocity Model 5000 0 X (m) 0 V1=2000 m/s V2=2700 m/s V3=3800 m/s Depth (m) V4=4000 m/s V5=4500 m/s 3000

  18. FDSynthetic Data Offset (m) Offset (m) 5000 0 5000 0 0 P-S P-P Time (s) P-S P-P 1.4 Horizontal Component Vertical Component

  19. LSMF Separation 5000 0 Offset (m) 5000 0 Offset (m) 0 P-P P-S Time (s) 1.4 Horizontal Component Vertical Component

  20. F-K Filtering Separation 5000 0 Offset (m) 5000 0 Offset (m) 0 P-S P-P Time (s) P-S P-P 1.4 Horizontal Component Vertical Component

  21. Test Results Indicate: LSMF works well for separating P-P and P-SV LSMF is superior to F-K filtering

  22. Examples • Graben Model • Mahogony Field Data

  23. Acquisition Survey Shot Line OBC 9 km 29 km

  24. Main Processing Flow Geometry assignment, datuming and so on Trace edit, noise elimination, dual-sensor summation Amplitude Recovery Static correction, (F-K filtering), multiple suppression LSMF, velocity analysis Migration Output

  25. Raw CSG Offset(m) Offset(m) -750 725 -750 725 0 Continuous events Continuous events Time (s) 4 Hydrophone component Vertical component

  26. Raw CSG Offset(m) Offset(m) -750 725 -750 725 0 Wormy events Wormy events Time (s) 4 Radial component Transverse component

  27. RawCRG X (m) X (m) 0 3750 0 3750 0 Continuous events Continuous events Time (s) 4 Hydrophone component Vertical component

  28. Raw CRG X (m) X (m) 0 3750 0 3750 0 Continuous events Continuous events Time (s) 4 Radial component Transverse component

  29. p s p s Rough Estimate of Static Shift Source Receiver 12 Receiver static Static shift (ms) Source Receiver Shot static -4 100 0 Station Number

  30. Data Analysis Indicates: TheShear static shifts exist These shifts mainly come from receivers and one-way Shear path from deeper reflector P-S waves originate from reflectors

  31. CRG1 Data before Using LSMF 0 Guided wave and P-S Time (s) 4 CRG1 (Vertical component)

  32. CRG1 Data after Using F-K Filtering 0 Unwanted waves remain Time (s) 4 CRG1 (Vertical component)

  33. CRG1 Data after Using LSMF 0 Less Noise remains Time (s) 4 CRG1 (Vertical component)

  34. Prestack Migration Image With F-K Separation Midpoint (Km) 0 4.6 0 c Time (s) 3.5

  35. Prestack Migration Image With LSMF Separation Midpoint (Km) 0 4.6 0 c Time (s) 3.5

  36. A Zoom View of Box A Midpoint (Km) Midpoint (Km) 0.6 1.4 0.6 1.4 2.0 Time (s) 3.2 FK+Mig. LSMF+Mig.

  37. A Zoom View of Box C Midpoint (Km) Midpoint (Km) 3.4 4.6 3.4 4.6 0.2 Time (s) 0.8 FK+Mig. LSMF+Mig.

  38. Outline • Motivation and Objective • LSMF Method • ExamplesGraben Model Mahogany Field Data • Summary

  39. Summary • P-SV waves in Mahogony data • originate from the deep reflectors • LSMF gives better separation results • and improves the migration image

  40. Summary • LSMF can eliminate unwanted noise, • such as guided waves • LSMF has negative impact on the • fidelity of data to some extent

  41. Summary Future Research: • Multiple Elimination • Prestack Depth Migration • Converted Wave Imaging

  42. Acknowledgement We are grateful to the 1999 sponsors of the UTAM consortium for financial support

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