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3D Super-virtual Refraction Interferometry Kai Lu King Abdullah University of Science and Technology.

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Presentation on theme: "3D Super-virtual Refraction Interferometry Kai Lu King Abdullah University of Science and Technology."— Presentation transcript:

1 3D Super-virtual Refraction Interferometry Kai Lu King Abdullah University of Science and Technology

2 Outline Introduction and Motivation Theory: conventional SVI with stationary phase integration Synthetic data example Field data example Conclusion Acknowledgement

3 Outline Introduction and Motivation Theory: conventional SVI with stationary phase integration Synthetic data example Field data example Conclusion Acknowledgement

4 B C A3 dt A2A1 dt 1.Stacked Refractions: + Stacking dt B C A Common Pair Gather (Dong et al., 2006) Benefit: SNR = N d AB AC ~ d BC A virtual ~ 2D Super-virtual Interferometry

5 2. Dedatum Virtual Refraction to Known Surface Point B C A A = * = * + d AB AC ~ d BC A src virtual real super-virtual d AB BC ~ d AC B rec supervirtual * virtual Raw traceVirtual trace (Calvert+Bakulin, 2004) Super-virtual trace B rec A src Datuming Dedatuming 2D Super-virtual Interferometry

6 Theory and workflow: Are first arrivals at far-offsets pickable ? Window around first arrivals and mute near offset Correlate and stack to generate virtual refractions Input Data Output Data Convolve and stack to generate Super-virtual refractions N Ʃ Ʃ Raw Data Super-virtual refraction Data Windowed Data Iterative SVI

7 Difficulties from 2D to 3D Difficulty to find locations of stationary sources and receivers S A1A1 Unknown Path Few sources and receiver available A2A2 Limited number of sources and receivers

8 Solution 2D: all traces are stationary 3D: stationary phase integration A B Virtual Trace S1S1 S2S2 S3S3 SnSn S*S*

9 Outline Introduction and Motivation Theory: conventional SVI with stationary phase integration Synthetic data example Field data example Conclusion Acknowledgement

10 Stationary Phase Integration Stationary phase analysis (Bleistein, 1984) applied to the line integral: Applied to SVI: Virtual trace AB A B S1S1 S2S2 S3S3 SnSn S*S*

11 Cross-correlation Type A B CRG A CRG B Cross-correlation Results Ʃ Correlation of S*A and S*B Virtual trace AB Source 1 180 Time (s) 0 4 Source 1 180 Source 1 180 Amplitude 1 S1S1 S1S1 SnSn SnSn S*

12 Virtual Trace Stacking over Source Lines A B S1S1 S2S2 S3S3 SnSn     lineN line1 line2 2D: Stacking over sources: 3D: Stacking over source lines: C A1 B C B C B = A2 A3

13 Super Virtual Trace – Convolution Type A S B1B1 B2B2 B3B3 BnBn     lineN line1 line2 2D: Stacking over receivers: 3D: Stacking over receiver lines: C A B1 C A B C * = B2 B3

14 Workflow of 3D SVI Window around the targeted refraction Input Band-pass filtered Data Output Data Iterative SVI

15 Outline Introduction and Motivation Theory: conventional SVI with stationary phase integration Synthetic data example Field data example Conclusion Acknowledgement

16 Synthetic Test – Undulating Layer Model V 1 =1500m/s V 2 =3000m/s 151 receivers, 76 sources on every line 11 survey lines

17 Line1 Line11 Synthetic Result Original data Data with random noise Super-virtual refractionIterative Super-virtual Refraction Trace Time (s) 0 3 1 151 Trace Time (s) 0 3 1 151 Trace Time (s) 0 3 1 151 Trace Time (s) 0 3 1 151

18 Outline Motivation: from 2D to 3D Theory: conventional SVI with stationary phase integration Synthetic data example Field data example Conclusion Acknowledgement

19 x [km] y [km] 214 -2 18 3D OBS Survey Geometry 19 400 m 50 m 5 m Sihil 3D OBS data – 234 OBS stations – 129 source-lines Irregular geometry. Map view

20 Field Results 1 Raw data Band-pass filtered data Super-virtual result Trace Time (s) 0 4 1 361 Trace Time (s) 0 4 1 361 Trace Time (s) 0 4 1 361

21 Zoom View Comparison Zoom view of band-pass filtered data Zoom view of super-virtual data Trace Time (s) 1 3 1 361 Trace Time (s) 1 3 1 361 Zoom view of super-virtual data Unpickable

22 Field Results 2 Raw data Super-virtual result Iterative Super-virtual result Trace Time (s) 0 4 1 361 Trace Time (s) 0 4 1 361 Trace Time (s) 0 4 1 361

23 Zoom View Comparison Raw data Super-virtual result Iterative Super-virtual result Trace Time (s) 0 4 1 361 Trace Time (s) 0 4 1 361 Trace Time (s) 0 4 1 361 Unpickable

24 Outline Introduction and Motivation Theory: conventional SVI with stationary phase integration Synthetic data example Field data example Conclusion Acknowledgement

25 Conclusion We apply stationary phase integration method to achieve super-virtual refraction with enhanced SNR in 3D cases. Iterative method is an option to further improve SNR when super-virtual refraction is still noisy. Artifacts can be produced because of the limited aperture for integration as well as a coarse spacing of sources or receivers.

26 Thank you !


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