Seismic Reflection: Processing and Interpretation
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Seismic Reflection: Processing and Interpretation

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Objectives. Develop a velocity model of the Santa Fe River Canyon to aid in structure interpretationUse predictive deconvolution to remove multiple reflections from the data . Processing Steps. Processing Steps. Defining Geometry. . Processing Steps. Killing Traces. Vibroseis signal had to be eliminatedChannels showing large amounts of noise were deleted.
Seismic Reflection: Processing and Interpretation

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1. Seismic Reflection: Processing and Interpretation Katie Wooddell UW Madison

2. Objectives Develop a velocity model of the Santa Fe River Canyon to aid in structure interpretation Use predictive deconvolution to remove multiple reflections from the data

3. Processing Steps

4. Processing Steps

5. Defining Geometry

6. Processing Steps

7. Killing Traces Vibroseis signal had to be eliminated Channels showing large amounts of noise were deleted

8. Processing Steps

9. Predictive Deconvolution What does it do? Clears seismic data by predicting and eliminating multiple reflections How does it work? A filter is designed that recognizes and eliminates repetitions in the signal

10. Deconvolution Equation

11. To Conceptualize. . .

12. Deconvolution Results

13. Processing Steps

14. Butterworth Filter Bandpass Filter Passes frequencies in the range of the vibroseis sweep (30-300 Hz) Effective in eliminating the noise amplified during predictive deconvolution

15. Butterworth Filtering

16. Processing Steps

17. Processing Steps

18. NMO Correction NMO corrects for the delay in first arrival times NMO shifts the arrival times according to a specific stacking velocity This is an important step in the velocity analysis

19. Processing Steps

20. Velocity Analysis A Constant Velocity Analysis was conducted on both deconvolved and non-deconvolved data The following NMO stacking velocities were run for each situation: - 1000 m/s -1200 m/s - 1400 m/s -1600 m/s - 1800 m/s -2000 m/s - 2200 m/s -2400 m/s

21. Conclusions Predictive deconvolution is an effective tool for eliminating multiples from seismic data A combination of the 2000 m/s and the 1600 m/s constant velocity models seems to produce a high resolution model This implies a higher average velocity medium on the east side of the fault, giving evidence that the normal La Bajada fault is being imaged

22. And a Special Thanks To. . . The SAGE professors for their knowledge and patience Team 5 for their hard work and some good times Michelle Herrera, my Processing partner Lauren Larkin, who was more enthusiastic about splicing together my seismic sections than I was


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