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Seismic Reflection: Processing and Interpretation






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

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Slide 1

Seismic Reflection:Processing and Interpretation

Katie Wooddell

UW Madison

Slide 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

Slide 3

Processing Steps

Slide 4

Processing Steps

Slide 5

Defining Geometry

Slide 6

Processing Steps

Slide 7

Killing Traces

  • Vibroseis signal had to be eliminated

  • Channels showing large amounts of noise were deleted

Slide 8

Processing Steps

Slide 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

Slide 10

Deconvolution Equation

Robertson 1998

Slide 11

To Conceptualize. . .

INPUT

OUTPUT

FILTER

=

*

Slide 12

Deconvolution Results

Location 109

Location 109

Time (ms)

Time (ms)

NO DECONVOLUTION

DECONVOLVED

Slide 13

Processing Steps

Slide 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

Slide 15

Butterworth Filtering

Location 109

Location 109

Time (ms)

Time (ms)

No Filter

Butterworth Filter

Slide 16

Processing Steps

Slide 17

Processing Steps

Slide 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

Slide 19

Processing Steps

Slide 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

Slide 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

Slide 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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