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Phase-encoded Modeling for Efficient Calculation of Green

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Stochastic Interferometry 7 Stochastic Interferometry 8 Romero et. al. (2000) ... Closed Geometry 12 Line Geometry 13 Geometry Comparison 14 Sigsbee2b ... – PowerPoint PPT presentation

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Title: Phase-encoded Modeling for Efficient Calculation of Green


1
Phase-encoded Modeling for EfficientCalculation
of Greens Functions
Samuel Brown February 5, 2009
2
Outline
  • Phase-encoded Migration
  • Phase-encoded Modeling
  • Examples
  • Signal-to-Noise Ratio
  • Applications
  • HMMs
  • Conclusions

1
3
Phase-encoded Migration
2
4
Phase-encoded Migration
3
5
Phase-encoded Migration

4
6
Phase-encoded Modeling
  • Can we extend this idea for modeling?
  • Can a few simulations produce as many Greens
    functions as any number of simulations?

5
7
Phase-encoded Modeling
  • What could we use these Greens functions for?
  • Exploration/Earthquake imaging
  • Waveform inversion gradients
  • Sensitivity kernels
  • Angle gathers

6
8
Stochastic Interferometry
7
9
Stochastic Interferometry
Romero et. al. (2000)
8
10
Stochastic Interferometry
Greens functions between any two model points
with two finite-difference simulations!
9
11
Model Extension
10
12
Closed Geometry
G(B A)
11
13
Closed Geometry
12
14
Line Geometry
13
15
Geometry Comparison
14
16
Sigsbee2b Above Salt
15
17
PEM Greens Functions
16
18
Sigsbee2b Below Salt
17
19
Sigsbee2b Below Salt
18
20
Extrapolate Stack
  • Place parallel lines of receivers in water
    column.
  • Spacing should be greater than the correlation
    length of noise.
  • Perform cross-correlations between field
    recorded at imaging point and each line receiver.
  • Perform up- and down-going separation of PEM
    Greens functions along each line.
  • Extrapolate each line to streamer/source datum
    and stack.

19
21
Signal-to-Noise Enhancement
20
22
Phase-encoded Modeling
  • What could we use these Greens functions for?
  • Exploration/Earthquake imaging
  • Waveform inversion gradients
  • Sensitivity kernels
  • Angle gathers

21
23
Sensitivity Kernels
Rytov Wavepath
Woodward (1992)
  • Dynamic ray tracing
  • Requires model smoothing
  • One-way wave equation
  • Requires one simulation for each interrogation
    point
  • PEM Greens functions
  • Signal-to-noise ratio

22
24
Angle Gathers
  • Assume first arrival can be extracted from PEM
    Greens Function and characterized in terms or
    traveltime and amplitude.
  • By taking the gradient of traveltimes, we can
    create a ray parameter to determine reflection
    angles.
  • This leads naturally to dip or angle gathers
    when imaging with PEM Greens functions.
  • Same flexibility as Kirchhoff methods!

23
25
1D HMM First Arrival
24
26
2D HMM First Arrival
25
27
2D HMM First Arrival
26
28
Conclusions
  • Phase-encoded modeling can be used to generate
    Greens functions between any two points using
    two finite-difference simulations.
  • Cross-talk related noise is a problem
  • Extrapolate stack algorithm can improve the
    signal-to-noise ratio.
  • Hidden Markov models show promise in extracting
    events from PEM Greens functions.

27
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Looking Forward
28
30
References
Romero, L. A., D. C. Ghiglia, C. C. Ober, and
S. A. Morton, 2000, Phase encoding of shot
records in prestack migration Geophysics, 65,
426-436. Woodward, M. J., 1992, Wave-equation
tomography Geophysics, 57, 15-26.
30
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