aHomestake Array and Wiener Filtering Array Coherence Wiener - - PowerPoint PPT Presentation

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aHomestake Array and Wiener Filtering Array Coherence Wiener - - PowerPoint PPT Presentation

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aHomestake Array and Wiener Filtering M. Coughlin Introduction aHomestake Array and Wiener Filtering Array Coherence Wiener Filtering Velocity Measurements Michael Coughlin, Jan Harms Conclusion August 11, 2016 1 / 16 Introduction

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SLIDE 1

aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

aHomestake Array and Wiener Filtering

Michael Coughlin, Jan Harms August 11, 2016

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SLIDE 2

aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

Introduction

With the original Homestake array (http://arxiv.org/abs/1403.7756):

1

We demonstrated that we can achieve more than an order of magnitude seismic-noise cancellation between about 0.05-0.5 Hz using Wiener filters with only a few seismometers separated by a distance of order 500 m.

2

At least a factor 50 NN reduction should in principle be feasible at the Homestake site around 0.1 Hz (subject to assumptions about scattering).

3

We have showed that this subtraction performance can be achieved without regularly updating the filter, indicating that the average properties of seismic fields at Homestake do not change significantly over timescales of weeks in this frequency band.

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aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

Introduction (continued)

Caveats to the analysis:

1

Assumed that seismic scattering at the Homestake site is representative for seismic scattering of the entire region that needs to be included for NN estimates.

2

Array not large enough to explore optimal array design and the many technical issues associated with the calculation of Wiener filters based on a large number of reference channels

3

Residual spectra contained a microseismic peak ... why? (body waves and surface waves? scattering?)

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aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

Wiener Filter (iHomestake)

(a) Wiener Filter

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SLIDE 5

aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

Introduction (continued)

Benefits of aHomestake array:

1

The array has significantly larger horizontal spacing than used in the iHomestake analysis.

2

Significantly more channels! We can try to use the larger aHomestake array to test these:

1

Distinguishing between body and surface waves

2

Whether a larger array with greater variation in station distances would yield even better subtraction over a broader range of frequencies

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aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

Seismic Spectra

Frequency [Hz] 10 -2 10 -1 10 0 10 1 Seismic Spectrum [m/s / Hz] 10 -10 10 -9 10 -8 10 -7 10 -6

300 800 D4850 WTP

(b) Seismic Spectra

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aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

Coherence vs. Relative Location (0.2 Hz)

X [m]

  • 10000
  • 5000

5000

Y [m]

  • 6000
  • 4000
  • 2000

2000 4000 6000 8000 log10(1 - Coherence)

  • 3
  • 2.5
  • 2
  • 1.5
  • 1
  • 0.5

(c) Coherence vs. Relative Location

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SLIDE 8

aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

Coherence as a function of distance (0.2 Hz)

Horizontal Distance [m]

2000 4000 6000 8000 10000

Coherence at 0.2 Hz

0.2 0.4 0.6 0.8 1 Relative Elevation [m]

  • 1500
  • 1000
  • 500

500 1000 1500

(d) Coherence as a function of distance (0.2 Hz)

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SLIDE 9

aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

Coherence as a function of distance (1.5 Hz)

Horizontal Distance [m]

2000 4000 6000 8000 10000

Coherence at 1.5 Hz

  • 1
  • 0.5

0.5 1 Relative Elevation [m]

  • 1500
  • 1000
  • 500

500 1000 1500

(e) Coherence as a function of distance (1.5 Hz)

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aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

Parameters

1

Target: 800:HHZ

2

Used all sub-surface seismometers (8)

3

Vertical channels only

4

1 Hour filter, 23 Hour subtraction

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SLIDE 11

aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

Low Frequency

Frequency [Hz]

10 -2 10 -1 10 0

Seismic Spectrum [(m/s)/ Hz]

10 -10 10 -9 10 -8 10 -7 10 -6 10 -5

Original Residual FF LNM HNM

(f) PSD

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SLIDE 12

aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

High frequency

Frequency [Hz]

10 -2 10 -1 10 0 10 1

Seismic Spectrum [(m/s)/ Hz]

10 -10 10 -9 10 -8 10 -7 10 -6 10 -5

Original Residual FF LNM HNM

(g) PSD

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SLIDE 13

aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

Parameters

1

3D KF-map decomposition ( k = (kx, ky, kz) → k = (kr, kθ, kφ) → v = 2πf

kr .)

2

Used all seismometers

3

Vertical channels only

4

1 week of data

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SLIDE 14

aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

Velocity vs. frequency

Frequency [Hz]

10 -2 10 -1 10 0 10 1

Velocity [m/s]

1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

(h) Velocity vs. frequency

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SLIDE 15

aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

Angle (tan−1(y/x)) vs. frequency vs. time

Frequency [Hz]

10 -2 10 -1 10 0 10 1

Time [Days]

1 2 3 4 5 6

Angle [rad]

  • 1.5
  • 1
  • 0.5

0.5 1 1.5

(i) Angle (tan−1(y/x)) vs. frequency vs. time

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SLIDE 16

aHomestake Array and Wiener Filtering

  • M. Coughlin

Introduction Array Coherence Wiener Filtering Velocity Measurements Conclusion

Conclusions

1

The aHomestake array covers a wider aperture than that of the

  • riginal Homestake array

2

We can use the aHomestake array to explore the effects of the assumptions of the original analysis

3

Numerical issues seem to be limiting the efficacy of the Wiener filters

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