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Automation of Shear-Wave Splitting Measurements using Cluster Analysis

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Automation of Shear-Wave Splitting Measurements using Cluster Analysis. / Teanby, Nicholas A; Van der Baan, M; Kendall, J-M.

In: Bulletin of the Seismological Society of America, Vol. 94, No. 2, 04.2004, p. 453 - 463.

Research output: Contribution to journalArticle

Harvard

Teanby, NA, Van der Baan, M & Kendall, J-M 2004, 'Automation of Shear-Wave Splitting Measurements using Cluster Analysis', Bulletin of the Seismological Society of America, vol. 94, no. 2, pp. 453 - 463. https://doi.org/10.1785/0120030123

APA

Teanby, N. A., Van der Baan, M., & Kendall, J-M. (2004). Automation of Shear-Wave Splitting Measurements using Cluster Analysis. Bulletin of the Seismological Society of America, 94(2), 453 - 463. https://doi.org/10.1785/0120030123

Vancouver

Teanby NA, Van der Baan M, Kendall J-M. Automation of Shear-Wave Splitting Measurements using Cluster Analysis. Bulletin of the Seismological Society of America. 2004 Apr;94(2):453 - 463. https://doi.org/10.1785/0120030123

Author

Teanby, Nicholas A ; Van der Baan, M ; Kendall, J-M. / Automation of Shear-Wave Splitting Measurements using Cluster Analysis. In: Bulletin of the Seismological Society of America. 2004 ; Vol. 94, No. 2. pp. 453 - 463.

Bibtex

@article{311c4e293fb94bab828ca55e54dd7f4c,
title = "Automation of Shear-Wave Splitting Measurements using Cluster Analysis",
abstract = "The propagation of two orthogonally polarized shear waves, or shear-wave splitting, is arguably the most robust indication of seismic anisotropy in the Earth. This splitting can be parameterized in terms of the polarization of the fast shear-wave ϕ and the lag time between fast and slow components δt. These two parameters provide constraints on the mechanism causing the anisotropy. All methods of calculating splitting require a shear-wave analysis window to be selected. Then the ϕ and δt that best account for the splitting in that window are calculated. Conventionally the shear-wave analysis window is picked manually. However, manual window selection is laborious and also very subjective; in many cases different windows give very different results. We present a method for automating the selection of the window. First, the splitting analysis is performed for a range of window lengths. Then a cluster analysis is applied in order to find those measurements that are stable over many different windows. Once clusters of stable results have been found, the final choice of shear-wave analysis window corresponds to the measurement with the lowest error in the cluster with the lowest variance. Resulting estimates of ϕ and δt are objective, and very large datasets can be analyzed easily. The success of the technique is illustrated with application to a microseismic dataset of 324 events, which confirms previously published results using manually selected analysis windows.",
author = "Teanby, {Nicholas A} and {Van der Baan}, M and J-M Kendall",
note = "Publisher: Seismological Society of America",
year = "2004",
month = "4",
doi = "10.1785/0120030123",
language = "English",
volume = "94",
pages = "453 -- 463",
journal = "Bulletin of the Seismological Society of America",
issn = "0037-1106",
publisher = "Seismological Society of America",
number = "2",

}

RIS - suitable for import to EndNote

TY - JOUR

T1 - Automation of Shear-Wave Splitting Measurements using Cluster Analysis

AU - Teanby, Nicholas A

AU - Van der Baan, M

AU - Kendall, J-M

N1 - Publisher: Seismological Society of America

PY - 2004/4

Y1 - 2004/4

N2 - The propagation of two orthogonally polarized shear waves, or shear-wave splitting, is arguably the most robust indication of seismic anisotropy in the Earth. This splitting can be parameterized in terms of the polarization of the fast shear-wave ϕ and the lag time between fast and slow components δt. These two parameters provide constraints on the mechanism causing the anisotropy. All methods of calculating splitting require a shear-wave analysis window to be selected. Then the ϕ and δt that best account for the splitting in that window are calculated. Conventionally the shear-wave analysis window is picked manually. However, manual window selection is laborious and also very subjective; in many cases different windows give very different results. We present a method for automating the selection of the window. First, the splitting analysis is performed for a range of window lengths. Then a cluster analysis is applied in order to find those measurements that are stable over many different windows. Once clusters of stable results have been found, the final choice of shear-wave analysis window corresponds to the measurement with the lowest error in the cluster with the lowest variance. Resulting estimates of ϕ and δt are objective, and very large datasets can be analyzed easily. The success of the technique is illustrated with application to a microseismic dataset of 324 events, which confirms previously published results using manually selected analysis windows.

AB - The propagation of two orthogonally polarized shear waves, or shear-wave splitting, is arguably the most robust indication of seismic anisotropy in the Earth. This splitting can be parameterized in terms of the polarization of the fast shear-wave ϕ and the lag time between fast and slow components δt. These two parameters provide constraints on the mechanism causing the anisotropy. All methods of calculating splitting require a shear-wave analysis window to be selected. Then the ϕ and δt that best account for the splitting in that window are calculated. Conventionally the shear-wave analysis window is picked manually. However, manual window selection is laborious and also very subjective; in many cases different windows give very different results. We present a method for automating the selection of the window. First, the splitting analysis is performed for a range of window lengths. Then a cluster analysis is applied in order to find those measurements that are stable over many different windows. Once clusters of stable results have been found, the final choice of shear-wave analysis window corresponds to the measurement with the lowest error in the cluster with the lowest variance. Resulting estimates of ϕ and δt are objective, and very large datasets can be analyzed easily. The success of the technique is illustrated with application to a microseismic dataset of 324 events, which confirms previously published results using manually selected analysis windows.

U2 - 10.1785/0120030123

DO - 10.1785/0120030123

M3 - Article

VL - 94

SP - 453

EP - 463

JO - Bulletin of the Seismological Society of America

JF - Bulletin of the Seismological Society of America

SN - 0037-1106

IS - 2

ER -