Options
Splitting parameter yield (SPY): A program for semiautomatic analysis of shear wave splitting
Author(s)
Language
English
Obiettivo Specifico
1.4. TTC - Sorveglianza sismologica delle aree vulcaniche attive
Status
Published
JCR Journal
JCR Journal
Peer review journal
Yes
Title of the book
Issue/vol(year)
/40 (2012)
Publisher
Elsevier
Pages (printed)
138-145
Issued date
2012
Abstract
SPY is a Matlab algorithm that analyzes seismic waveforms in a semiautomatic way, providing
estimates of the two observables of the anisotropy: the shear-wave splitting parameters. We chose
to exploit those computational processes that require less intervention by the user, gaining objectivity
and reliability as a result. The algorithm joins the covariance matrix and the cross-correlation
techniques, and all the computation steps are interspersed by several automatic checks intended to
verify the reliability of the yields. The resulting semiautomation generates two new advantages in the
field of anisotropy studies: handling a huge amount of data at the same time, and comparing different
yields. From this perspective, SPY has been developed in the Matlab environment, which is widespread,
versatile, and user-friendly. Our intention is to provide the scientific community with a new monitoring
tool for tracking the temporal variations of the crustal stress field.
estimates of the two observables of the anisotropy: the shear-wave splitting parameters. We chose
to exploit those computational processes that require less intervention by the user, gaining objectivity
and reliability as a result. The algorithm joins the covariance matrix and the cross-correlation
techniques, and all the computation steps are interspersed by several automatic checks intended to
verify the reliability of the yields. The resulting semiautomation generates two new advantages in the
field of anisotropy studies: handling a huge amount of data at the same time, and comparing different
yields. From this perspective, SPY has been developed in the Matlab environment, which is widespread,
versatile, and user-friendly. Our intention is to provide the scientific community with a new monitoring
tool for tracking the temporal variations of the crustal stress field.
References
Bianco, F., Scarf!ı, L., Del Pezzo, E., Patan! e, D., 2006. Shear wave splitting changes
associated with the 2001 volcanic eruption on Mt Etna. Geophysical Journal
International 167, 959–967.
Bianco, F., Zaccarelli, L., 2009. A reappraisal of shear wave splitting parameters
from Italian active volcanic areas through a semiautomatic algorithm. Journal
of Seismology 13, 253–266. doi:10.1007/s10950-008-9125-z.
Booth, D.C., Crampin, S., 1985. Shear-wave polarizations on a curved wavefront at
an isotropic free-surface. Geophysical Journal Royal Astronomical Society 83,
31–45.
Crampin, S., Volti, T., Stefa´ nsson, R., 1999. A successfully stress forecast earthquake.
Geophysical Journal International 138, F1–F5.
Crampin, S., Chastin, S., 2003. A review of shear wave splitting in the crack-critical
crust. Geophysical Journal International 155, 221–240.
Crampin, S., Gao, Y., 2006. A review of techniques for measuring shear-wave
splitting above small earthquakes. Physics of the Earth and Planetary Interiors
159, 1–14.
Crampin, S., Peacock, S., 2008. A review of the current understanding of seismic
shear-wave splitting in the Earth’s crust and common fallacies in interpretation.
Wave Motion 45, 675–722.
Di Vito, M.A., Isaia, R., Orsi, G., Southon, J., de Vita, S., D’Antonio, M., Pappalardo, L.,
Piochi, M., 1999. Volcanism and deformation since 12,000 years at the Campi
Flegrei caldera (Italy). Journal of Volcanology and Geothermal Research 91,
221–246.
Gao, Y., Hao, P., Crampin, S., 2006. SWAS: A shear-wave analysis system for semiautomatic
measurement of shear-wave splitting above small earthquakes.
Physics of the Earth and Planetary Interiors 159, 71–89.
Gerst, A., Savage, M.K., 2004. Seismic anisotropy beneath Ruapehu volcano: a
possible forecasting tool. Science 306, 1543–1547.
Goldstein, P., Snoke, A., 2005. SAC Availability for the IRIS Community. Incorporated
Institutions for Seismology Data Management Center Electronic Newsletter.
/http://www.iris.edu/news/newsletter/vol7no1/page1.htmS.
Hao, P., Gao, Y., Crampin, S., 2008. An Expert System for measuring shear-wave
splitting above small earthquakes. Computer & Geosciences 34, 226–234.
Jurkevics, A., 1988. Polarization analysis of 3-component array data. Bulletin of the
Seismological Society of America 78 (5), 1725–1743Klin, P., Priolo, E., 2008. Numerical simulation of seismic experiments in volcanic
areas: development of a technique based on the Pseudo-spectral Fourier
method and its application to the build up of synthetic data sets for the
Campi Flegrei area. In: Marzocchi, W., Zollo, A. (Eds.), Conception, Verification
and Application of Innovative Techniques to Study Active VolcanoesINGV-DPC,
Rome, pp. 233–248.
Savage, M.K., Wessel, A., Teanby, N.A., Hurst, A.W., 2010. Automatic measurement
of shear wave splitting and applications to time varying anisotropy at Mount
Ruapehu volcano, New Zealand. Journal of Geophysical Research 115,
B12321–255.
Silver, P.G., 1996. Seismic anisotropy beneath the continents: probing the depths
of geology. Annual Review of Earth and Planetary Sciences 24, 385–432.
Silver, P.G., Chan, W.W.J., 1991. Shear wave splitting and sub-continental mantle
deformation. Journal of Geophysical Research 96, 16429–16454.
Simons, F.J., 2004. Personal Webpage, open source software, /http://geoweb.
princeton.edu/people/simons/software.htmlS, [Accessed February 24, 2010].
Teanby, N.A., Kendall, J.M., Jones, R.H., Barkved, O., 2004a. Stress-induced temporal
variations in seismic anisotropy observed in microseismic data. Geophysical
Journal International 156, 459–466. doi:10.1111/j.1356-246X.2004.02212.x.
Teanby, N.A., Kendall, J.M., van der Baan, M., 2004b. Automation of shear-wave
splitting measurements using cluster analysis. Bulletin of the Seismological
Society of America 94, 453–463.
The Mathworks, Inc., 2011. Matlab. /www.mathworks.comS[Accessed January
24, 2011].
Trauth, M.H., 2007. Matlab Recipes for Earth Science, 2nd ed. Springer-Verlag,
Berlin, New York.
W¨ ustefeld, A., Bokelmann, G., Zaroli, C., Barroul, G., 2008. SplitLab: A shear-wave
splitting environment in Matlab. Computer & Geosciences 34, 515–528.
Wuestefeld, A., Al Arrasi, O., Verdon, J.P., Wookey, J., Kendall, M., 2010. A strategy
for automated analysis of passive microseismic data to image seismic
anisotropy and fracture characteristic. Geophysical Prospecting 58, 755–773.
Zaccarelli, L., Bianco, F., 2008. A shear wave analysis system for semi-automatic
measurements of shear wave splitting above volcanic earthquakes: descriptions
and applications. In: Marzocchi W., Zollo A. (Eds.), Conception, Verification
and Application of Innovative Techniques to Study Active Volcanoes.
INGV–DPC, Rome, pp. 113–124. ISBN 978-88-89972-09-0.
Zaccarelli, L., Pandolfi, D., Bianco, F., Saccorotti, G., Bean, C.J., Del Pezzo, E., 2009.
Temporal Changes in seismic wave propagation characteristics during
the 2002–2003 Mt Etna eruption. Geophysical Journal International 178,
1779–1788.
associated with the 2001 volcanic eruption on Mt Etna. Geophysical Journal
International 167, 959–967.
Bianco, F., Zaccarelli, L., 2009. A reappraisal of shear wave splitting parameters
from Italian active volcanic areas through a semiautomatic algorithm. Journal
of Seismology 13, 253–266. doi:10.1007/s10950-008-9125-z.
Booth, D.C., Crampin, S., 1985. Shear-wave polarizations on a curved wavefront at
an isotropic free-surface. Geophysical Journal Royal Astronomical Society 83,
31–45.
Crampin, S., Volti, T., Stefa´ nsson, R., 1999. A successfully stress forecast earthquake.
Geophysical Journal International 138, F1–F5.
Crampin, S., Chastin, S., 2003. A review of shear wave splitting in the crack-critical
crust. Geophysical Journal International 155, 221–240.
Crampin, S., Gao, Y., 2006. A review of techniques for measuring shear-wave
splitting above small earthquakes. Physics of the Earth and Planetary Interiors
159, 1–14.
Crampin, S., Peacock, S., 2008. A review of the current understanding of seismic
shear-wave splitting in the Earth’s crust and common fallacies in interpretation.
Wave Motion 45, 675–722.
Di Vito, M.A., Isaia, R., Orsi, G., Southon, J., de Vita, S., D’Antonio, M., Pappalardo, L.,
Piochi, M., 1999. Volcanism and deformation since 12,000 years at the Campi
Flegrei caldera (Italy). Journal of Volcanology and Geothermal Research 91,
221–246.
Gao, Y., Hao, P., Crampin, S., 2006. SWAS: A shear-wave analysis system for semiautomatic
measurement of shear-wave splitting above small earthquakes.
Physics of the Earth and Planetary Interiors 159, 71–89.
Gerst, A., Savage, M.K., 2004. Seismic anisotropy beneath Ruapehu volcano: a
possible forecasting tool. Science 306, 1543–1547.
Goldstein, P., Snoke, A., 2005. SAC Availability for the IRIS Community. Incorporated
Institutions for Seismology Data Management Center Electronic Newsletter.
/http://www.iris.edu/news/newsletter/vol7no1/page1.htmS.
Hao, P., Gao, Y., Crampin, S., 2008. An Expert System for measuring shear-wave
splitting above small earthquakes. Computer & Geosciences 34, 226–234.
Jurkevics, A., 1988. Polarization analysis of 3-component array data. Bulletin of the
Seismological Society of America 78 (5), 1725–1743Klin, P., Priolo, E., 2008. Numerical simulation of seismic experiments in volcanic
areas: development of a technique based on the Pseudo-spectral Fourier
method and its application to the build up of synthetic data sets for the
Campi Flegrei area. In: Marzocchi, W., Zollo, A. (Eds.), Conception, Verification
and Application of Innovative Techniques to Study Active VolcanoesINGV-DPC,
Rome, pp. 233–248.
Savage, M.K., Wessel, A., Teanby, N.A., Hurst, A.W., 2010. Automatic measurement
of shear wave splitting and applications to time varying anisotropy at Mount
Ruapehu volcano, New Zealand. Journal of Geophysical Research 115,
B12321–255.
Silver, P.G., 1996. Seismic anisotropy beneath the continents: probing the depths
of geology. Annual Review of Earth and Planetary Sciences 24, 385–432.
Silver, P.G., Chan, W.W.J., 1991. Shear wave splitting and sub-continental mantle
deformation. Journal of Geophysical Research 96, 16429–16454.
Simons, F.J., 2004. Personal Webpage, open source software, /http://geoweb.
princeton.edu/people/simons/software.htmlS, [Accessed February 24, 2010].
Teanby, N.A., Kendall, J.M., Jones, R.H., Barkved, O., 2004a. Stress-induced temporal
variations in seismic anisotropy observed in microseismic data. Geophysical
Journal International 156, 459–466. doi:10.1111/j.1356-246X.2004.02212.x.
Teanby, N.A., Kendall, J.M., van der Baan, M., 2004b. Automation of shear-wave
splitting measurements using cluster analysis. Bulletin of the Seismological
Society of America 94, 453–463.
The Mathworks, Inc., 2011. Matlab. /www.mathworks.comS[Accessed January
24, 2011].
Trauth, M.H., 2007. Matlab Recipes for Earth Science, 2nd ed. Springer-Verlag,
Berlin, New York.
W¨ ustefeld, A., Bokelmann, G., Zaroli, C., Barroul, G., 2008. SplitLab: A shear-wave
splitting environment in Matlab. Computer & Geosciences 34, 515–528.
Wuestefeld, A., Al Arrasi, O., Verdon, J.P., Wookey, J., Kendall, M., 2010. A strategy
for automated analysis of passive microseismic data to image seismic
anisotropy and fracture characteristic. Geophysical Prospecting 58, 755–773.
Zaccarelli, L., Bianco, F., 2008. A shear wave analysis system for semi-automatic
measurements of shear wave splitting above volcanic earthquakes: descriptions
and applications. In: Marzocchi W., Zollo A. (Eds.), Conception, Verification
and Application of Innovative Techniques to Study Active Volcanoes.
INGV–DPC, Rome, pp. 113–124. ISBN 978-88-89972-09-0.
Zaccarelli, L., Pandolfi, D., Bianco, F., Saccorotti, G., Bean, C.J., Del Pezzo, E., 2009.
Temporal Changes in seismic wave propagation characteristics during
the 2002–2003 Mt Etna eruption. Geophysical Journal International 178,
1779–1788.
Type
article
File(s)
No Thumbnail Available
Name
Splitting parameter yield (SPY) A program for semiautomatic analysis of shear-wave splitting.pdf
Description
main article
Size
618.35 KB
Format
Adobe PDF
Checksum (MD5)
2760b884c05ba20f79fce1c05cc78ca5