Skip to main content
SpringerLink
Log in

Waveform Retrieval and Phase Identification for Seismic Data from the CASS Experiment

  • Published:
Pure and Applied Geophysics Aims and scope Submit manuscript

Abstract

The little destruction to the deployment site and high repeatability of the Controlled Accurate Seismic Source (CASS) shows its potential for investigating seismic wave velocities in the Earth's crust. However, the difficulty in retrieving impulsive seismic waveforms from the CASS data and identifying the seismic phases substantially prevents its wide applications. For example, identification of the seismic phases and accurate measurement of travel times are essential for resolving the spatial distribution of seismic velocities in the crust. Until now, it still remains a challenging task to estimate the accurate travel times of different seismic phases from the CASS data which features extended wave trains, unlike processing of the waveforms from impulsive events such as earthquakes or explosive sources. In this study, we introduce a time-frequency analysis method to process the CASS data, and try to retrieve the seismic waveforms and identify the major seismic phases traveling through the crust. We adopt the Wigner-Ville Distribution (WVD) approach which has been used in signal detection and parameter estimation for linear frequency modulation (LFM) signals, and proves to feature the best time-frequency convergence capability. The Wigner-Hough transform (WHT) is applied to retrieve the impulsive waveforms from multi-component LFM signals, which comprise seismic phases with different arrival times. We processed the seismic data of the 40-ton CASS in the field experiment around the Xinfengjiang reservoir with the WVD and WHT methods. The results demonstrate that these methods are effective in waveform retrieval and phase identification, especially for high frequency seismic phases such as PmP and SmS with strong amplitudes in large epicenter distance of 80–120 km. Further studies are still needed to improve the accuracy on travel time estimation, so as to further promote applicability of the CASS for and imaging the seismic velocity structure.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Alekseev, A.S., Chichinin, I.S. and Korneev, V.A., 2005. Powerful low-frequency vibrators for active seismology. Bull. Seismol. Soc. Am., 95, 1–17.

  • Bakun, W.H. and Joyner, W.B., 1984. The M L scale in central California. Bull. Seismol. Soc. Am., 74, 1827–1843.

  • Barbarossa, S., 1995. Analysis of multicomponent LFM signals by a combined Wigner-Rough transform. IEEE Signal, 43, 1511–1515.

  • Brenguier, F., Campillo, M., Hadziioannou, C., Shapiro, N.M., Nadeau, R.M. and Larose, E., 2008. Postseismic relaxation along the San Andreas Fault at Parkfield from continuous seismological observations, Science, 321, 1478–1481.

  • Chen, Y. and Li, Y.J., 2007a. Seismic wave radar research: using active source to detect continental crust structure. J. Univer. Sci. and Tech. of China, 37, 813–819.

  • Chen, Y., Zhang, X.K., Qiu, X.L., Ge, H.K., Liu, B.J. and Wang, B.S., 2007b. A new way to generate seismic waves for continental crustal exploration. Chinese Sci. Bull., 52, 1317–1321.

  • Choi, H. and Williams, W.J., 1988. Improved time-frequency representation of multicomponent signals using exponential kernels. IEEE Trans on SP, 37, 862–871.

  • Christensen, N.I. and Mooney, W.D., 1995. Seismic velocity structure and composition of the continental crust: A global view. J. Geophys. Res., 100, B7, 9761–9788.

  • Diao, F., Xiong, X. and Wang, R., 2011. Mechanisms of transient postseismic deformation following the 2001 Mw 7.8 Kunlun (China) Earthquake. Pure App. Geophys., 168, 767–779.

  • Hadziioannou, C., Larose, E., Baig, A., Roux, P. and Campillo, M., 2011. Improving temporal resolution in ambient noise monitoring of seismic wave speed. J. Geophys. Res., 116, B07304.

  • Haimovich, A.M., Peckham, C. and Teti, J.G., 1994. SAR imagery of moving targets: Application of time-frequency distributions for estimating motion parameters. In: Proc 1994 SPIE’s International Symposium on Aerospace and Sensing, 2238, 238–247.

  • Hutton, L.K. and Boore, D.M., 1987. The M L scale in southern California. Bull. Seismol. Soc. Am., 77, 2074–2094.

  • Ikuta, R., Yamaoka, K., Miyakawa, K., Kunitomo, T. and Kumazawa, M., 2002. Continuous monitoring of propagation velocity of seismic wave using ACROSS. Geophys. Res. Lett., 29, 1627.

  • Ikuta, R. and Yamaoka, K., 2004. Temporal variation in the shear wave anisotropy detected using the Accurately Controlled Routinely Operated Signal System (ACROSS). J. Geophys. Res., 109, B09305.

  • Leary, P.C., Malin, P.E., Phinny, R.A., Brocher, T. and VonColln, R., 1979. Systematic monitoring of millisecond traveltime variations near Palmdale, California. J. Geophys. Res., 84, 659–666.

  • Li, S.L., Mooney, W.D. and Fan, J.C., 2006. Crustal structure of mainland China from deep seismic sounding data. Tectonophysics, 420, 239–252.

  • Liao, C.W., Zhuang, C.T. and Liang, H.S., 2003. Initial experimental result of Accurately Controlled Routinely Operated Signal System (ACROSS). Earthq. Res. in China, 19, 89–96.

  • Liu, K. S. and Tsai, Y. B., 2009. Large effects of Moho reflections (SmS) on peak ground motion in Northwestern Taiwan. Bull. Seismol. Soc. Am., 99, 255–267.

  • Luo, Y., Ni, S.D. and Chen, Y., 2010. A case study on the effect of post-critical SmS on ground motion in Yingjiang, Yunnan Province, China. Earthq. Res. in China., 26, 131–141.

  • Mori, J. and Helmberger, D.V., 1996. Large-amplitude Moho reflection (SmS) from Landers aftershocks, southern California, Bull. Seismol. Soc. Am., 86, 1845–1852.

  • Ni, S.D., Siddharthan, R.V. and Anderson, J.G., 1997. Characteristics of nonlinear response of deep saturated solid deposits. Bull. Seismol. Soc. Am., 87, 342–355.

  • Nielsen, C. and Thybo, H., 2009. Lower crustal intrusions beneath the southern Baikal Rift Zone: Evidence from full-waveform modelling of wide-angle seismic data. Tectonophysics, 470, 298–318.

  • Niu, F.L., Silver, P.G., Thomas, D.M., Cheng, X. and Majer, E.L., 2008. Preseismic velocity changes observed from active source monitoring at the Parkfield SAFOD drill site. Nature, 454, 204–208.

  • Peng, Z. and Ben-Zion, Y., 2006. Temporal changes of shallow seismic velocity around the Karadere-Duzce branch of the North anatolian fault and strong ground motion. Pure Appl. Geophys., 163, 567–599.

  • Rao, R. and Taylor, F.J., 1990. Estimation of instantaneous frequency using the discrete Wigner distribution. Electr. Lett., 26, 246–248.

  • Reasenberg, P. and Aki, K., 1974. A precise, continuous measurement of seismic velocity for monitoring in situ stress. J. Geophys. Res., 79, 399–406.

  • Saiga, A., Yamaoka, K. and Kunitomo, T., 2006. Continuous observation of seismic wave velocity and apparent velocity using a precise seismic array and ACROSS seismic source. Earth Planets Space, 58, 993–1005.

  • Schaff, D.P. and Richards, P.G., 2004. Repeating seismic events in China. Science, 303, 1176–1178.

  • Selin, A. and William, J.W., 2005. Minimum entropy time-frequency distributions. IEEE Sig. Pro. Lett., 12, 37–40.

  • Silver, P.G., Daley, T.M., Niu, F. and Majer, E.L., 2007. Active source monitoring of cross-well seismic traveltime for stress-induced changes. Bull. Seismol. Soc. Am., 97, 281–293.

  • Wang, B.S., Yang, W., Yuan, S.Y., Guo, S.J., Ge, H.K., Xu, P. and Chen, Y., 2010. An experimental study on the excitation of large volume airgun in small volume water body. J. Geophys. Eng., 7, 388–394.

  • Wang, B.S., Wang, W.T., Ge, H.K., Xu, P. and Wang, B., 2011. Monitoring subsurface changes with active sources. Advances in Earth Science, 26, 249–256.

  • Wang, H.T., Zhuang, S.T., Xue, B., Zhao, C.P. and Zhu, Z.Y., 2009a. Precisely and actively seismic monitoring. Chinese J. Geophys., 52, 1808–1815.

  • Wang, W.T., Wang, B.S., Ge, H.K., Chen, Y., Yuan, S.Y., Yang, W. and Li, Y.J., 2009b. Using active source to monitor velocity variation in shallow sediment caused by the Wenchuan Earthquake. Earthq. Res. in China, 25, 223–233.

  • Wu, C.Q., Peng, Z.G. and Ben-Zion, Y., 2009. Non-linearity and temporal changes of fault zone site response associated with strong ground motion. Geophys. J. Int., 176, 265–278.

  • Xu, Z.J. and Song, X.D., 2009. Temporal changes of surface wave velocity associated with major Sumatra earthquakes from ambient noise correlation. PNAS, 106, 14207–14212.

  • Yang, W., Ge, H.K. and Wang, B.S., 2010. Velocity changes observed by the precisely controlled active source for the Mianzhu M s 5.6 earthquake. Chinese J. Geophys., 53, 1149–1157.

  • Yang, Z., Liu, B., Wang, Q., Wang, H., Yuan, S., 2011. 2-D P-wave velocity structure in the Xinfengjiang reservoir area - Results of Yingde-Heyuan-Luhe deep seismic sounding profile. Progress in Geophys. (in Chinese), 26(6), 1968–1975.

  • Yamamura, K., Sano, O., Utada, H.,Takei, Y., Nakao, S. and Fukao, Y., 2003. Long-term observation of in situ seismic velocity and attenuation. J. Geophys. Res., 108, B6, 2317.

  • Yamaoka, K., Kunitomo, T., Miyakawa, K., Kobayashi, K. and Kumazawa, M., 2001. A trial for monitoring temporal variation of seismic velocity using an ACROSS system. The Island Arc, 10, 336–347.

  • Zhu, L.P., and Rivera, A., 2002. A note on the dynamic and static displacements from a point source in multilayered media. Geophys. J. Int., 148, 619–627.

Download references

Acknowledgments

We would like to thank the Editor, Dr. Elena Kozlovskaya, Dr. Mariusz Majdanski and an anonymous reviewer for their valuable comments, which greatly improved the manuscript. This work was supported by China Earthquake Administration fund (Grant No. 200808068), NSFC (Grant No. 41074032) and special fund from the State Key Laboratory of Geodesy and Earth’s Dynamics.

Author information

Authors and Affiliations

  1. State Key Laboratory of Geodesy and Earth’s Dynamics, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, 430077, China

    Zhiwei Li & Sidao Ni

  2. Key Laboratory of Petroleum Resource Research, Institute of Geology and Geophysics Chinese Academy of Sciences, Beijing, 100029, China

    Qingyu You & Tianyao Hao

  3. Institute of Earthquake Science, China Earthquake Administration, Beijing, 100036, China

    Hongti Wang & Cantao Zhuang

Authors
  1. Zhiwei Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qingyu You
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sidao Ni
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tianyao Hao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hongti Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Cantao Zhuang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Qingyu You or Sidao Ni.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Li, Z., You, Q., Ni, S. et al. Waveform Retrieval and Phase Identification for Seismic Data from the CASS Experiment. Pure Appl. Geophys. 170, 815–830 (2013). https://doi.org/10.1007/s00024-012-0585-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00024-012-0585-2

Keywords

Search

Navigation