Skip to main content

Advertisement

We’d like to understand how you use our websites in order to improve them. Register your interest.

Automatic seismic wave arrival detection and picking with stationary analysis: Application of the KM2O-Langevin equations

Abstract

An automatic detection and a precise picking of the arrival times of seismic waves using digital seismograms are important for earthquake early detection systems. Here we suggest a new method for detecting and picking P-and S-wave signals automatically. Compared to methods currently in use, our method requires fewer assumption with properties of the data time series. We divide a record into intervals of equal lengths and check the “local and weak stationarity” of each interval using the theory of the KM2O-Langevin equations. The intervals are stationary when these include only background noise, but the stationarity breaks abruptly when a seismic signal arrives and the intervals include both the background noise and the P-wave. This break of stationarity makes us possible to detect P-wave arrival. We expand the method for picking of S-waves. We applied our method to earthquake data from Hi-net Japan, and 90% of P-wave auto-picks were found to be within 0.1 s of the corresponding manual picks, and 70% of S-wave picks were within 0.1 s of the manual picks. This means that our method is accurate enough to use as a part of the seismic early detection system.

References

  1. Akaike, H. and T. Nakagawa, Statistical Analysis and Control of Dynamic Systems, KTK Scientific Publishers, Tokyo, 1988.

    Google Scholar 

  2. Allen, R., Automatic phase pickers: Their present use and future prospects, Bull. Seism. Soc. Am., 72, 225–242, 1982.

    Google Scholar 

  3. Anant, S. K. and F. U. Dowla, Wavelet transform methods for phase identification in three-component seismogram, Bull. Seism. Soc. Am., 87, 1598–1612, 1997.

    Google Scholar 

  4. Leonard, M., Comparison of manual and automatic onset time picking, Bull. Seism. Soc. Am., 90, 1384–1390, 2000.

    Article  Google Scholar 

  5. Leonard, M. and B. L. N. Kennett, Multi-component autoregressive techniques for the analysis of seismograms, Phys. Earth Planet. Interiors, 113, 247–264, 1999.

    Article  Google Scholar 

  6. Maeda, N., A method for reading and checking phase times in auto-processing system of seismic wave data, Zisin, 38, 365–379, 1985.

    Google Scholar 

  7. Matsuura, M. and Y. Okabe, On a non-linear prediction problem for one-dimensional stochastic processes, Japan J. Math., 27, 51–112, 2001.

    Google Scholar 

  8. Okabe, Y., On the theory of KM2O-Langevin equations for stationary flows (1): characterization theorem, J. Math. Soc. Japan., 51, 817–841, 1999.

    Article  Google Scholar 

  9. Okabe, Y., On the theory of KM2O-Langevin equations for stationary flows (2): construction theorem, Acta Applicandae Mathematicae., 63, 307–322, 2000.

    Article  Google Scholar 

  10. Okabe, Y. and Y. Nakano, The theory of KM2O-Langevin equations and its applications to data analysis (I): stationary analysis, Hokkaido Math. J., 20, 45–90, 1991.

    Article  Google Scholar 

  11. Okabe, Y. and T. Yamane, The theory of KM2O-Langevin equations and its applications to data analysis (II): deterministic analysis, Nagoya Math. J., 152, 175–201, 1998.

    Google Scholar 

  12. Okabe, Y., M. Matsuura, M. Takeo, and H. Ueda, On an abnormality test for detecting initial phases of earthquakes, Math. Eng. Tech. Rep., METR-2003-41, Department of Mathematical Informatics, The University of Tokyo, 2003.

    Google Scholar 

  13. Reading, A. M., W. Mao, and D. Gubbins, Polarization filtering for automatic picking of seismic data and improved converted phase detection, Geophys. J. Int., 147, 227–234, 2001.

    Article  Google Scholar 

  14. Sleeman, R. and T. van Eck, Robust automatic P-phase picking: an on-line implementation in the analysis of broadband seismogram recordings, Phys. Earth Planet. Interiors, 113, 265–275, 1999.

    Article  Google Scholar 

  15. Snedecor, G. W., W. G. Cochran, ISU Statistics Depts. Staff, D. F. Cox, Statistical Methods, 8th ed., pp. 53–55, pp. 71-73, Blackwell Publishing Limited, 1989.

    Google Scholar 

  16. Student (Gosset, W. S.), The probable error of a mean, Biometrika, 6, 1., 1–25, 1908

    Article  Google Scholar 

  17. Takanami, T. and G. Kitagawa, A new efficient procedure for the estimation of onset times of seismic waves, J. Phys. Earth, 36, 267–290, 1988.

    Article  Google Scholar 

  18. Vidale, J. E., Complex polarization analysis of particle motion, Bull. Seism. Soc. Am., 76, 1393–1405, 1986.

    Google Scholar 

  19. Withers, M., R. Aster, C. Young, J. Beiriger, M. Harris, S. Moore, and J. Trujikko, A comparison of select trigger algorithms for automated global seismic phase and event detection, Bull. Seism. Soc. Am., 88, 95–106, 1998.

    Google Scholar 

  20. Yokota, T., S. Zhou, M. Mizoue, and I. Nakamura, An automatic measurement of the arrival time of seismic waves and its application to an on-line processing system, Bull. Earthq. Res. Inst. Univ. Tokyo, 55, 449–484, 1981 (in Japanese with English abstract).

    Google Scholar 

  21. Zhang, H., C. Thurber, and C. Rowe, Automatic P-Wave arrival detection and picking with multiscale wavelet analysis for single-component recordings, Bull. Seism. Soc. Am., 93, 1904–1912, 2003.

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Sho Nakamula.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Nakamula, S., Takeo, M., Okabe, Y. et al. Automatic seismic wave arrival detection and picking with stationary analysis: Application of the KM2O-Langevin equations. Earth Planet Sp 59, 567–577 (2007). https://doi.org/10.1186/BF03352719

Download citation

Key words

  • Waveform
  • arrival
  • picker
  • KM2O-Langevin equations
  • auto-regressive model
  • P-wave
  • S-wave