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

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.

[1]  Christopher John Young,et al.  A comparison of select trigger algorithms for automated global seismic phase and event detection , 1998, Bulletin of the Seismological Society of America.

[2]  M. Leonard,et al.  Multi-component autoregressive techniques for the analysis of seismograms , 1999 .

[3]  Reinoud Sleeman,et al.  Robust automatic P-phase picking: an on-line implementation in the analysis of broadband seismogram recordings , 1999 .

[4]  Weijian Mao,et al.  Polarization filtering for automatic picking of seismic data and improved converted phase detection , 2001 .

[5]  M. Leonard,et al.  Comparison of Manual and Automatic Onset Time Picking , 2000 .

[6]  Student,et al.  THE PROBABLE ERROR OF A MEAN , 1908 .

[7]  N. Maeda.  A Method for Reading and Checking Phase Time in Auto-Processing System of Seismic Wave Data , 1985 .

[8]  John E. Vidale,et al.  Complex polarization analysis of particle motion , 1986 .

[9]  Farid U. Dowla,et al.  Wavelet transform methods for phase identification in three-component seismograms , 1997, Bulletin of the Seismological Society of America.

[10]  R. V. Allen,et al.  Automatic phase pickers: Their present use and future prospects , 1982 .

[11]  Genshiro Kitagawa,et al.  A NEW EFFICIENT PROCEDURE FOR THE ESTIMATION OF ONSET TIMES OF SEISMIC WAVES , 1988 .

[12]  Y. Okabe,et al.  On a non-linear prediction problem for one-dimensional stochastic processes , 2001 .

[13]  Y. Okabe,et al.  The theory of KM2O-Langevin equations and its applications to data analysis (III): Deterministic analysis , 1998, Nagoya Mathematical Journal.

[14]  Y. Okabe.  On the theory of $\mathrm{KM}_{2O}$-Langevin equations for stationary flows (1): characterization theorem , 1999 .

[15]  Clifford H. Thurber,et al.  Automatic P-Wave Arrival Detection and Picking with Multiscale Wavelet Analysis for Single-Component Recordings , 2003 .

[16]  G. Tunnicliffe Wilson,et al.  Statistical analysis and control of dynamic systems , 1988 .

[17]  Yuji Nakano,et al.  The theory of $\text{KM}_{2}\text{O}$-Langevin equations and its applications to data analysis (I): Stationary analysis , 1991 .