Estimation of arrival times from seismic waves: a manifold-based approach*

SUMMARY We propose a new method to analyse seismic time-series and estimate the arrival times of seismic waves. Our approach combines two ingredients: the time-series are first lifted into a highdimensional space using time-delay embedding; the resulting phase space is then parametrized using a non-linear method based on the eigenvectors of the graph Laplacian. We validate our approach using a data set of seismic events that occurred in Idaho, Montana, Wyoming and Utah between 2005 and 2006. Our approach outperforms methods based on singular-spectrum analysis, wavelet analysis and short-term average/long-term average (STA/LTA).

[1]  Filippos Vallianatos,et al.  Automatic $P$-Phase Picking Based on Local-Maxima Distribution , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[2]  John M. Lee Introduction to Topological Manifolds , 2000 .

[3]  Thomas Meier,et al.  Automated determination of P-phase arrival times at regional and local distances using higher order statistics , 2010 .

[4]  Andreas Rietbrock,et al.  Optimized automatic pickers: application to the ANCORP data set , 2010 .

[5]  Jin Wang Adaptive Training of Neural Networks for Automatic Seismic Phase Identification , 2002 .

[6]  D. Broomhead,et al.  Cancelling deterministic noise by constructing nonlinear inverses to linear filters , 1996 .

[7]  Vera Schlindwein,et al.  Nature, wavefield properties and source mechanism of volcanic tremor: a review , 2003 .

[8]  R. Vautard,et al.  Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series , 1989 .

[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]  D. Giardini,et al.  Automatic seismic phase picking and consistent observation error assessment: application to the Italian seismicity , 2006 .

[11]  J. Virieux,et al.  An hp-adaptive discontinuous Galerkin finite-element method for 3-D elastic wave modelling , 2010 .

[12]  Stavros M. Panas,et al.  PAI-S/K: A robust automatic seismic P phase arrival identification scheme , 2002, IEEE Trans. Geosci. Remote. Sens..

[13]  Dimitris Manolakis,et al.  Rapid Joint Detection and Classification with Wavelet Bases via Bayes Theorem , 2000 .

[14]  R. Gilmore Topological analysis of chaotic dynamical systems , 1998 .

[15]  U. Feige,et al.  Spectral Graph Theory , 2015 .

[16]  C. Richter An instrumental earthquake magnitude scale , 1935 .

[17]  Juan J. Galiana-Merino,et al.  Seismic $P$ Phase Picking Using a Kurtosis-Based Criterion in the Stationary Wavelet Domain , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Chi K. Tse,et al.  Optimal embedding parameters: a modelling paradigm , 2004 .

[19]  Marian Anghel,et al.  Dynamical System Analysis and Forecasting of Deformation Produced by an Earthquake Fault , 2003, physics/0305099.

[20]  G. P. King,et al.  Extracting qualitative dynamics from experimental data , 1986 .

[21]  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.

[22]  Walter Freiberger,et al.  AN APPROXIMATE METHOD IN SIGNAL DETECTION , 1963 .

[23]  Henry D I Abarbanel,et al.  False neighbors and false strands: a reliable minimum embedding dimension algorithm. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[24]  K. Konstantinou,et al.  Deterministic non-linear source processes of volcanic tremor signals accompanying the 1996 Vatnajökull eruption, central Iceland , 2002 .

[25]  J. A. Stewart,et al.  Nonlinear Time Series Analysis , 2015 .

[26]  Konstantinos Papadopoulos,et al.  Reconstruction of low‐dimensional magnetospheric dynamics by singular spectrum analysis , 1993 .

[27]  Martin Casdagli,et al.  Nonlinear prediction of chaotic time series , 1989 .

[28]  L. Tsimring,et al.  The analysis of observed chaotic data in physical systems , 1993 .

[29]  L. Persson Statistical tests for regional seismic phase characterizations , 2003 .

[30]  James P. Crutchfield,et al.  Geometry from a Time Series , 1980 .

[31]  R. V. Allen,et al.  Automatic earthquake recognition and timing from single traces , 1978, Bulletin of the Seismological Society of America.

[32]  Mikhail Belkin,et al.  Laplacian Eigenmaps for Dimensionality Reduction and Data Representation , 2003, Neural Computation.

[33]  E. Pezzo,et al.  Model for high‐frequency Strombolian tremor inferred by wavefield decomposition and reconstruction of asymptotic dynamics , 2008 .

[34]  The “little variable factor” a statistical discussion of the reading of seismograms , 1966 .

[35]  Jon Berger,et al.  Seismic Detectors: The State-of-the-Art , 1981 .

[36]  Guo Yuan,et al.  Estimating the predictability of an oceanic time series using linear and nonlinear methods , 2004 .

[37]  F. Takens Detecting strange attractors in turbulence , 1981 .

[38]  Amir Averbuch,et al.  A diffusion framework for detection of moving vehicles , 2010, Digit. Signal Process..

[39]  P. Mazzega,et al.  Detectability of deterministic non-linear processes in Earth rotation time-series—II. Dynamics , 1999 .

[40]  David Pozo-Vázquez,et al.  Spectral characteristics and predictability of the NAO assessed through Singular Spectral Analysis , 2002 .

[41]  David W. Scott,et al.  Multivariate Density Estimation: Theory, Practice, and Visualization , 1992, Wiley Series in Probability and Statistics.

[42]  Ronald R. Coifman,et al.  Diffusion Maps, Reduction Coordinates, and Low Dimensional Representation of Stochastic Systems , 2008, Multiscale Model. Simul..

[43]  R. Coifman,et al.  Diffusion Wavelets , 2004 .

[44]  Naoki Saito,et al.  Data Analysis and Representation on a General Domain using Eigenfunctions of Laplacian , 2008 .

[45]  P. Mazzega,et al.  Detectability of deterministic non-linear processes in Earth rotation time-series-II. Dynamics: Non-linear processes in Earth rotation time-series---II , 2002 .

[46]  Martin Käser,et al.  Dynamic rupture modeling on unstructured meshes using a discontinuous Galerkin method , 2009 .

[47]  Intermittent behaviour of volcanic tremor at Mt. Etna , 1996 .

[48]  Fractal properties of tremor and gas piston events observed at Kilauea Volcano, Hawaii , 1991 .

[49]  Schreiber,et al.  Noise reduction in chaotic time-series data: A survey of common methods. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[50]  Alexander Zien,et al.  Semi-Supervised Learning , 2006 .

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

[52]  J. Ampuero,et al.  Spectral element modeling of spontaneous earthquake rupture on rate and state faults: Effect of velocity‐strengthening friction at shallow depths , 2008 .

[53]  Philippe Gaillot,et al.  Characterization of seismic waveforms and classification of seismic events using chirplet atomic decomposition. Example from the Lacq gas field (Western Pyrenees, France) , 2006 .

[54]  R. K. Tiwari,et al.  Nature of earthquake dynamics in the central Himalayan region: a nonlinear forecasting analysis , 2003 .

[55]  A. Velasco UNCERTAINTY IN PHASE ARRIVAL TIME PICKS FOR REGIONAL SEISMIC EVENTS: AN EXPERIMENTAL DESIGN , 2001 .

[56]  N. Lapusta,et al.  Three‐dimensional boundary integral modeling of spontaneous earthquake sequences and aseismic slip , 2009 .

[57]  Kevin Judd,et al.  Embedding as a modeling problem , 1998 .

[58]  G. Akrivis A First Course In The Numerical Analysis Of Differential Equations [Book News & Reviews] , 1998, IEEE Computational Science and Engineering.

[59]  P. Bérard,et al.  Embedding Riemannian manifolds by their heat kernel , 1994 .

[60]  M. Maggioni,et al.  Manifold parametrizations by eigenfunctions of the Laplacian and heat kernels , 2008, Proceedings of the National Academy of Sciences.

[61]  John M. Lee Riemannian Manifolds: An Introduction to Curvature , 1997 .

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

[63]  Sunil Arya,et al.  An optimal algorithm for approximate nearest neighbor searching fixed dimensions , 1998, JACM.

[64]  Eric R. Ziegel,et al.  The Elements of Statistical Learning , 2003, Technometrics.

[65]  Cataldo Godano,et al.  Dynamical similarity of explosions at Stromboli volcano , 2004 .

[66]  Yehuda Ben-Zion,et al.  Collective behavior of earthquakes and faults: Continuum‐discrete transitions, progressive evolutionary changes, and different dynamic regimes , 2008 .