Automatic microseismic denoising and onset detection using the synchrosqueezed continuous wavelet transform

ABSTRACTTypical microseismic data recorded by surface arrays are characterized by low signal-to-noise ratios (S/Ns) and highly nonstationary noise that make it difficult to detect small events. Currently, array or crosscorrelation-based approaches are used to enhance the S/N prior to processing. We have developed an alternative approach for S/N improvement and simultaneous detection of microseismic events. The proposed method is based on the synchrosqueezed continuous wavelet transform (SS-CWT) and custom thresholding of single-channel data. The SS-CWT allows for the adaptive filtering of time- and frequency-varying noise as well as offering an improvement in resolution over the conventional wavelet transform. Simultaneously, the algorithm incorporates a detection procedure that uses the thresholded wavelet coefficients and detects an arrival as a local maxima in a characteristic function. The algorithm was tested using a synthetic signal and field microseismic data, and our results have been compared wit...

[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]  Flavio Poletto,et al.  A blind interpretation of drill‐bit signals , 2000 .

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

[4]  E. Mousset,et al.  A connectionist approach for automatic labeling of regional seismic phases using a single vertical component seismogram , 1996 .

[5]  Peter M. Shearer,et al.  Characterization of global seismograms using an automatic-picking algorithm , 1994, Bulletin of the Seismological Society of America.

[6]  Susan E. Hough,et al.  Frequency-Dependent Seismic Attenuation within the Hispaniola Island Region of the Caribbean Sea , 2012 .

[7]  H. Akaike.  A new look at the statistical model identification , 1974 .

[8]  R. Roberts,et al.  Real-time event detection, phase identification and source location estimation using single station three-component seismic data , 1989 .

[9]  Michael J. Procopio,et al.  Estimation of arrival times from seismic waves: a manifold-based approach* , 2011 .

[10]  E. Wagenmakers,et al.  AIC model selection using Akaike weights , 2004, Psychonomic bulletin & review.

[11]  Jean Baptiste Tary,et al.  Potential use of resonance frequencies in microseismic interpretation , 2012 .

[12]  A. Jurkevics.  Polarization analysis of three-component array data , 1988 .

[13]  F. Ringdal,et al.  The detection of low magnitude seismic events using array-based waveform correlation , 2006 .

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

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

[16]  Chuan Li,et al.  A generalized synchrosqueezing transform for enhancing signal time-frequency representation , 2012, Signal Process..

[17]  R. Paul Young,et al.  Using Continuous Microseismic Records for Hydrofracture Diagnostics and Mechanics , 2009 .

[18]  Ali M. Reza,et al.  Automatic Earthquake Signal Onset Picking Based on the Continuous Wavelet Transform , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[19]  Arye Nehorai,et al.  Analysis of a polarized seismic wave model , 1996, IEEE Trans. Signal Process..

[20]  Jouni Saari.  Automated phase picker and source location algorithm for local distances using a single three-component seismic station , 1991 .

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

[22]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[23]  E. R. Kanasewich,et al.  Time sequence analysis in geophysics , 1973 .

[24]  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.

[25]  Hengchang Dai,et al.  Automatic picking of seismic arrivals in local earthquake data using an artificial neural network , 1995 .

[26]  Gregory C. Beroza,et al.  PageRank for Earthquakes , 2014 .

[27]  Daniel E. McNamara,et al.  Ambient Noise Levels in the Continental United States , 2004 .

[28]  Miaki Ishii,et al.  Continuous Wavelet Decomposition Algorithms for Automatic Detection of Compressional‐ and Shear‐Wave Arrival Times , 2015 .

[29]  Stefano Parolai,et al.  Denoising of Seismograms Using the S Transform , 2009 .

[30]  N. Magotra,et al.  Single-station seismic event detection and location , 1989 .

[31]  Ta-Liang Teng,et al.  Artificial neural network-based seismic detector , 1995, Bulletin of the Seismological Society of America.

[32]  Mirko van der Baan,et al.  Applications of the synchrosqueezing transform in seismic time-frequency analysis , 2014 .

[33]  Manfred Baer,et al.  An automatic phase picker for local and teleseismic events , 1987 .

[34]  Mark D. Zoback,et al.  Long-period, long-duration seismic events during hydraulic fracture stimulation of a shale gas reservoir , 2011 .

[35]  E. S. Husebye,et al.  A new three-component detector and automatic single-station bulletin production , 1992 .

[36]  Geoffrey J. McLachlan,et al.  Finite Mixture Models , 2019, Annual Review of Statistics and Its Application.

[37]  Colin MacBeth,et al.  The application of back‐propagation neural network to automatic picking seismic arrivals from single‐component recordings , 1997 .

[38]  Hau-Tieng Wu,et al.  The Synchrosqueezing algorithm for time-varying spectral analysis: Robustness properties and new paleoclimate applications , 2011, Signal Process..

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

[40]  S. Mostafa Mousavi,et al.  Average QLg, QSn, and observation of Lg blockage in the Continental Margin of Nova Scotia , 2014 .

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

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

[43]  Christophe Maisons,et al.  Validation of Surface and Shallow Microseismic Array for Deep Reservoir Monitoring , 2012 .

[44]  Jerry M. Mendel,et al.  First break refraction event picking using fuzzy logic systems , 1994, IEEE Trans. Fuzzy Syst..

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

[46]  M. Farge.  Wavelet Transforms and their Applications to Turbulence , 1992 .

[47]  ThakurGaurav,et al.  The Synchrosqueezing algorithm for time-varying spectral analysis , 2013 .

[48]  Mirko van der Baan,et al.  Spectral estimation—What is new? What is next? , 2014 .

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

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

[51]  Paul Anderson,et al.  It's a matter of size: Magnitude and moment estimates for microseismic data , 2010 .

[52]  A. Grossmann,et al.  DECOMPOSITION OF HARDY FUNCTIONS INTO SQUARE INTEGRABLE WAVELETS OF CONSTANT SHAPE , 1984 .

[53]  S. K. Yung,et al.  An example of seismic time picking by third-order bicoherence , 1997 .

[54]  S. Mostafa Mousavi,et al.  Hybrid Seismic Denoising Using Higher-Order Statistics and Improved Wavelet Block Thresholding , 2016 .

[55]  Yehuda Ben-Zion,et al.  Automatic picking of direct P, S seismic phases and fault zone head waves , 2014 .

[56]  Leo Eisner,et al.  Comparison of surface and borehole locations of induced seismicity , 2010 .

[57]  Aldo Zollo,et al.  Short Note S-Wave Identification by Polarization Filtering and Waveform Coherence Analyses , 2012 .

[58]  Athanasios Lois,et al.  Strategy for automated analysis of passive microseismic data based on S-transform, Otsu's thresholding, and higher order statistics , 2012 .

[59]  Yangkang Chen,et al.  Random noise attenuation by f-x empirical mode decomposition predictive filtering , 2014 .

[60]  I. Daubechies.  Orthonormal bases of compactly supported wavelets , 1988 .

[61]  Mostafa Naghizadeh,et al.  Seismic data interpolation and denoising in the frequency-wavenumber domain , 2012 .

[62]  E. S. Husebye,et al.  Wavefield decomposition using ML-probabilities in modelling single-site 3-component records , 1988 .

[63]  L. Hadjileontiadis,et al.  A higher-order statistics-based phase identification of three-component seismograms in a redundant wavelet transform domain , 1999, Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics. SPW-HOS '99.

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

[65]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[66]  Mauricio D. Sacchi,et al.  Multicomponent f-x seismic random noise attenuation via vector autoregressive operators , 2012 .

[67]  Ingrid Daubechies,et al.  A Nonlinear Squeezing of the Continuous Wavelet Transform Based on Auditory Nerve Models , 2017 .

[68]  Stavros M. Panas,et al.  Automatic P phase picking using maximum kurtosis and κ-statistics criteria , 2004, IEEE Geosci. Remote. Sens. Lett..

[69]  Christopher Heil,et al.  Continuous and Discrete Wavelet Transforms , 1989, SIAM Rev..

[70]  Gregory C. Beroza,et al.  An Empirical Approach to Subspace Detection , 2014 .

[71]  Elizabeth Campbell,et al.  Microseismic Deformation Rate Monitoring , 2009 .

[72]  C. Scholz,et al.  Two types of reservoir-induced seismicity , 1988 .

[73]  Alberto Michelini,et al.  Automatic picking of P and S phases using a neural tree , 2006 .

[74]  G-Akis Tselentis,et al.  A new automatic S-onset detection technique: Application in local earthquake data , 2013 .

[75]  Leo Eisner,et al.  Reservoir characterization using surface microseismic monitoring , 2010 .

[76]  Haizhao Yang,et al.  Synchrosqueezed wave packet transforms and diffeomorphism based spectral analysis for 1D general mode decompositions , 2013, 1311.4655.

[77]  D. Donoho.  Nonlinear Solution of Linear Inverse Problems by Wavelet–Vaguelette Decomposition , 1995 .

[78]  Patrick Flandrin,et al.  One or Two frequencies? The Synchrosqueezing Answers , 2011, Adv. Data Sci. Adapt. Anal..

[79]  C. Pearson,et al.  The relationship between microseismicity and high pore pressures during hydraulic stimulation experiments in low permeability granitic rocks , 1981 .

[80]  Sylvain Meignen,et al.  Time-Frequency Reassignment and Synchrosqueezing: An Overview , 2013, IEEE Signal Processing Magazine.

[81]  Federico Botella,et al.  A real-time earthquake detector with prefiltering by wavelets , 2003 .

[82]  Anne Mangeney,et al.  An Automatic Kurtosis‐Based P ‐ and S ‐Phase Picker Designed for Local Seismic Networks , 2014 .

[83]  Vladimir Grechka,et al.  Future of Microseismic Analysis: Integration of Monitoring and Reservoir Simulation , 2011 .

[84]  Martin Vetterli,et al.  Adaptive wavelet thresholding for image denoising and compression , 2000, IEEE Trans. Image Process..

[85]  G. A. Sobolev,et al.  Microseismic impulses as earthquake precursors , 2006 .

[86]  P. P. Vaidyanathan,et al.  Wavelet-based denoising by customized thresholding , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[87]  Richard M. Allen,et al.  Automatic detection and rapid determination of earthquake magnitude by wavelet multiscale analysis of the primary arrival , 2006 .

[88]  I. Johnstone,et al.  Ideal spatial adaptation by wavelet shrinkage , 1994 .

[89]  Jean Baptiste Tary,et al.  Time-varying autoregressive model for spectral analysis of microseismic experiments and long-period volcanic events , 2014 .

[90]  I. Daubechies,et al.  Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool , 2011 .

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

[92]  Mirko van der Baan,et al.  Body Wave Separation in the Time-Frequency Domain , 2015, IEEE Geoscience and Remote Sensing Letters.

[93]  Jiajun Han,et al.  Microseismic and seismic denoising via ensemble empirical mode decomposition and adaptive thresholding , 2015 .

[94]  Mark W. McClure,et al.  The Importance of Slow Slip on Faults During Hydraulic Fracturing Stimulation of Shale Gas Reservoirs , 2012 .

[95]  Mirko van der Baan,et al.  Random and coherent noise attenuation by empirical mode decomposition , 2009 .

[96]  N. Magotra,et al.  Seismic event detection and source location using single-station (three-component) data , 1987 .