Volume 44 Issue 3
Jun.  2022
Turn off MathJax
Article Contents
Meng J,Wu Y X,Li Y N. 2022. First arrival time picking algorithm of micro-seismic based on improved STA/LTA and adaptive VMD. Acta Seismologica Sinica,44(3):388−400 doi: 10.11939/jass.20200199
Citation: Meng J,Wu Y X,Li Y N. 2022. First arrival time picking algorithm of micro-seismic based on improved STA/LTA and adaptive VMD. Acta Seismologica Sinica44(3):388−400 doi: 10.11939/jass.20200199

First arrival time picking algorithm of micro-seismic based on improved STA/LTA and adaptive VMD

doi: 10.11939/jass.20200199
  • Received Date: 2020-12-04
  • Rev Recd Date: 2021-05-26
  • Available Online: 2022-04-08
  • Publish Date: 2022-06-27
  • Accurate and reliable picking of the first arrival time is one of the critical steps in micro-seismic monitoring. Aiming at the problem of low accuracy of first arrival picking for micro-seisms under low signal-to-noise ratio, the traditional short term averaging/long term averaging algorithm is improved by introducing weight factor according to the change of signal amplitude to improve the accuracy of initial pickup. In order to further reduce the pickup error, variational mode decomposition (VMD) is optimized based on cross-correlation coefficient and permutation entropy criterion, and decomposition layers are determined adaptively. Then, the signals of 2−3 s before and after the initial pickup are decomposed by VMD, and the Kurtosis-Akaike information criterion (AIC) values of the decomposed intrinsic mode functions (IMF) are calculated to get the arrival time of each IMF, and the secondary arrival time is obtained by comprehensively weighting the picking results and energy ratios of each IMF. Simulation results show that the improved STA/LTA can reduce the initial picking error by more than 0.01 s at low SNR; compared with empirical mode decomposition (EMD) and wavelet packet decomposition, the adaptive VMD decomposition can reduce the picking error again, and the finalaverage picking error is less than 0.023 s. The first arrival time picking results of real micro-seismic signals show that the proposed algorithm can identify the first break of P-wave quickly and effectively, and the error is smaller than that of manual picking, which shows that the algorithm is effective and the picking accuracy is high.

     

  • loading
  • [1]
    Jia R S,Tan Y L,Sun H M,Hong Y F. 2015. Method of automatic detection on micro-seismic P-arrival time under low signal-to-noise ratio[J]. Journal of China Coal Society,40(8):1845–1852 (in Chinese).
    [2]
    Li W,Jiang X L,Chen H B,Jin Z P,Liu Z J,Li X W,Lin J X. 2018. Denosing method of mine microseismic signal based on EEMD_Hankel_SVD[J]. Journal of China Coal Society,43(7):1910–1917 (in Chinese).
    [3]
    Liu H,Zhang J Z. 2014. STA/LTA algorithm analysis and improvement of microseismic signal automatic detection[J]. Progress in Geophysics,29(4):1708–1714 (in Chinese).
    [4]
    Liu X M,Zhao J J,Wang Y M,Peng P A. 2017. Automatic picking of microseismic events P-wave arrivals based on improved method of STA/LTA[J]. Journal of Northeastern University (Natural Science),38(5):740–745 (in Chinese).
    [5]
    Tang G J,Wang X L. 2015. Parameter optimized variational mode decomposition method with application to incipient fault diagnosis of rolling bearing[J]. Journal of Xian Jiaotong University,49(5):73–81 (in Chinese).
    [6]
    Tian Y P,Zhao A H. 2016. Automatic identification of P-phase based on wavelet packet and kurtosis-AIC method[J]. Acta Seismologica Sinica,38(1):71–85 (in Chinese).
    [7]
    Wang Z J,Chang X,Wang J Y,Du W H,Duan N Q,Dang C Y. 2018. Gearbox fault diagnosis based on permutation entropy optimized variational mode decomposition[J]. Transactions of the Chinese Society of Agricultural Engineering,34(23):59–66 (in Chinese).
    [8]
    Zhao D P,Liu X Q,Liu Y X,Wang Z S,Zhao H,Zhang Y L. 2013. Detection of regional seismic events by high order statistics method and automatic identification of direct P-wave first motion by AIC method[J]. Seismological and Geomagnetic Observation and Research,34(5/6):61–69 (in Chinese).
    [9]
    Zheng J D,Cheng J S,Yang Y. 2013. Modified EEMD algorithm and its applications[J]. Journal of Vibration and Shock,32(21):21–26 (in Chinese).
    [10]
    Zheng X X,Zhou G W,Ren H H,Fu Y. 2017. A rolling bearing fault diagnosis method based on variational mode decomposition and permutation entropy[J]. Journal of Vibration and Shock,36(22):22–28 (in Chinese).
    [11]
    Zhu Q J,Jiang F X,Wei Q D,Wang B,Liu J H,Liu X H. 2018. An automatic method determining arrival times of microseismic P-phase in Hydraulic fracturing of coal seam[J]. Chinese Journal of Rock Mechanics and Engineering,37(10):2319–2333 (in Chinese).
    [12]
    Bandt C,Pompe B. 2002. Permutation entropy:A natural complexity measure for time series[J]. Phys Rev Lett,88(17):174102. doi: 10.1103/PhysRevLett.88.174102
    [13]
    Charles M,Ge M C. 2018. Enhancing manual P-phase arrival detection and automatic onset time picking in a noisy microseismic data in underground mines[J]. Int J Min Sci Technol,28(4):691–699. doi: 10.1016/j.ijmst.2017.05.024
    [14]
    Dragomiretskiy K,Zosso D. 2014. Variational mode decomposition[J]. IEEE Trans Signal Proc,62(3):531–544. doi: 10.1109/TSP.2013.2288675
    [15]
    Gaci S. 2014. The use of wavelet-based denoising techniques to enhance the first-arrival picking on seismic traces[J]. IEEE Trans Geosci Remote Sens,52(8):4558–4563. doi: 10.1109/TGRS.2013.2282422
    [16]
    Kirbas I,Peker M. 2017. Signal detection based on empirical mode decomposition and Teager-Kaiser energy operator and its application to P and S wave arrival time detection in seismic signal analysis[J]. Neural Comput Appl,28(10):3035–3045. doi: 10.1007/s00521-016-2333-5
    [17]
    Li F Y,Zhang B,Verma S,Marfurt K J. 2018. Seismic signal denoising using thresholded variational mode decomposition[J]. Explora Geophys,49(4):450–461. doi: 10.1071/EG17004
    [18]
    Li X B,Shang X Y,Wang Z W,Dong L J,Weng L. 2016. Identifying P-phase arrivals with noise:An improved Kurtosis method based on DWT and STA/LTA[J]. J Appl Geophys,133:50–61. doi: 10.1016/j.jappgeo.2016.07.022
    [19]
    Li X B, Shang X Y, Morales-Esteban A, Wang Z W. 2017. Identifying P phase arrival of weak events: The Akaike information criterion picking application based on the empirical mode decomposition[J] Comput Geosci, 100: 57–66.
    [20]
    Liu M Z,Yang J X,Cao Y P,Fu W N,Cao Y L. 2017. A new method for arrival time determination of impact signal based on HHT and AIC[J]. Mech Syst Signal Proc,86:177–187. doi: 10.1016/j.ymssp.2016.10.003
    [21]
    Shang X Y,Li X B,Morales-Esteban A,Dong L J. 2018. Enhancing micro-seismic P-phase arrival picking:EMD-cosine function-based denoising with an application to the AIC picker[J]. J Appl Geophys,150:325–337. doi: 10.1016/j.jappgeo.2017.09.012
    [22]
    Xue Y J,Cao J X,Wang D X,Du H K,Yao Y. 2016. Application of the variational-mode decomposition for seismic time-frequency analysis[J]. IEEE J Select Top Appl Earth Observ Remote Sens,9(8):3821–3831. doi: 10.1109/JSTARS.2016.2529702
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(14)  / Tables(1)

    Article Metrics

    Article views (136) PDF downloads(48) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return