Time-Arrival Location of Seismic P-Wave Based on Wavelet Transform

Abstract:

The automatic pick of seismic first arrivals is a foundational problem in Seismic Exploration. Picking the first arrival of P-wave is an important problem in the seismic research field. The modulus maxima of wavelet transform is a useful method for picking up the singularities of function. For applying the modulus maxima method to investigate the arrival time of P-wave, it is necessary to eliminate the influence of random factors. Based on standard deviation, we present a method to reduce the influence of random factors. Then we get an approach to detect the arrival time of P-wave by means of window energy ratio factors. The results of data analysis indicate that our method is more effective.

• Periodical: Advanced Materials Research (Volume 722)
• Pages: 239-243
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.722.239
• Online since: July 2013
• Authors: Xiao Hong Liu
• Keywords: Maximal Overlap Discrete Wavelet Transform, Modulus Maxima Value, Seismic P-Wave, Window Energy Ratio

References

[1] Gilbert Strang, Truong Nguyen: Wavelets and filter banks, Wellesley College. 9(3), 78-86 (1996)

[2] Zheng Qing-qing: Singularity Detection via Wavelet Transform Modulus Maxima. Remote Sensing Information. 9(3), 1000-1002 (2008)

[3] Mallat S, Hwang W L: Singularity detection and processing with wavelets. IEEE Transactions on Information Theory. 32(2), 6l7-643 (1992)

DOI: 10.1109/18.119727

[4] Wang Jingzhong, Xu Tianling, Yuan Kaiguo: Audio digital watermarking algorithm based on energy ratio of wavelet coefficient. Computer Applications and Software. 6(2), 2-8 (2011)

[5] Xu Jiandong, Huang Jianfa, Wei Fuquan: Correlation Fractal and Multifractal Characteristics of Seismic Activity in the Taiwan Area. 79(2), 14-20 (2005).

DOI: 10.1111/j.1755-6724.2005.tb00885.x

[6] Boschetti F, Dentith M D, List R D: A fractal-based algorithm for detecting first arrivals on seismic traces. Geophysics. 61(4), 1095-1102 (1993)

DOI: 10.1190/1.1444030

[7] panakkat Ashif, adeli Hojjat: Recurrent Neural Network for Approximate Earthquake Time and Location Prediction Using Multiple Seismicity Indicators. Computer-Aided Civil and Infrastructure Engineering Volume:24,Issue Number: 4,Publisher: Blackwell Publishing, 4(6), 1093-9687 (2009)

DOI: 10.1111/j.1467-8667.2009.00595.x

[8] Wu Jing-Jin Chen Wei: (Nanchang University, Nanchang 330029); Edge Detection Based on Multi-scale Lifting Wavelet; Journal of Chongqing University of Science and Technology (Natural Sciences Edition). 1(4), 90-99 (2009)

[9] Donald B. Percival, Andrew T. Walden: Wavelet methods for time series analysis. Cambridge University Press. 8(5), 23-29 (2000)