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Multi-threshold Wavelet Packet-Based Method to Attenuate Noise from Seismic Signal

Published: 28 March 2018 Publication History

Abstract

Seismic data often contains different types of noise, and eliminating noise is one of the most important issues in seismic data processing. Noise on seismic data has influence on decline of SNR (signal to noise ratio) and resolution ratio of seismic data. Because of the reasons above, it is difficult to accurately obtain the geological structure by analyzing seismic signal. In view of limitation of selecting threshold value in the traditional wavelet analysis method, this paper proposes the multi-threshold wavelet packet method based on the frequency sequence. Through theoretical analysis and simulation of seismic signal, the de-noising processing is realized by using the multi-threshold wavelet packet de-noising method, the results show that the method can effectively filter out seismic noise and reserve the useful signal with the middle and high frequency. So the capability of noise reduction is superior to other traditional methods, which can effectively improve the resolution ratio of the seismic signal and establish the foundation for later inversion of geological structure.

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Cited By

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  • (2023)Microseismic signal denoising using simple bandpass filtering based on normal time–frequency transformActa Geophysica10.1007/s11600-022-01012-171:5(2217-2232)Online publication date: 10-Feb-2023
  • (2022)A Novel Drinking Category Detection Method Based on Wireless Signals and Artificial Neural NetworkEntropy10.3390/e2411170024:11(1700)Online publication date: 21-Nov-2022
  • (2022)Using the Features Extracted From the Ambient Noise Cross-Correlation Function to Evaluate the Performance of Broadband SeismographIEEE Access10.1109/ACCESS.2022.322892910(130224-130232)Online publication date: 2022

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  1. Multi-threshold Wavelet Packet-Based Method to Attenuate Noise from Seismic Signal

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    cover image ACM Other conferences
    IEEA '18: Proceedings of the 7th International Conference on Informatics, Environment, Energy and Applications
    March 2018
    256 pages
    ISBN:9781450363624
    DOI:10.1145/3208854
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • Shanghai Jiao Tong University: Shanghai Jiao Tong University
    • University of Wollongong, Australia

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 28 March 2018

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    Author Tags

    1. Seismic data
    2. frequency sequence
    3. multi-threshold

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    • Refereed limited

    Funding Sources

    • fund of national engineering laboratory of local engineering and disaster prevention and reduction technology in mountain area. & T application development projects in Chongqing

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    IEEA '18

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    Cited By

    View all
    • (2023)Microseismic signal denoising using simple bandpass filtering based on normal time–frequency transformActa Geophysica10.1007/s11600-022-01012-171:5(2217-2232)Online publication date: 10-Feb-2023
    • (2022)A Novel Drinking Category Detection Method Based on Wireless Signals and Artificial Neural NetworkEntropy10.3390/e2411170024:11(1700)Online publication date: 21-Nov-2022
    • (2022)Using the Features Extracted From the Ambient Noise Cross-Correlation Function to Evaluate the Performance of Broadband SeismographIEEE Access10.1109/ACCESS.2022.322892910(130224-130232)Online publication date: 2022

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