Continuous time-varying Q-factor estimation method in the time-frequency domain

被引:0
|
作者
Qing-Han Wang
Yang Liu
Cai Liu
Zhi-Sheng Zheng
机构
[1] Jilin University,College of Geo
来源
Applied Geophysics | 2020年 / 17卷
关键词
local centroid frequency; local time-frequency transform; -factor estimation; shaping regularization;
D O I
暂无
中图分类号
学科分类号
摘要
The Q-factor is an important physical parameter for characterizing the absorption and attenuation of seismic waves propagating in underground media, which is of great significance for improving the resolution of seismic data, oil and gas detection, and reservoir description. In this paper, the local centroid frequency is defined using shaping regularization and used to estimate the Q values of the formation. We propose a continuous time-varying Q-estimation method in the time-frequency domain according to the local centroid frequency, namely, the local centroid frequency shift (LCFS) method. This method can reasonably reduce the calculation error caused by the low accuracy of the time picking of the target formation in the traditional methods. The theoretical and real seismic data processing results show that the time-varying Q values can be accurately estimated using the LCFS method. Compared with the traditional Q-estimation methods, this method does not need to extract the top and bottom interfaces of the target formation; it can also obtain relatively reasonable Q values when there is no effective frequency spectrum information. Simultaneously, a reasonable inverse Q. filtering result can be obtained using the continuous time-varying Q values.
引用
收藏
页码:844 / 856
页数:12
相关论文
共 50 条
  • [21] A combined time-frequency filtering strategy for Q-factor compensation of poststack seismic data
    Lupinacci, Wagner Moreira
    de Franco, Allan Peixoto
    Moura Oliveira, Sergio Adriano
    de Moraes, Fernando Sergio
    GEOPHYSICS, 2017, 82 (01) : V1 - V6
  • [22] A time-frequency feature prediction network for time-varying radio frequency interference
    Wan, Pengcheng
    Feng, Weike
    Tong, Ningning
    Wei, Wei
    Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University, 2023, 41 (03): : 587 - 594
  • [23] Maximum likelihood estimator of operational modal analysis for linear time-varying structures in time-frequency domain
    Zhou, Si-Da
    Heylen, Ward
    Sas, Paul
    Liu, Li
    JOURNAL OF SOUND AND VIBRATION, 2014, 333 (11) : 2339 - 2358
  • [24] Time-frequency sweeping scheme assessment method for time-varying multiple emitters tracking task
    Yang Y.
    Cao X.
    Shi X.
    Yu C.
    Zhang W.
    Zhang T.
    Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2024, 46 (01): : 219 - 226
  • [25] Bayesian Lattice Filters for Time-Varying Autoregression and Time-Frequency Analysis
    Yang, Wen-Hsi
    Holan, Scott H.
    Wikle, Christopher K.
    BAYESIAN ANALYSIS, 2016, 11 (04): : 977 - 1003
  • [26] Analysis and classification of time-varying signals with multiple time-frequency structures
    Papandreou-Suppappola, A
    Suppappola, SB
    IEEE SIGNAL PROCESSING LETTERS, 2002, 9 (03) : 92 - 95
  • [27] Time-frequency analysis of time-varying spectra with application to rotorcraft testing
    Conn, T
    Hamilton, J
    IEEE ANTENNAS AND PROPAGATION MAGAZINE, 2005, 47 (02) : 148 - 153
  • [28] Robust time-varying Wiener filters: Theory and time-frequency formulation
    Matz, G
    Hlawatsch, F
    PROCEEDINGS OF THE IEEE-SP INTERNATIONAL SYMPOSIUM ON TIME-FREQUENCY AND TIME-SCALE ANALYSIS, 1998, : 401 - 404
  • [29] Adaptive time-frequency analysis based on time-varying parameters model
    Liu, Shuai
    Zhou, HongJuan
    Jin, Ming
    Qiao, XiaoLin
    2006 8TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, VOLS 1-4, 2006, : 283 - +
  • [30] Discrete time-frequency characterizations of dispersive linear time-varying systems
    Jiang, Ye
    Papandreou-Suppappola, Antonia
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2007, 55 (05) : 2066 - 2076