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
  • [31] Time-domain estimation of time-varying linear systems
    Chiann, C
    Morettin, PA
    JOURNAL OF NONPARAMETRIC STATISTICS, 2005, 17 (03) : 365 - 383
  • [32] Time-frequency ridge estimation: An effective tool for gear and bearing fault diagnosis at time-varying speeds
    Li, Yifan
    Zhang, Xin
    Chen, Zaigang
    Yang, Yaocheng
    Geng, Changqing
    Zuo, Ming J.
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2023, 189
  • [33] Estimation of multiple, time-varying motions using time-frequency representations and moving-objects segmentation
    Alexiadis, Dimitrios S.
    Sergiadis, George D.
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2008, 17 (06) : 982 - 990
  • [34] Time-frequency analysis for bearing fault diagnosis using multiple Q-factor Gabor wavelets
    Zhang, Xin
    Liu, Zhiwen
    Wang, Jiaxu
    Wang, Jinglin
    ISA TRANSACTIONS, 2019, 87 : 225 - 234
  • [35] Nonparametric estimation of the time-varying frequency and amplitude
    Katkovnik, V
    STATISTICS & PROBABILITY LETTERS, 1997, 35 (04) : 307 - 315
  • [36] CANONICAL TIME-FREQUENCY, TIME-SCALE, AND FREQUENCY-SCALE REPRESENTATIONS OF TIME-VARYING CHANNELS
    Rickard, Scott T.
    Balan, Radu V.
    Poor, H. Vincent
    Verdu, Sergio
    COMMUNICATIONS IN INFORMATION AND SYSTEMS, 2005, 5 (02) : 197 - 226
  • [37] A time-varying prony method for instantaneous frequency estimation at low SNR
    Beex, AAL
    Shan, PJ
    ISCAS '99: PROCEEDINGS OF THE 1999 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOL 3: ANALOG AND DIGITAL SIGNAL PROCESSING, 1999, : 5 - 8
  • [38] Time-varying prony method for instantaneous frequency estimation at low SNR
    Beex, A.A.
    Shan, Peijun
    Proceedings - IEEE International Symposium on Circuits and Systems, 1999, 3
  • [39] Time-frequency ridge fusion method and defective identification of planetary gearbox running on time-varying condition
    Jiang X.-X.
    Li S.-M.
    Zhou D.-W.
    Chen Y.-F.
    Shi J.-J.
    Zhendong Gongcheng Xuebao/Journal of Vibration Engineering, 2017, 30 (01): : 127 - 134
  • [40] On time-varying factor models: Estimation and testing
    Su, Liangjun
    Wang, Xia
    JOURNAL OF ECONOMETRICS, 2017, 198 (01) : 84 - 101