TY - JOUR
T1 - Inversion-driven attenuation compensation using synchrosqueezing transform
AU - Zhang, Guowei
AU - Gao, Jinghuai
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/1
Y1 - 2018/1
N2 - Attenuation is a fundamental mechanism as seismic wave propagates through the earth. The loss of high-frequency energy and concomitant phase distortion can be compensated by inverse Q filtering to enhance the resolution of seismic data. Since the attenuation process depends on time and frequency, it is routinely performed in the time-frequency domain. The synchrosqueezing transform (SST), which provides highly localized time-frequency representations for the nonstationary signals due to reduced spectral smearing, is applied to implement the inverse Q filtering scheme. However, the amplitude compensation process is unstable because energy amplification is involved. To stabilize it, the amplitude compensation is regarded as an inverse problem with an L1-norm regularization term in the SST domain. The iteratively reweighted least-squares algorithm is used to solve the regularized inverse problem. Synthetic and real data examples illustrate the stability and effectiveness of the proposed method.
AB - Attenuation is a fundamental mechanism as seismic wave propagates through the earth. The loss of high-frequency energy and concomitant phase distortion can be compensated by inverse Q filtering to enhance the resolution of seismic data. Since the attenuation process depends on time and frequency, it is routinely performed in the time-frequency domain. The synchrosqueezing transform (SST), which provides highly localized time-frequency representations for the nonstationary signals due to reduced spectral smearing, is applied to implement the inverse Q filtering scheme. However, the amplitude compensation process is unstable because energy amplification is involved. To stabilize it, the amplitude compensation is regarded as an inverse problem with an L1-norm regularization term in the SST domain. The iteratively reweighted least-squares algorithm is used to solve the regularized inverse problem. Synthetic and real data examples illustrate the stability and effectiveness of the proposed method.
KW - Attenuation compensation
KW - Inversion
KW - L1-norm regularization
KW - Synchrosqueezing transform (SST)
UR - https://www.scopus.com/pages/publications/85039796839
U2 - 10.1109/LGRS.2017.2777598
DO - 10.1109/LGRS.2017.2777598
M3 - 文章
AN - SCOPUS:85039796839
SN - 1545-598X
VL - 15
SP - 132
EP - 136
JO - IEEE Geoscience and Remote Sensing Letters
JF - IEEE Geoscience and Remote Sensing Letters
IS - 1
ER -