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Structure-Guided Multiscale Impedance Inversion Based on Modified Total Variation Regularization

delete2024-01-01
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PRE
AI
H
Hao Li
Y
Yi-an Cui
P
Pu Wang *
Y
Youjun Guo
Y
Yang Yuan
P
Pengfei Zhang
柳建新 (Jianxin Liu)
DOI:10.1109/TGRS.2024.3491212delete
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Abstract

Abstract

En 中文
Seismic impedance inversion is an effective technique for estimating subsurface rock attributes from poststack data. The inversion efficacy, however, can be compromised by factors such as data noise, initial model, and regularization constraints. Traditional single trace inversion usually exhibits obvious spatial discontinuities due to the absence of geometric constraints on the reconstructed impedances, especially in datasets with high noise levels, while the inversion may easily get trapped in local minima because of a poor initial model. To improve the imaging quality, we develop a structure-guided modified total variation (SGMTV) regularization scheme. This introduces seismic features extracted from seismic data into the modified total variation (MTV) regularization scheme, aiming to simultaneously reconstruct multitrace impedances with enhanced structures and suppressed model noise. Moreover, the SGMTV inversion is integrated with a time-domain multiscale strategy to alleviate its dependence on initial model. Both synthetic and field examples demonstrate the superiority of the multiscale SGMTV inversion compared with the conventional methods. The robust performance establishes it as a reliable tool for seismic imaging and interpretations.
Keywords:
Mathematical models
Impedance
Data models
TV
Noise
Reflection coefficient
Image reconstruction
Convolution
Wavelet transforms
Time-domain analysis
Modified total variation (MTV) regularization
multiscale strategy
multitrace impedance inversion
structure-guided constraints
time domain

Journal

IEEE Transactions on Geoscience and Remote Sensing cover
IEEE Transactions on Geoscience and Remote Sensing
IF:
8.6
Papers:
2.1W
Citations:
10.7W

Organization

M
ministry of education - china
Scholars:
2.5W
Papers: 1.0W
Citations: 13