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Structure-oriented prestack waveform inversion

delete2022-03-03
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PRE
AI
J
Jian Zhang *
X
Xiaoyan Zhao
J
Jingye Li
X
Xiaohong Chen
DOI:10.1190/geo2021-0452.1delete
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摘要

摘要

En 中文
The prediction of elastic parameters (i.e., P-, S-wave velocity, and density) is one of the key tasks of seismic reservoir characterization. The amplitude-variation-with-offset/angle seismic inversion based on the exact Zoeppritz equation (EZE) or its approximations presupposes a single interface and ignores wave-propagation effects, resulting in low accuracy inversion results. The analytical solution of the 1D wave equation (i.e., the reflectivity method [RM]) can simulate more of the totality of wave-propagation effects, including transmission losses and internal multiples, thus improving the accuracy of the inversion results. However, the RM-based inversion method is sensitive to noise and is usually performed trace-by-trace. When trace by-trace-based inversion results are combined into a 2D profile, the lateral continuity of the final results is poor, which affects the subsequent interpretation and evaluation. To address these issues, the RM-based structure-oriented prestack waveform inversion (SORM) method is proposed to suppress the effects of data noise and improve the geologic reliability of the inversion results. This method adds an additional structure-oriented constraint term to the objective function, which facilitates the integration of the structural orientation into the inversion algorithm in the form of dips. We carry out the method on a synthetic model as well as on a field data set. A series of numerical tests indicate that the SORM gives significantly more accurate and geologically reliable results compared with inversion based on EZE or trace-by trace RM.
Keyword:
REFLECTIVITY METHOD
AMPLITUDE-VARIATION
SYNTHETIC SEISMOGRAMS
PARAMETER-ESTIMATION
AVO INVERSION
CASE-HISTORY
INFORMATION
COMPUTATION
OFFSET
GAS

期刊

Geophysics 封面图
Geophysics
IF:
3.2
论文数:
8.4K
被引数:
3.3W

机构

S
Southwest Jiaotong University
学者数:
2.9W
论文数: 2.1W
被引数: 2.3W
C
china university of petroleum
学者数:
4.1W
论文数: 2.7W
被引数: 30
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