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Frequency-Dependent AVO Inversion Using a Modified Window-Parameter-Optimized S-Transform for High Gas-Saturation Reservoir Delineation.

Authors :
Luo, Xin
Chen, Xuehua
Lv, Bingnan
Liu, Junjie
Wu, Haojie
Wang, Peng
Source :
IEEE Geoscience & Remote Sensing Letters; 2023, Vol. 20, p1-5, 5p
Publication Year :
2023

Abstract

The dispersion induced by fluid flow is a useful characteristic of hydrocarbon reservoirs and can be deduced from frequency-dependent amplitude versus offset (FAVO) inversion. However, FAVO inversion strongly depends on the spectral decomposition method, which directly affects the resolution of inversion results. In this letter, we propose a new time–frequency analysis method, named modified window-parameter-optimized S-transform (MWPOST), for improving the resolution of FAVO inversion. In MWPOST, the optimized scale parameter of the window function can be adaptively obtained according to the amplitude spectra of actual signals. Synthetic signal analysis indicates that the method has excellent performance with higher time–frequency resolution. Then, we present a high-precision FAVO inversion method using MWPOST for high gas-saturation reservoir delineation. The field seismic data application illustrates that the dispersion factor inverted by the proposed method has a higher time resolution and exhibits better performance for delineating the reservoir boundary with high gas saturation. The proposed method can improve the precision of FAVO and it is feasible to detect the location and spatial distribution of high gas-saturation reservoirs. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1545598X
Volume :
20
Database :
Complementary Index
Journal :
IEEE Geoscience & Remote Sensing Letters
Publication Type :
Academic Journal
Accession number :
176253170
Full Text :
https://doi.org/10.1109/LGRS.2023.3243846