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Prediction of sweet spots in tight sandstone reservoirs based on anisotropic frequency-dependent AVO inversion.
- Source :
- Journal of Geophysics & Engineering; Oct2021, Vol. 18 Issue 5, p664-680, 17p
- Publication Year :
- 2021
-
Abstract
- The frequency-dependent amplitude-versus-offset (FAVO) method has become a practical method for fluid detection in sand reservoirs. At present, most FAVO inversions are based on the assumption that reservoirs are isotropy, but the application effect is not satisfactory for fractured reservoirs. Hence, we analyse the frequency variation characteristics of anisotropy parameters in tight sandstone reservoirs based on a new petrophysical model, and propose a stepwise anisotropic FAVO inversion method to extract frequency-dependent attributes from prestack seismic field data. First, we combine the improved Brie's law with the fine-fracture model to analyse frequency-dependent characteristics of velocities and Thomsen anisotropy parameters at different gas saturations and fracture densities. Then, we derive an anisotropic FAVO inversion algorithm based on Rüger's approximation formula and propose a stepwise anisotropic FAVO inversion method to obtain the dispersions of anisotropy parameters. Finally, we propose a method that combines the inversion spectral decomposition with the stepwise anisotropy FAVO inversion and apply it to tight sand reservoirs in the Xinchang area. We use P-wave velocity dispersion and anisotropy parameter ε dispersion to optimise favourable areas. Numerical analysis results show that velocity dispersion of the P-wave is sensitive to fracture density, which can be used for fracture prediction in fractured reservoirs. In contrast, anisotropic parameter dispersion is sensitive to gas saturation and can be used for fluid detection. The seismic data inversion results show that velocity dispersion of the P-wave and anisotropic parameter dispersion are sensitive to fractured reservoirs in the second member of Xujiahe Group, which is consistent with logging interpretation results. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 17422132
- Volume :
- 18
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- Journal of Geophysics & Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 157146380
- Full Text :
- https://doi.org/10.1093/jge/gxab044