Application of LCSSI method in elastic impedance inversion based on orthogonal matching pursuit algorithm
- Guang Chen (China University of Petroleum–Beijing) | Hui Zhou (China University of Petroleum–Beijing) | Mingdi Liu (China University of Petroleum–Beijing) | Yonghui Tao (China University of Petroleum–Beijing) | Haiyang Wang (China University of Petroleum–Beijing)
- Document ID
- Society of Exploration Geophysicists
- 2016 SEG International Exposition and Annual Meeting, 16-21 October, Dallas, Texas
- Publication Date
- Document Type
- Conference Paper
- 2016. Society of Exploration Geophysicists
- Prestack, Common angle, Algorithm, Inversion, AVO/AVA
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- 15 since 2007
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Elastic impedance inversion is an important prestack inversion method in reservoir prediction and fluid identification. Constrained sparse spike inversion (CSSI) used to be the most widely used method in poststack seismic inversion. Because of the relationship between the elastic impedance and the wave impedance, the CSSI can be directly applied to the prestack elastic impedance inversion. However, CSSI usually suffers from strongly ill-posed problem when using some local optimization algorithm, such as conjugate gradient (CG) method, and has a strong dependence on the initial model of reflection coefficient. Besides, conventional CSSI separately inverts the time locations and amplitudes of sparse-spikes, which increases the computational complexity. In this paper, we improve CSSI theory with a linear wave impedance constraint, which is named as LCSSI. We apply orthogonal matching pursuit (OMP) non-linear algorithm to linear constrained sparse spike prestack elastic impedance inversion. We derive a linear matrix equation from the cost function and use OMP algorithm to invert the sparse-spikes' time locations and amplitudes simultaneously. Due to OMP, this method can reduce dependence on initial model and obtain the inversion results precisely and quickly. Numerical examples indicate that our method can achieve a good performance even for noisy data, while the CG algorithm fails to get a desirable inversion result.
Presentation Date: Wednesday, October 19, 2016
Start Time: 8:00:00 AM
Presentation Type: ORAL
|File Size||1 MB||Number of Pages||5|
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