Concurrent estimation of seismic reflectivity and Q by using an optimal dictionary learning method Article Swipe
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· 2023
· Open Access
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· DOI: https://doi.org/10.3389/feart.2023.1121956
The seismic reflectivity and quality factor Q play an important role in seismic processing and interpretation, such as improving the resolution of seismic data and enhancing the reservoir identification. Most methods estimate seismic reflectivity and Q separately. However, the error of Q model has a negative impact on the reflectivity estimation and the interference of reflectivity makes Q estimates less reliable. In this paper, we propose a new method for concurrent estimation of seismic reflectivity and Q by using optimal dictionary learning. This new method first constructs a complete dictionary based on the non-stationary convolution model, then computes the reflectivity series under different dictionary matrices with the corresponding referencing Q values, and finally selects the optimal dictionary matrix by comprehensively analyzing the residual and reflectivity sparsity so as to obtain seismic reflectivity and Q simultaneously. The results of synthetic and real data examples test confirm the effectiveness of the proposed method. The proposed method provides accurate estimation of seismic reflectivity and Q , improves the vertical resolution without losing weak events and offers more accurate information concerning stratigraphic features in great details.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/feart.2023.1121956
- https://www.frontiersin.org/articles/10.3389/feart.2023.1121956/pdf
- OA Status
- gold
- References
- 36
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4317387948