Q-Factor Estimation via Convolutional Seismic Modeling

Leandro R. S. Farias, Tales V. R. O. Câmara, Luiz F. Q. Silveira, Kenji Nose Filho, Tiago Barros

DOI: 10.14209/sbrt.2025.1571144698

Evento: XLIII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2025)

Keywords:

Abstract

This work proposes a method for estimating the Q-factor from surface reflection data by formulating an inverse problem based on the convolutional model. The approach is flexible, allowing easy substitution of different attenuation models within the same framework. The Q-factor is estimated by minimizing a mean square error cost function using gradient descent. Additionally, we investigate the impact of model mismatch by generating data with one attenuation model and inverting it using another. This highlights the importance of model choice in Q-estimation and supports the method's potential integration into seismic processing workflows.

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