Multiple Matching Attenuation Based on Curvelet Domain Extended Filtering

The paper develops a multiple matching attenuation method based on extended filtering in the curvelet domain, which combines the traditional Wiener filtering method with the matching attenuation method in curvelet domain. Firstly, the method uses the predicted multiple data to generate the Hilbert transform records, time derivative records and time derivative records of Hilbert transform. Then, the above records are transformed into the curvelet domain and multiple matching attenuation based on least squares extended filtering is performed. Finally, the attenuation results are transformed back into the time-space domain. Tests on the model data and field data show that the method proposed in the paper effectively suppress the multiples while preserving the primaries well. Furthermore, it has higher accuracy in eliminating multiple reflections, which is more suitable for the multiple attenuation tasks in the areas with complex structures compared to the time-space domain extended filtering method and the conventional curvelet transform method.