In seismic exploration, multiples pose significant challenges, particularly in marine exploration. This study developed a method for suppressing interbed multiples based on the inverse scattering series(ISS) method in...In seismic exploration, multiples pose significant challenges, particularly in marine exploration. This study developed a method for suppressing interbed multiples based on the inverse scattering series(ISS) method in the curvelet domain. The curvelet transform(CT), as a multi-scale and multi-directional transformation method, can sparsely represent seismic data, facilitating the capture of the main features of seismic data. By combining CT with the ISS method, the seismic data was first converted to the curvelet domain using CT. Then, the interbed multiples were predicted in the curvelet domain through the ISS method. This approach did not require building a model of the subsurface medium, offering high applicability and practicality. Furthermore, CT can sparsely represent seismic data, reducing the computational load of the ISS method. By performing an inverse CT on the predicted multiples, they were reconstructed in the time-space domain and subtracted from the original seismic data, and ultimately the effective signal with suppressed multiples was obtained. The numerical experiments demonstrate that this method not only significantly improves computational efficiency but also reduces memory consumption while ensuring accuracy. This study provides an innovative approach for multiples suppression in seismic data processing and is expected to play an important role in practical seismic exploration.展开更多
文摘In seismic exploration, multiples pose significant challenges, particularly in marine exploration. This study developed a method for suppressing interbed multiples based on the inverse scattering series(ISS) method in the curvelet domain. The curvelet transform(CT), as a multi-scale and multi-directional transformation method, can sparsely represent seismic data, facilitating the capture of the main features of seismic data. By combining CT with the ISS method, the seismic data was first converted to the curvelet domain using CT. Then, the interbed multiples were predicted in the curvelet domain through the ISS method. This approach did not require building a model of the subsurface medium, offering high applicability and practicality. Furthermore, CT can sparsely represent seismic data, reducing the computational load of the ISS method. By performing an inverse CT on the predicted multiples, they were reconstructed in the time-space domain and subtracted from the original seismic data, and ultimately the effective signal with suppressed multiples was obtained. The numerical experiments demonstrate that this method not only significantly improves computational efficiency but also reduces memory consumption while ensuring accuracy. This study provides an innovative approach for multiples suppression in seismic data processing and is expected to play an important role in practical seismic exploration.
