The attenuation of prestack internal multiples based on virtual seismic events is computationally costly and hinders seismic data processing. We propose a multiples attenuation method for poststack seismic data by app...The attenuation of prestack internal multiples based on virtual seismic events is computationally costly and hinders seismic data processing. We propose a multiples attenuation method for poststack seismic data by approximating conventional virtual events. The proposed method is iterative. The proposed method is tested using 2D synthetic and the field poststack seismic datasets. Compared with the conventional virtual events method, the proposed method does not require data regularization and offers higher computation efficiency. The method requires to know the travel time of the primary reflection waves. The results of the application to 2D field datasets suggest that the proposed method attenuates the internal multiples while highlighting the deep primaries.展开更多
基金supported by the National Natural Science Foundation of China(No.41674122)National Science and Technology Major Project of China(No.2016ZX05004003)National Basic Research Program of China(No.2013CB228602)
文摘The attenuation of prestack internal multiples based on virtual seismic events is computationally costly and hinders seismic data processing. We propose a multiples attenuation method for poststack seismic data by approximating conventional virtual events. The proposed method is iterative. The proposed method is tested using 2D synthetic and the field poststack seismic datasets. Compared with the conventional virtual events method, the proposed method does not require data regularization and offers higher computation efficiency. The method requires to know the travel time of the primary reflection waves. The results of the application to 2D field datasets suggest that the proposed method attenuates the internal multiples while highlighting the deep primaries.
基金supported by the Open Fund project of Jiangxi Research Center of Nuclear Geoscience Data Science and Systems Engineering Technology“Research on intelligent recognition method of low-order fault based on V-net deep learning architecture”(JETRCNGDSS202205)“Study on the method of identifying the superior reservoir of tight sandstone based on depth learning”(JETRCNGDSS202103)+1 种基金School-level project of the East China University of Technology“Study on the method of identifying low-order faults with geological big data”(DHBK2019222)the Ministry of Education 2021 the first batch of industry-university collaboration projects(202101185011).