Deblending massive OBN data acquired by efficient and blended shooting method
CHEN Yingpeng1, ZHANG Hongjun1, LIU Yong1, ZHAO Min1, SONG Jiawen2, QI Qunli1
1. Overseas Business Department, GRI, BGP Inc., CNPC, Zhuozhou, Hebei 072750, China; 2. Research & Development Center, BGP Inc., CNPC, Zhuozhou, Hebei 072750, China
Abstract：Compared with land blended data with simple noises, OBN blended data have many types of noises due to the special method of OBN acquisition. Two primary causes for the multiple types of noises are heavy overlapped shots on the logical coordinate system and severe geometry deformation. After analyzing the types of noises in OBN data, we studied iterative dynamic mapping, pre-processing of logical shot coordinates and sparse inversion deblending technology. The sparse inversion deblending method is based on FKK. It globally maps the logical positions of all overlapped shots in a dynamic and iterative way to recongnize noises, and then it accurately and quickly deblends the massive seismic data severely blended. The application in Block A shows that the deblended OBN data are of high fidelity, indicating that the method can provide optimal results while improving deblending efficientcy.
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