In this research, we present a seismic trace interpolation method which uses seismic data with surface-related multiples. It is different from conventional seismic data interpolation using information transformation o...In this research, we present a seismic trace interpolation method which uses seismic data with surface-related multiples. It is different from conventional seismic data interpolation using information transformation or extrapolation of adjacent channels for reconstruction of missing seismic data. In this method there are two steps, first, we construct pseudo-primaries by cross-correlation of surface multiple data to extract the missing near- offset information in multiples, which are not displayed in the acquired seismic record. Second, we correct the pseudo-primaries by applying a Least-squares Matching Filter （LMF） and RMS amplitude correction method in time and space sliding windows. Then the corrected pseudo-primaries can be used to fill the data gaps. The method is easy to implement, without the need to separate multiples and primaries. It extracts the seismic information contained by multiples for filling missing traces. The method is suitable for seismic data with surfacerelated multiples.展开更多
基金sponsored by:the National Basic Research Program of China (973 Program) (2007CB209605)the National Natural Science Foundation of China (40974073)the National Hi-tech Research and Development Program of China (863 Program) (2009AA06Z206)
文摘In this research, we present a seismic trace interpolation method which uses seismic data with surface-related multiples. It is different from conventional seismic data interpolation using information transformation or extrapolation of adjacent channels for reconstruction of missing seismic data. In this method there are two steps, first, we construct pseudo-primaries by cross-correlation of surface multiple data to extract the missing near- offset information in multiples, which are not displayed in the acquired seismic record. Second, we correct the pseudo-primaries by applying a Least-squares Matching Filter （LMF） and RMS amplitude correction method in time and space sliding windows. Then the corrected pseudo-primaries can be used to fill the data gaps. The method is easy to implement, without the need to separate multiples and primaries. It extracts the seismic information contained by multiples for filling missing traces. The method is suitable for seismic data with surfacerelated multiples.
