Technology and application of internal multiple suppression for seismic data based on source layer
The development of low-speed coal seam will form internal multiples with strong energy,which makes primaries in seismic data submerged and difficult to identify,resulting in the low accuracy of seismic imaging,which seriously affects the subsequent seismic interpretation.In view of the above problem of internal multiple suppression,this paper develops and forms an internal multiple suppression technology based on source layer according to the characteristics of the energy and frequency of field data in the work area,and carries out application research in Huaizhong area.In response to the multiple characteristics in the research area,the Radon transform was first used in the early processing stage to suppress the multiples in the pre-stack data.However,due to significant differences in the energy and frequency of multiples in the lateral direction,it is difficult to completely suppress these internal multiples in pre-stack data.Therefore,there are still strong multiples on the post-stack profile,and appropriate multiple suppression methods need to be selected before suppression.The results of model synthesis data and filed data application show that the method and technology proposed in this paper.In field data processing,first of all,we analyze the source layer generated by internal multiples.Then,we extract the virtual events of the primaries generated by this source layer.Next,we construct the relevant virtual events and internal multiples with the primaries generated below the source layer.Fininally,we use adaptive matching subtraction for multiples suppression.The proposed approach can effectively suppress internal multiples between model data and field data,while also effectively protect primaries.And the correctness of the proposed method is verified.Moreover,the structural characteristics of the field data profile after internal multiples suppression are more in line with sedimentary laws,and the lateral differences in multiples energy and frequency are reduced,providing reliable data for subsequent hydrocarbon source rock prediction.
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