论文详情
It is difficult to accurately pick the first arrival of a seismic wave.In the mountainous areas of western China,this might be due to the great topographic relief,the weak energy,and the low signal-to-noise ratio (SNR) of the seismic data.Based on the principle of the stationary phase stack,the super-virtual refraction interferometry can effectively enhance weak signals and simplify the pickup of the first arrival.In this study,with the aim of addressing the problem of inconsistent amplitude caused by the uneven stack of the super-virtual refraction interferometry,the cross-correlation and the convolution-type of interferometry are combined into a blend-type interferometry to ensure the consistency of the number of stacks.Subsequently,in order to further increase the stack number of the first arrival of the virtual refracted wave,it is proposed to stack jointly in both source and receiver domains.Moreover,to address the problem of wavelet sidelobe,which is generated by cross-correlation or convolution,a deconvolution is introduced,so that the influence of the wavelet sidelobe can be reduced and the energy loss for the far offset data can be compensated.Finally,the technical process of signal enhancement based on the super-virtual refraction interferometry in first arrival identification is utilized to solve field data.This technical process is suitable for industrial application.Tests on both model and field data showed that the method can effectively enhance the low-energy first arrival of far-field data,so that the first arrival can be identified with high precision,the SNR of the seismic data can be improved,and high-quality input data can be provided for subsequent processing,such as static correction.
国家科技重大专项(2016ZX05004003)、国家自然科学基金(41674122)和国家重点基础研究发展(973)计划(2013CB228602)共同资助。