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被动源地震数据包含丰富的低频信息,本文有效地提取并利用这些信息对缺失低频的主动源地震数据进行低频重构,提出了基于多正弦窗的被动源多窗谱重构方法,并给出了相应的多震源多道重构公式。与常规互相关法和常规反褶积法重构的被动源记录相比,该方法能重构出更为准确的相对振幅信息。通过分析被动源数据重构前后的频谱特性,发现被动源的低频特性在重构和去噪处理后能更明显的体现出来。并提出了一种用被动源数据重构主动源低频信息的方法,即在功率谱上进行匹配,并在频域进行补偿和平滑。最后进行了数值算例的验证,对低频重构后的数据进行了叠前深度偏移处理。能量匹配方法能够用被动源的低频信息有效地重构主动源缺失的低频信息,低频重构后的记录在偏移成像中能体现更多的细节信息和深部构造。
Passive source seismic data contains abundant low-frequency information. In this paper, this information is effectively extracted and used to reconstruct low-frequency active source seismic data with low frequency. A multi-pass window reconstruction method based on multi-sine window is proposed. The corresponding multi-source multi-channel reconstruction formula. Compared with the conventional cross-correlation and conventional deconvolution reconstruction of passive source records, this method can reconstruct more accurate relative amplitude information. By analyzing the spectral characteristics before and after reconstruction of passive data, it is found that the low frequency characteristic of passive source can be more obvious after reconstructing and denoising. A method to reconstruct the low-frequency information of the active source using passive source data is proposed, that is, matching is performed on the power spectrum and compensated and smoothed in the frequency domain. Finally, numerical examples are given to validate the pre-stack depth migration of the reconstructed data. The energy matching method can effectively reconstruct the low frequency information missing from the active source with the low frequency information of the passive source. The low frequency reconstructed recording can show more detail information and deep structure in the migration imaging.