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分数阶S变换(FRST)具有较强的时频聚集性。利用FRST处理地震数据,通过合适的分数阶参数将频率轴旋转到适当位置,即可实现目标地质特征信息的最佳识别。由于不同的地震信号的最优分数阶参数可能不同,因而对整体的分数阶参数的最优估计不利于对多道地震数据的处理。本文首先利用FRST分离出共频率数据体,并利用共频率数据体进行了低频伴影分析,然后提出FRST和盲分离结合的方法,不需要对地震数据的最优分数阶参数进行估计,即可提取识别有效地质特征信息的独立频谱,提高对地震数据的解释效率。仿真实验表明在分数阶时频域内此方法能有效分离出独立的频率信息。将该方法用于实际的地震数据,并与已知井信息进行比对,验证了其有效性。
Fractional-order S transform (FRST) has strong time-frequency clustering. By using FRST to process seismic data and rotating the frequency axis to the appropriate position with appropriate fractional order parameters, the best identification of the target geological feature information can be achieved. Because the optimal fractional parameters of different seismic signals may be different, the optimal estimation of the overall fractional parameters is not conducive to the processing of multi-channel seismic data. In this paper, the FRST is used to separate the common frequency data body and the low frequency companion analysis by using the common frequency data body. Then, a combination of FRST and blind separation is proposed, which does not need to estimate the optimal fractional parameters of seismic data Extract the independent spectrum that identifies the effective geological features and improve the efficiency of interpretation of seismic data. Simulation results show that this method can effectively separate the independent frequency information in fractional frequency domain. The method is applied to the actual seismic data and compared with the known well information to verify its effectiveness.