基于相对熵的时差相位差自动识别校正方法

针对地震资料处理中存在的时差、相位差问题,提出了一种时差、相位差自动识别校正方法.该方法以希尔伯特变换和相对熵算法为理论基础,以KL散度为判别准则,全过程数据驱动,自动化实现时差、相位差的识别与校正,有效降低人工识别成本,避免人为因素带来的误差.文中详细阐述了相关原理及实施过程,并通过数值模拟结果验证了该方法的正确性和...

Timelag and phaselag automatic recognition and correction method based on relative entropy

Aiming at the problem of timelag and phaselag in the processing of seismic data,an automatic recognition and correction(ARC)method is proposed.The method is based on Hilbert transform and relative entropy algorithm.Kullback-Leibler divergence is used as the criterion.The whole process is data driven,and the recognition and correction of timelag and phaselag are realized automatically,which effectively reduces the cost of artificial identification and avoids errors caused by human factors.In this paper,the related principles and implementation process are expounded in detail,and the correctness and effectiveness of the method are verified by numerical simulation results.The application analysis of merged and multi-component actual seismic data shows that compared with manual identification and theoretical value correction,this method can effectively improve the accuracy of recognition and correction,enhance the consistency of events,improve the quality of the sections,and provide technical support for subsequent processing and interpretation.