摘要
Multiple wave is one of the important factors affecting the signal-to-noise ratio of marine seismic data.The model-driven-method(MDM)can effectively predict and suppress water-related multiple waves,while the quality of the multiple wave contribution gathers(MCG)can affect the prediction accuracy of multiple waves.Based on the compressed sensing framework,this study used the sparse constraint under LO norm to optimize MCG,which can not only reduce the false in the prediction and improve the image accuracy,but also saves computing time.At the same time,the MDM-type method for multiple wave suppression can be improved.The unified prediction of multiple types of water-related multiple waves weakens the dependence of conventional MDM on the adaptive subtraction process in suppressing water-related multiple waves,improves the stability of the method,and simultaneously,reduces the computational load.Finally,both theoretical model and practical data prove the effectiveness of the present method.
水体相关多次波是海上地震数据处理主要的噪声来源之一,模型驱动类方法(Model-Drived-Method,MDM)可以有效地对水体相关多次波进行预测和压制,其中多次波贡献道集(multiples contribution gathers,MCG)的质量是影响该类方法多次波预测精度的主要因素。本文利用基于L0范数稀疏约束优化MCG,减弱多次波预测过程中所产生的假象,不但提高预测精度,而且在理论上减少了一定的计算量。同时对MDM类方法压制多次波进行了改进,通过对多种类型水体相关多次波的统一预测,弱化了常规MDM在压制水体相关多次波时对自适应减去过程的依赖程度,提高了方法的稳定性。理论模型证明了本文方法的有效性,实际资料案例进一步说明方法的应用潜力。
基金
supported by the National Natural Science Foundation of China(No.41504102)
the High-level Talents Initiation Project of North China University of Water Resources and Electric Power(No.40438)
