基于VMD算法在地震数据时频分析中的应用

Application of VMD algorithm in time-frequency analysis of seismic data

受新开发的变分模态分解(VMD)的启发,本文引入一种基于VMD的时频分析方法来分析地震数据.VMD的原理是将信号分解成具有一定中心频率的模态分量,通过这些分量来重构原始信号.这种分解方式可以降低各个模态中的残余噪声,同时进一步减少冗余的模态,很好的克服了模态混叠问题.此外,VMD是一种自适应信号分解技术,它可以非递归地将多分量信号分解为几个准正交固有模态函数,与EMD及其推广(如EEMD,CEEMD)相比,有坚实的数学基础.将VMD方法与CEEMD方法进行比较,对合成数据进行测试显示了基于VMD的时频分析方法具有更好的时频聚焦性,同时对实际数据处理也表明该方法具有突出地质特征和地层信息的潜力.

Inspired by the newly developed Variational Mode Decomposition(VMD),this paper introduces a time-frequency analysis method based on VMD to analyze seismic data.The principle of VMD is to decompose the signal into modal components with a certain center frequency,through modal components we can reconstruct the original signal.The decomposition method can reduce the residual noise in each mode,and it can further decrease the redundant mode,which overcomes the mode-mixing problem well.Moreover,VMD is an adaptive signal decomposition technique,which can nonrecursively decompose a multicomponent signal into several quasi-orthogonal intrinsic mode functions.This new tool,in contrast to Empirical Mode Decomposition(EMD)and its variations,such as EEMD,CEEMD,is based on a solid mathematical foundation.Comparing the VMD with the CEEMD and testing the synthesized data shows that the time-frequency analysis method based on VMD has better time-frequency focusing.Simultaneously,application on seismic data processing also shows the potential of the proposed approach in highlighting geologic characteristics and stratigraphic information effectively.