时频域变分模态分解地震资料去噪方法

强噪声干扰、信噪比过低是造成深层地震资料成像不佳的主要因素。为此，提出在时频域内将变分模态分解算法应用于分频地震资料的噪声压制处理的新思路。首先，通过希尔伯特-黄变换（HHT）构建地震数据的解析信号，将地震数据转换到时频域，在时频域进行分频变分模态分解；随后，分析有效信号与噪声在时频切片上的能量分布，在此基础上优选出有效信号模态分量重构时频切片；最后反变换回时空域，达到噪声压制的目的。应用模型数据分析了关键参数对去噪效果的影响；实际资料的应用结果表明该算法可有效压制较强的随机背景噪声，同时对陡倾角的线性干扰也有明显的压制作用。

Seismic data de-noising method based on VMD in time-frequency domain

Strong noise interference is the primary factor that causes poor imaging of deep seismic data. A new idea applies a variable mode decomposition algorithm to noise suppression. Firstly, the analytical signals of seismic data are constructed by Hilbert-Huang transform (HHT), then the seismic data are converted into time-frequency domain where time-frequency slices are decomposed as instrinsic mode functions (IMFs) by the variable mode decomposition algorithm；then the energy distribution of effective signals and noises on the time-frequency slices is analyzed，and the time-frequency slices are reconstructed by the effective IMFs; and finally the slices are transformed back to the space-time domain to achieve the goal of noise suppression. The control of key parameters on the denoising effect of the algorithm has been analyzed on model data. The results of actual data have verified that the algorithm can effectively suppress strong random noises,and it is also effective for suppressing linear noises.