Research On Desert Seismic Signal Denoising Based On 2D Compact Variational Mode Decomposition

Seismic exploration is the main method to obtain geological information,and the exploitation of oil and gas resources can be realized through the obtained geological information.With the increase in demand for oil and gas resources and the maturity of exploration technology,conventional oil and gas exploration has been unable to meet people's needs.Unconventional oil and gas exploration has entered people's field of vision and has become a research hotspot.In seismic exploration,compared with conventional oil and gas fields,the acquisition environment of unconventional oil and gas fields is harsh,and the received seismic data contains more complex noise.So the signal-to-noise Ratio(SNR)of the seismic data collected is relatively low,which increases the difficulty of seismic data analysis.Therefore,the primary task of seismic signal processing is to improve the signal-to-noise ratio of seismic data and suppress the random noise in seismic data.This paper mainly studies the seismic signals in desert areas.The desert area is rich in oil and gas resources and has very broad prospects for exploration.However,the geographical environment of the desert area is complicated.The random noise in the seismic signal has the characteristics of low frequency,non-Gaussian,non-stationary,etc.The noise and the effective signal will overlap in the frequency domain.Conventional seismic signal denoising methods cannot effectively remove the desert earthquake Random noise in the signal.Therefore,it is necessary to find an effective method that can remove the noise of desert seismic signals.Variational modal decomposition(VMD)decomposes the signal non-recursively into a limited number of narrow-band modal functions distributed around the center frequency,which has been widely used in seismic signal processing.However,VMD decomposes the signal into different modes according to the frequency,which has no obvious suppression effect on desert low-frequency noise.Two dimensional variational mode decomposition(2D-VMD)extends the VMD algorithm to two dimensions,and can decompose the signal into a limited number of inherent modal functions with specific directions and vibration characteristics.The two dimensional compact variational mode decomposition(2D-CVMD)algorithm introduces a binarysupport function on the basis of 2D-VMD.Through total variation(TV)and L1 norm penalized binary support functions,it can promote the mode in the frequency domain Sparsity.In this paper,the 2D-CVMD algorithm is applied to the noise suppression of desert seismic signals.First,the two-dimensional desert seismic signals are decomposed,and the signals are decomposed into finite modal components and corresponding binary support functions.The modal component has a specific direction,and the signal and noise modes are determined according to the directionality of the mode,the noise mode is discarded,and the signal mode is retained.Using the binary support function as a mask of signal modal components,a mask modal is obtained.Finally,the mask modals are added to obtain the denoised signal.The above algorithm is used for synthetic desert seismic data processing.The f-x domain prediction filtering,wavelet transform and VMD algorithm are used as comparative experiments.By comparing the signal denoising maps in the time-frequency domain,the single-channel signal comparison map,and the SNR values,it can be seen that this method can effectively suppress the noise and achieve the retention of valid signals.Applying the algorithm to the processing of actual desert seismic data,compared with the traditional seismic signal denoising algorithm,this method can suppress the noise and restore the same phase continuously and clearly.