Reduce the Noise of Transient Electromagnetic Signal Based on the Method of SMA-VMD-WTD

Abstract

To reduce all kinds of noise interference in the transient electromagnetic signal, and improve the resolution of abnormal resistance in detection area. In this paper, a method based on Slime Mould Algorithm (SMA) optimized Variational Mode Decomposition (VMD) combined with Wavelet Threshold Denoising (SMA-VMD-WTD) was proposed to identify and eliminate the noise. Firstly, the slime mould algorithm (SMA) was used to select the key parameters in VMD. Then, the signal was adaptively decomposed by VMD according to the optimized parameters to obtain certain modal components, and divided them into effective signal components and noise components. Finally, the effective signal components were further processed by Wavelet Threshold Denoising (WTD) and reconstructed to obtain the transient electromagnetic signal with noise removal. The simulation signal tests with different noise intensity were built, and this method was compared with Ensemble Empirical Mode Decomposition (EEMD), WTD, unoptimized VMD and SMA to optimize VMD for reducing noise analysis of simulation tests. The results showed that SMA-VMD-WTD was more effective in identifying and eliminating transient electromagnetic signal noise. The method was applied to a geological exploration area, which verified the field applicability of this method. The results of the simulation tests and field test showed that SMA-VMD-WTD was a better denoising method for transient electromagnetic signal.