CSEM Data Denoising Based on STL-LPFMD

Strong electromagnetic interference is one of the main factors affecting the effectiveness of electromagnetic exploration. In this study, the seasonal-trend decomposition based on Loess (STL) and low-pass feature mode decomposition (LPFMD) are applied to controlled-source electromagnetic method (CSEM) signal processing for the first time. The method we proposed is verified the effectiveness and practicability by the simulated and measured data of wide-field electromagnetic method (WFEM). The results show that the combination of STL and LPFMD realizes effective removal of strong electromagnetic interference and further improves the signal-to-noise ratio (SNR) of CSEM observed data.