Time–frequency electromagnetic data contain frequency and transient electromagnetic information and can be used to determine the apparent resistivity both in the frequency and time domains.The observation data contains three types of noise:the harmonics interference at 50 Hz,high-frequency random noise,and low-frequency noise.We use frequency-domain bandstop filtering to remove the harmonics interference noise,segmentation and extension median filtering,and fitting of fixed extremes in empirical mode decomposition to remove the high-frequency and low-frequency noise,respectively;furthermore,we base the selection of median filtering window size on the variance and skewness coefficient of the data.We first remove the harmonics interference at 50 Hz,then the high-frequency noise,and finally the low-frequency noise.We test the proposed methodology by using theory and experiments,and we find that the three types of noises are removed,the phase and amplitude information of the signal are maintained,and high-quality waveforms are obtained in the time domain.
We propose a novel method that combines gray system theory and robust M-estimation method to suppress the interference in controlled-source electromagnetic data. We estimate the standard deviation of the data using a gray model because of the weak dependence of the gray system on data distribution and size. We combine the proposed and threshold method to identify and eliminate outliers. Robust M-estimation is applied to suppress the effect of the outliers and improve the accuracy. We treat the M-estimators of the preserved data as the true data. We use our method to reject the outliers in simulated signals containing noise to verify the feasibility of our proposed method. The processed values are observed to be approximate to the expected values with high accuracy. The maximum relative error is 3.6676%, whereas the minimum is 0.0251%. In processing field data, we observe that the proposed method eliminates outliers, minimizes the root-mean-square error, and improves the reliability of controlled-source electromagnetic data in follow-up processing and interpretation.
Mo DanJiang Qi-YunLi Di-QuanChen Chao-JianZhang Bi-Mingand Liu Jia-Wen
