The advantages of the long-offset transient electromagnetic method include deep detection and sensitive response to resistivity anomalies. It is widely used in underground mineral resources exploration, fluid identification in petroleum reservoirs, hydraulic fracturing, and dynamic residual oil and gas monitoring. After the primary field signal is turned off, grounded electrodes or coils are used to observe the secondary eddy field. The secondary field signal decays quickly and has a large dynamic range and a wide frequency band but is easily affected by various natural and human electromagnetic interferences. Therefore, noise reduction and distortion correction are important issues in the processing of transient electromagnetic data. This paper proposes a systematic noise interference suppression process. Multi-period and positive–negative bipolar signal stackings were used to remove random noise and suppress DC offset signals. Then, a time-domain inverse digital recursive method was applied to remove characteristic frequency signals, e.g., power frequency signals and their harmonic interference. A standard noise-free signal was constructed through forward modeling simulation and verified by adding different types of noise. Finally, high-quality transient electromagnetic secondary field attenuation signals were obtained through overlapping windowing technology. We applied this algorithm to obtain electromagnetic data from dynamic monitoring of hydraulic fracturing in Fuling shale gas and from a copper–iron metal mine in Daye City, demonstrating its effectiveness.

The long-offset transient electromagnetic (LOTEM) method, as a widely applied electromagnetic exploration technique, plays a significant role in mineral resource exploration, hydraulic fracturing monitoring, and fluid identification in oil and gas reservoirs. However, due to external interference, the signals acquired by this method often contain substantial noise, which severely affects the reliability of subsequent inversion and interpretation. Therefore, denoising is a critical issue in LOTEM data processing. To address this problem, this paper proposes a denoising study for LOTEM post-stack signals based on a combination of windowed interpolation and singular spectrum analysis. First, the stacking method and windowed interpolation are employed to remove most of the random noise and power-line interference (including its harmonics). Then, singular spectrum analysis is applied to further suppress noise and obtain higher-quality signal data. Experimental results demonstrate that the proposed method performs well in denoising, effectively reducing the root mean square error (RMSE) of the signal and improving its signal-to-noise ratio (SNR). The method was validated using LOTEM data collected from Zhongjiang County, Sichuan Province. The validation results show that the method can effectively remove noise interference from underground media, providing essential technical support for inversion and interpretation.