Magnetotelluric(MT)is a method of detecting electrical structures. The natural field source signal is weak, and there are many factors that affect the impedance estimation results, such as dead band, near-field interference, and random noise, so it is difficult to obtain accurate electromagnetic response in strong interference area. The stable and reliable impedance estimation is the premise for the follow-up inversion and interpretation. In order to suppress noise and improve the accuracy of impedance estimation, researchers have proposed various new data processing methods. However, these data processing methods are not widely used due to insufficient stability and poor applicability. The classic remote-reference method and robust estimation method are still the most widely used methods. This paper analyzes the characteristics of the strong interference data and the applicable scope of various data processing methods, combined with the processing effect of the measured magnetotelluric data in the strong interference area in eastern China, and summarizes a set of data processing strategies suitable for the strong interference area.

The remote-reference method can effectively suppress coherent noise. It is essential in data processing in strong interference areas. Usually, the results will be improved after processing by remote reference. The remote-reference site should be selected at a place far enough away from the measuring point without interference.

Robust estimation can highlight high-coherence signals and suppress low-coherence signals. In the dead band, the coherence of the natural field signal is higher than that of the background noise signal, so the robust estimation processing can improve the data processing result of the dead band. The intensity and coherence of the long-lasting near-field interference signal is higher than that of the natural-field signal. The robust estimation process will treat the near-field interference as the desired signal and suppress the natural source signal. Therefore, data containing long-term strong near-field interference is not suitable for using robust estimation but non-robust estimation. For data that is not well processed by the two methods, we can try a combination of the two. By carefully selecting the power spectrum obtained by the two methods, it is possible to improve the processing result.

Increasing the number of data segments can provide more sets of power spectra for selection, and also increase the probability of obtaining higher quality power spectra. Through careful selection of multiple power spectra, it is more likely to obtain better processing results than when the number of segments is smaller.

During the day when there is a lot of human activity, the interference signal is strong. And at night, the interference signal is weak. The measured data well proves this point, so we should extend the acquisition time at night as much as possible, and the data processing should also focus on the night data.

In general, it is more likely to obtain better data with longer acquisition time. Research on synthetic data shows that the maximum valid period of magnetotelluric theoretical data is 1/8 of the data duration. The measured data results of Fengning Station also support this conclusion. The longer the data acquisition time is, the more effective power spectra can be obtained, and the more likely it is to select a better quality spectrum from them, and obtain a stable impedance estimation result. Therefore, the data collection time should be adjusted reasonably according to the interference situation during the observation to ensure the stability of the impedance estimation result.

Magnetotelluric data processing methods are not invariable, and different data processing methods should be adopted according to the actual situation. When the better data processing method is not yet mature, flexible application of existing method is the necessary means for magnetotelluric data processing.

Many synthetic model studies suggested that the best way to obtain good 3D interpretation results is to distribute the MT sites at a 2D grid array with regular site spacing over the target area. However, MT 3D inversion was very difficult about 10 years ago. A lot of MT data were collected along one profile and then interpreted with 2D inversion. How to apply the state-of-the-art 3D inversion technique to interpret the accumulated mass MT profiles data is an important topic. Some studies on 3D inversion of measured MT profile data suggested that 2D inversions usually had higher resolution for the subsurface than 3D inversions. Meanwhile, they often made their interpretation based on 2D inversion results, and 3D inversion results were only used to evaluate whether the overall resistivity structures were correct. Some researchers thought that 3D inversions could not resolute the local structure well, while 2D inversion results could agree with the surface geologic features much well and interpret the geologic structures easily. But in the present paper, we find that the result of 3D inversion is better than that of 2D inversion in identifying the location of the two local faults, the Shade Fault(SDF)and the Yunongxi Fault(YNXF), and the deep structures.
In this paper, we first studied the electrical structure of SDF and YNXF based on a measured magnetotelluric(MT) profile data. Besides, from the point of identifying active faults, we compared the capacity of identifying deep existing faults between 2D inversion models and 3D models with different inversion parameters. The results show that both 2D and 3D inversion of the single-profile data could obtain reasonable and reliable electrical structures on a regional scale. Combining 2D and 3D models, and according to our present data, we find that both SDF and YNXF probably have cut completely the high resistivity layer in the upper crust and extended to the high conductivity layer in the middle crust. In terms of the deep geometry of the faults, at the profile's location, the SDF dips nearly vertically or dips southeast with high dip angle, and the YNXF dips southeast at depth. In addition, according to the results from our measured MT profile, we find that the 3D inversion of single-profile MT data has the capacity of identifying the location and deep geometry of local faults under present computing ability. Finally, this research suggests that appropriate cell size and reasonable smoothing parameters are important factors for the 3D inversion of single-profile MT data, more specifically, too coarse meshes or too large smoothing parameters on horizontal direction of 3D inversion may result in low resolution of 3D inversions that cannot identify the structure of faults. While, for vertical mesh size and data error thresholds, they have limited effect on identifying shallow tectonics as long as their changes are within a reasonable range. 3D inversion results also indicate that, to some extent, adding tippers to the 3D inversion of a MT profile can improve the model's constraint on the deep geometry of the outcropped faults.