Research On Interference Suppression And Quality Evaluation Method Of Ground-Airborne Frequency-Domain Electromagnetic Detection Data

The ground-airborne frequency-domain electromagnetic detection is a new geophysical exploration method developed in recent years.The detection of the electrical characteristics of underground structures in the survey area is realized by the way of laying electromagnetic emission sources on the ground and measuring magnetic field in the air.By studying the spatial and frequency characteristics of electromagnetic field,the abnormal body of underground electric property is detected,which is more and more widely used in the fields of underground resource exploration,engineering geological environment investigation and so on.Based on the project of National Natural Science Foundation of China and the exploration project of West Chongqing and Sichuan-Tibet railway,this paper studies interference suppression and quality evaluation methods of ground-airborne electromagnetic detection data in the frequency domain.The main research contents are as follows:1)Due to the influence of flight factors and environmental factors,low-frequency motion noise,random noise,peak noise,attitude noise and high-frequency noise exist in the collected data,which seriously affects the accuracy of subsequent data inversion interpretation.To better adapt to the complex environment of field detection and improve the accuracy of detection,this paper suppressed the interference existing in the data from the perspective of data processing,so as to extract target signal more accurately and evaluate the quality of detection data to ensure qualified data participate in subsequent data processing and interpretation.This research has academic and practical significance for the accurate extraction of target signal in the ground-airborne frequency domain electromagnetic detection.2)Aiming at random noise and peak noise,combined with the characteristics of the ground-airborne frequency domain electromagnetic data,the time-window superposition filtering method based on Robust-M estimation is proposed,and the influence of abnormal data can be eliminated or weakened by coefficient weighting.Compared with the traditional smoothing filtering,this method can suppress the random noise and peak noise effectively.Aiming at the attitude noise,according to the Faraday electromagnetic induction principle,the magnetic field response with the attitude of the receiving coil can be divided into dynamic response and static response,and the attitude correction is carried out from the two aspects respectively.The dynamic response is only related to the attitude angle of the coil,so it can be removed by theoretical calculation directly.For the static response,it is not only related to the attitude angle,but also related to the background conductivity of the measured area.The static response coefficient is corrected by constructing the BP neural network model,so as to achieve the static response correction.The quality evaluation method of groundairborne frequency domain electromagnetic data is studied.Based on the existing ground-airborne electromagnetic response program and simulated data in the laboratory,the influence of flight height and yaw distance on measurement accuracy is analyzed.The field detection data is evaluated from three aspects: flight height,yaw degree and signal-to-noise ratio.3)The effectiveness of the interference suppression method proposed in this paper and the rationality of the data quality evaluation method are verified by the application in the simulated data and field measured data,so that the ground-airborne frequency domain electromagnetic detection method can be better applied in the complex environment of field detection.