Abstract:

In the course of time domain airborne electromagnetic exploration, induction electromotive force is produced by the movement of the receiver coil in the earth’s magnetic field, which is the main noise source in AEM data because of its large amplitude. Coil motion noise covers mainly low frequency band. Though its amplitude will rapidly decreases with frequency increasing, it still contains higher frequency components than transmitting frequency. Therefore, the traditional high pass filter has certain limitation in dealing with coil motion noise. According to the airborne electromagnetic data characteristics, polynomial is used to approximate motion noise for each full waveform half cycle, and then Lagrange method is employed to solve polynomial coefficient of motion noise. The polynomial coefficients are calculated by matrix inverse and finally motion noise is subtracted from each half cycle electromagnetic data. Furthermore, polynomial approximation method is applied to the synthetic data contaminated by low frequency motion noise comparing with traditional high pass filter method. Simulation results indicated that, the polynomial approximation method shows more effective in dealing with coil motion noise of airborne electromagnetic data, which can increase the signal to noise ratio more than 40 dB.

Key words: airborne electromagnetic data, coil motion noise, polynomial approximation, high pass filter