1. Laboratory of Geophysical Electromagnetic Probing Technologies, Ministry of Natural Resources, Langfang 065000, China 2. Institute of Geophysical and Geochemical Exploration, CAGS, Langfang 065000, China 3. National Research Center of Geoexploration Technology, Langfang 065000, China 4. China Water Northeastern Investigation,Design and Research Co.,Ltd.,Changchun 130026, China
The main noise source of time-domain airborne electromagnetic survey is sferics that affects the quality of data. In practical work, how to remove sferics efficiently and quickly is the key to data preprocessing. Previous studies of trimmed mean/median filter have a good effect on sferic noise removal. However, there are some problems with single-window-filter. Small window filter does not completely remove the sferics, while large window filter can remove the sferic noise well, but the data at the power on, peak and power off will be over-averaged. Therefore, this paper proposes the hybrid window trim-mean filter, that is, small window parameter filter is adopted for the data at the power on, peak and power off every half cycle, and large window parameter filter is adopted for other data. This method can ensure the trend of data change and better remove the airborne noise at the same time. The removal of sferic noise can not only improve the SNR of data but also increase the exploration depth and provide high-quality data for data processing.
Yin C C, Zhang B, Liu Y H , et al. Review on airborne EM technology and developments[J]. Chinese Journal of Geophysics, 2015,58(8):2637-2653.
[2]
Spies B R . Local noise prediction filtering for central induction transient electromagnetic sounding[J]. Geophysics, 1988,53(8):1068-1079.
[3]
Buselli G, Pik J P, Hwang H S . AEM noise reduction with remoter referencing[J]. Exploration Geophysics, 1998,29(2):71-76.
[4]
Buselli G, Cmeron M . Robust statistical method for reducing sferics noise contaminating transient electromagnetic mezasurements[J]. Geophysics, 1996,61(6):1633-1646.
[5]
Bouchedda A, Chouteau M, Keating P , et al. Sferics noise reduction in time-domain electromagnetic systems: application to MegaTEM II signal enhancement[J]. Exploration Geophysics, 2010,41:225-239.
[6]
李楠 . 时间域航空电磁数据与处理技术研究[D]. 长春:吉林大学, 2010.
[6]
Li N . Research on airborne time-domain electromagnetic data processing[D]. Changchun: Jilin University, 2010.
[7]
吕东伟 . 吊舱式时间域直升机航空电磁数据处理方法研究[D]. 成都:成都理工大学, 2011.
[7]
Lyu D W . Methods study of helicopter-borne towed bird time domain electromagnetic data processing[D]. Chengdu:Chengdu University of Technology, 2011.
[8]
殷长春 . 航空电磁理论与勘查技术[M]. 北京: 科学出版社, 2018.
[8]
Yin C C. Airborne electromagnetic theory and exploration technology [M]. Beijing: Science Press, 2018.
[9]
Macnae James C, Lamontagnet Y, West G F . Noise processing techniques for time-domain EM systems[J]. Geophysics, 1984,49(7):934-948.
[10]
Bednar J B, Watt T L . Alpha-trimmed means and their relationship to median filters[J]. IEEE Transctions on Acoustics, Speech, and Dignal Processing, 1984,32(1):145-153.
[11]
Sutarno D, Vozoff K . Robust M-estimation of magnetotelluric impedance tensors[J]. Exploration Geophysics, 1989,20(3):383-398.
[12]
Cull J P . Signal processing concepts for airborne SIROTEM data[J]. Exploration Geophysics, 1991,22(1):97-100.
[13]
Lane R, Plunkett C, Price A , et al. Streamed data—a source of insight and improvement for time domain airborne EM[J]. Exploration Geophysics, 1998,29(2):16-23.
Li D S . Three-Dimensional modeling of grounded electrical source airborne transient electromagnetic and reduction method of electromagnetic noise[D]. Changchun: Jilin University, 2016.
[15]
Reninger P A, Martelet G, Deparis J , et al. Singular value decomposition as a denoising tool for airborne time domain electromagnetic data[J]. Journal of Applied Geophysics, 2011,75(2):264-276.
[16]
谢宾 . 时间域航空电磁数据去噪方法研究[D]. 长春: 吉林大学, 2015.
[16]
Xie B . Study on noise removal of time-domain airborne electromagnetic data[D]. Changchun: Jilin University, 2015.
[17]
Huang W, Ben F, Yin C C , et al. Three-dimensional arbitrarily anisotropic modeling for time-domain airborne electromagnetic surveys[J]. Applied Geophysics, 2017,14(3):431-440.
