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A study of sferic removal from time domain airborne electromagnetic data |
Fang BEN1,2,3, Wei HUANG1,2,3( ), Ning LU1,2,3, Fei HAN4, Hong-Shan ZHENG1,2,3, Zhi-Qiang DING1,2,3, Jun-Feng LI1,2,3 |
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 |
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Abstract 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.
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Received: 11 May 2019
Published: 22 April 2020
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Corresponding Authors:
Wei HUANG
E-mail: huangwei2012511@163.com
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The diagram of Trim-mean filter processing
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Two extension methods
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Comparison of noise removal effects of different filter window lengths
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Comparison of noise removal effects of different trim lengths
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Effects of hybrid window trim-mean filter
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