LIU WeiQiang,
Lü QingTian*,
LIN PinRong et al
.0.Anti-interference processing for multi-period full waveform induced polarization data and the application in a large-scale detection Chinese Journal of Geophysics(in Chinese),(): 1-,doi: 10.6038/cjg2019M0418
Anti-interference processing for multi-period full waveform induced polarization data and the application in a large-scale detection
LIU WeiQiang 1,2, Lü QingTian1,2*, LIN PinRong2, CHEN RuJun3, CHEN ChaoJian3
1 MNR Laboratory of Geophysical EM Probing Technologies, Institute of Geophysical and Geochemical Exploration, CAGS, Langfang, 065000, China
2 MNR Key Laboratory of Metallogeny and Mineral Assessment, Institute of Mineral Resources, CAGS，Beijing, 100037, China
3 Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, School of Geosciences and Info-Physics, Central South University, Changsha, 400071, China
Abstract：Induced polarization (IP) is one of the most important electrical exploration branch approach in ore deposits survey, However the existence of various electromagnetic interferences restricts the application of IP in the large-scale exploration. Recently, many research institutes have developed 3D disturbed full-waveform IP instrument system, which provides a new stage for the IP signal processing. In this paper, a complete anti-interference processing method based on statistical analysis for the multi-period full-waveform IP samples is proposed. Empirical mode decomposition is used for separation of low-frequency trend term interference; Correlation analysis is used to eliminate the sudden strong noise interference; Robust statistics are used for multi-period time series stack. The subsection robust average and low frequency relative phase spectrum are used to extract the time/frequency field IP parameters. The above data processing method is applied to the three-dimensional full-waveform IP data acquired by domestic distributed electrical system and compared with the common processing methods such as linear fitting and mean stacking. The research shows that the new method can effectively identify and suppress the strong noise interference in IP data, improve the quality of IP data when the current electrode space is large and the frequency is low, and further promote the application of IP method in deep mineral resources exploration.
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