Journal of Jilin University(Earth Science Edition) ›› 2020, Vol. 50 ›› Issue (6): 1870-1886.doi: 10.13278/j.cnki.jjuese.20190211

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Spatial and Temporal Distribution Characteristics of Electromagnetic Fields in Strong Noise Area

Zhou Cong1, Tang Jingtian2, Yuan Yuan1, Li Guang1, Xiao Xiao2, Deng Juzhi1   

  1. 1. State Key Laboratory of Nuclear Resources and Environment(East China University of Technology), Nanchang 330013, China;
    2. Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring(Central South University), Ministry of Education, Changsha 410083, China
  • Received:2019-10-01 Published:2020-12-11
  • Supported by:
    Supported by National Key R & D Program of China (2018YFC0603202), National Natural Science Foundation of China (41904072, 41904073, 41904076), Science and Technology Research Project of Education Department of Jiangxi Province (GJJ180398) and Fund from the State Key Laboratory of Nuclear Resources and Environment (East China University of Technology) (NRE1919)

Abstract: Noise is one of the bottlenecks that restrict the application effect of electromagnetic prospecting. Understanding the characteristics of electromagnetic fields is primary for an electromagnetic research in strong noise areas. Based on the investigation of interference sources and a large amount of measured data in Lu-Zong ore concentration area, we summarized the main types of electromagnetic noise sources in strong noise areas, and the distribution characteristics of the noise-containing electromagnetic fields in time, frequency,and space domain by comparing and analyzing various types of electromagnetic field data with different conditions. The results show that the noise sources in Lu-Zong area can be classified into different forms; the data of the noisy electromagnetic fields often have significant morphological, amplitude, structural, and correlative characteristics in time domain; the spectrum figures often show different time and frequency band characteristics; the frequency domain responses often show distortion in certain frequency bands, and the "near source" distortion is the most typical one. The spatial distribution of noise influence is related to the types of field sources, observation orientations, and underground structures. According to the characteristics of noise data, the pertinent processing algorithm or research direction is pointed out, which provides a reference for the application of electromagnetic methods in strong noise areas.

Key words: geophysics, electromagnetic prospecting, electromagnetic fields, magnetotellurics, noise, Lu-Zong ore concentration area

CLC Number: 

  • P631
[1] 杨生. 大地电磁测深法环境噪声抑制研究及其应用[D]. 长沙:中南大学, 2004. Yang Sheng. The Study of Restraining Environmental Noise and Its Application in Magnetotelluric Sounding[D]. Changsha:Central South University, 2004.
[2] Simpson F, Bahr K. Practical Magnetotellurics[M]. Cambridge:Cambridge University Press, 2005.
[3] Junge A. Characterization of and Correction for Cultural Noise[J]. Surveys in Geophysics, 1996, 17(4):361-391.
[4] Iliceto V, Santarato G. On the Interference of Man-Made EM Fields in the Magnetotelluric ‘Dead Band’[J]. Geophysical Prospecting, 1999, 47(5):707-719.
[5] Garcia X, Jones A G. Atmospheric Sources for Audio-Magnetotelluric (AMT) Sounding[J]. Geophysics, 2002, 67(2):448-458.
[6] 周聪, 汤井田,任政勇, 等. 音频大地电磁法"死频带"畸变数据的Rhoplus校正[J]. 地球物理学报, 2015, 58(12):4648-4660. Zhou Cong, Tang Jingtian, Ren Zhengyong, et al. Application of the Rhoplus Method to Audio Magnetotelluric Dead Band Distortion Data[J]. Chinese Journal of Geophysics, 2015, 58(12):4648-4660.
[7] 汤井田, 何继善. 可控源音频大地电磁法及其应用[M]. 长沙:中南大学出版社, 2005. Tang Jingtian, He Jishan. Methods and Applications of CSAMT[M]. Changsha:Central South University Press, 2005.
[8] 张良怀, 李征西, 张京辉, 等. 50万伏超高压输电线的电磁场时空分布特征及其实验研究[J]. 东北地震研究, 1998,14(1):17-30. Zhang Lianghuai, Li Zhengxi, Zhang Jinghui, et al. Experimental Research of Electromagnetic Field Distribution Around 500 kV Supervoltage Power Line[J]. Seismological Research of Northeast China, 1998, 14(1):17-30.
[9] 李桐林, 刘福春, 韩英杰, 等. 50万伏超高压输电线的电磁噪声的研究[J]. 长春科技大学学报, 2000, 30(1):80-83. Li Tonglin, Liu Fuchun, Han Yingjie, et al.The Study of Electromagnetic Noise Created by High Voltage Transmission Line[J]. Journal of Changchun University of Science and Technology, 2000, 30(1):80-83.
[10] Pádua M B, Padilha A L, Vitorello I. Disturbances on Magnetotelluric Data due to DC Electrified Railway:A Case Study from Southeastern Brazil[J]. Earth Planets & Space, 2002, 54(5):591-596.
[11] Villante U, Piancatelli A, Palangio P. On the Man-Made Contamination on ULF Measurements:Evidence for Disturbances Related to an Electrified DC Railway[J]. Annales Geophysicae, 2014, 32(9):1153-1161.
[12] 范翠松. 矿集区强干扰大地电磁噪声特点及去噪方法研究[D]. 长春:吉林大学, 2009. Fan Cuisong. The Strong Noise Characteristics of MT in Ore Concentration Area and Research of Denoise Method[D]. Changchun:Jilin University, 2009.
[13] 汤井田, 徐志敏, 肖晓, 等. 庐枞矿集区大地电磁测深强噪声的影响规律[J]. 地球物理学报, 2012, 55(12):4147-4159. Tang Jingtian, Xu Zhimin, Xiao Xiao, et al. Effect Rules of Strong Noise on Magnetotelluric (MT) Sounding in the Lu-Zong Ore Cluster Area[J]. Chinese Journal of Geophysics, 2012, 55(12):4147-4159.
[14] 徐志敏. 庐枞大地电磁干扰噪声研究[D]. 长沙:中南大学, 2012. Xu Zhimin. Study of Magnetotelluric Interference Noise of Lu-Zong[D]. Changsha:Central South University, 2012.
[15] 王辉, 程久龙, 腾星智, 等. 矿区近场源噪声对大地电磁测深数据的影响及其压制方法[J]. 地球物理学进展, 2016, 31(3):1358-1366. Wang Hui, Cheng Jiulong, Teng Xingzhi, et al. Source Effect on Magnetotelluric Data Due to Mining Area and Its Suppression[J]. Progress in Geophysics, 2016, 31(3):1358-1366.
[16] Tang J T, Zhou C, Wang X Y, et al. Deep Electrical Structure and Geological Significance of Tongling Ore District[J]. Tectonophysics, 2013, 606(1):78-96.
[17] 汤井田, 张林成, 王显莹, 等. 庐枞矿集区矾山-将军庙地区AMT三维反演及地质结构解释[J]. 地球物理学报, 2018, 61(4):1576-1587. Tang Jingtian, Zhang Lincheng, Wang Xianying,et al. Subsurface Electrical Structure of the Fanshan-Jiangjunmiao Area in the Lujiang-Zongyang Ore District Derived from 3-D Inversion of Audio-Magnetotelluric Data[J].Chinese Journal of Geophysics, 2018, 61(4):1576-1587.
[18] 周聪. 时空阵列电磁法及试验研究兼论庐枞矿集区三维电性结构[D]. 长沙:中南大学, 2016. Zhou Cong. Theoretical and Experimental Study of Space-Time Array Electromagnetic Method and Three-Dimensional Electrical Structure of Lu-Zong Ore District[D]. Changsha:Central South University, 2016.
[19] 汤井田, 李晋, 肖晓, 等. 数学形态滤波与大地电磁噪声压制[J]. 地球物理学报, 2012, 55(5):1784-1793. Tang Jingtian, Li Jin, Xiao Xiao, et al. Mathematical Morphology Filtering and Noise Suppression of Magnetotelluric Sounding Data[J]. Chinese Journal of Geophysics, 2012, 55(5):1784-1793.
[20] 蔡剑华, 王先春, 胡惟文. 基于经验模态分解与小波阈值的MT信号去噪方法[J]. 石油地球物理勘探, 2013,48(2):303-307. Cai Jianhua, Wang Xianchun, Hu Weiwen. A Method for MT Data Denoising Based on Empirical Mode Decomposition and Wavelet Threshold[J]. Oil Geophysical Prospecting, 2013, 48(2):303-307.
[21] Kappler K N. A Data Variance Technique for Automated Despiking of Magnetotelluric Data with a Remote Reference[J]. Geophysical Prospecting, 2012, 60(1):179-191.
[22] 王辉, 程久龙, 姚郁松, 等. 基于站间天然电磁场单位脉冲响应的大地电磁时间序列去噪方法[J]. 地球物理学报, 2019, 62(3):1057-1070. Wang Hui, Cheng Jiulong, Yao Yusong, et al. A New Method of Noise Deletion in Magnetotelluric Time-Series Based on Impulse Response of Inter-Station Transfer Function[J]. Chinese Journal of Geophysics, 2019, 62(3):1057-1070.
[23] 汤井田, 李广, 肖晓, 等. 基于压缩感知重构算法的大地电磁强干扰分离[J]. 地球物理学报, 2017, 60(9):3642-3654. Tang Jingtian, Li Guang, Xiao Xiao, et al. Strong Noise Separation for Magnetotelluric Data Based on a Signal Reconstruction Algorithm of Compressive Sensing[J]. Chinese Journal of Geophysics, 2017, 60(9):3642-3654.
[24] 汤井田, 李广, 周聪, 等.基于字典学习的音频大地电磁数据处理[J].地球物理学报, 2018, 61(9):3835-3850. Tang Jingtian, Li Guang, Zhou Cong, et al. Denoising AMT Data Based on Dictionary Learning[J]. Chinese Journal of Geophysics, 2018, 61(9):3835-3850.
[25] 曹小玲, 刘开元, 严良俊. 大地电磁的小波变换-独立分量分析去噪[J]. 石油地球物理勘探, 2018, 53(1):206-213. Cao Xiaoling, Liu Kaiyuan, Yan Liangjun. Magnetotelluric Data De-Noising Based on Wavelet Transform and Independent Component Analysis[J]. Oil Geophysical Prospecting, 2018, 53(1):206-213.
[26] Weckmann U, Magunia A, Ritter O. Effective Noise Separation for Magnetotelluric Single Site Data Processing Using a Frequency Domain Selection Scheme[J]. Geophysical Journal International, 2005, 161(3):635-652.
[27] Smirnov M Y. Magnetotelluric Data Processing with a Robust Statistical Procedure Having a High Breakdown Point[J]. Geophysical Journal International, 2003, 152(1):1-7.
[28] 景建恩, 魏文博, 陈海燕, 等. 基于广义S变换的大地电磁测深数据处理[J]. 地球物理学报, 2012, 55(12):4015-4022. Jing Jian'en, Wei Wenbo, Chen Haiyan, et al. Magnetotelluric Sounding Data Processing Based on Generalized S Transformation[J]. Chinese Journal of Geophysics, 2012, 55(12):4015-4022.
[29] 凌振宝, 王沛元, 万云霞, 等. 强人文干扰环境的电磁数据小波去噪方法研究[J]. 地球物理学报, 2016, 59(9):3436-3447. Ling Zhenbao, Wang Peiyuan, Wan Yunxia, et al. A Combined Wavelet Transform Algorithm Used for De-Noising Magnetotellurics Data in the Strong Human Noise[J].Chinese Journal of Geophysics, 2016, 59(9):3436-3447.
[30] 王正海, 耿欣, 姚卓森, 等. 基于经验模态分解的MT数据脉冲类电磁噪声处理[J].吉林大学学报(地球科学版), 2014, 44(1):344-349. Wang Zhenghai, Geng Xin, Yao Zhuosen, et al. Like-Impulse Electromagnetic Noise Processing Based on Empirical Mode Decomposition[J]. Journal of Jilin University (Earth Science Edition), 2014, 44(1):344-349.
[31] 范翠松, 李桐林, 王大勇. 小波变换对MT数据中方波噪声的处理[J]. 吉林大学学报(地球科学版), 2008, 38(增刊1):61-63. Fan Cuisong, Li Tonglin, Wang Dayong.Treatment of Wavelet Transform for Square Wave Noise in MT Data[J]. Journal of Jilin University (Earth Science Edition), 2008, 38(Sup.1):61-63.
[32] 张刚, 庹先国, 王绪本, 等. 磁场相关性在远参考大地电磁数据处理中的应用[J]. 石油地球物理勘探, 2017, 52(6):1333-1343. Zhang Gang, Tuo Xianguo, Wang Xuben, et al. Application of Magnetic Field Correlation in Remote Reference Magnetotelluric Data Processing[J]. Oil Geophysical Prospecting, 2017, 52(6):1333-1343.
[33] Sokolova E Y, Varentsov M I, Group E P W. RRMC Technique Fights Highly Coherent EM Noise[C]//Ritter O, Brasse H. Protokoll Uber Das 21 Kolloquium Elektromagnetische Tiefenforschung. Potsdam:Dtsch Geophys Ges, 2005:124-136.
[34] Oettinger G, Haak V, Larsen J C. Noise Reduction in Magnetotelluric Time-Series with a New Signal-Noise Separation Method and Its Application to a Field Experiment in the Saxonian Granulite Massif[J]. Geophysical Journal International, 2010, 146(3):659-669.
[35] 汤井田, 周聪, 张林成. CSAMT电场y方向视电阻率的定义及研究[J].吉林大学学报(地球科学版), 2011,41(2):552-558. Tang Jingtian, Zhou Cong, Zhang Lincheng. A New Apparent Resistivity of CSAMT Defined by Electric Field y-Direction[J]. Journal of Jilin University (Earth Science Edition), 2011, 41(2):552-558.
[36] 周聪, 汤井田, 庞成, 等.时空阵列混场源电磁法理论及模拟研究[J]. 地球物理学报, 2019, 62(10):3827-3842. Zhou Cong, Tang Jingtian, Pang Cheng, et al. A Theory and Simulation Study on the Space-Time Array Hybrid Source Electromagnetic Method[J]. Chinese Journal of Geophysics, 2019, 62(10):3827-3842.
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