强干扰环境下的大地电磁时间序列处理过程

doi:10.3969/j.issn.0253-4967.2022.03.014

地震地质 ›› 2022, Vol. 44 ›› Issue (3): 786-801.DOI: 10.3969/j.issn.0253-4967.2022.03.014

• 极低频地震电磁专题文章 • 上一篇下一篇

强干扰环境下的大地电磁时间序列处理过程

张赟昀¹⁾(), 王培杰²⁾, 陈小斌¹^,²⁾^,^*(), 詹艳²⁾, 韩冰²⁾, 王立凤²⁾, 赵国泽²⁾

1)应急管理部国家自然灾害防治研究院, 北京 100085
2)中国地震局地质研究所, 地震动力学国家重点实验室, 北京 100029

收稿日期:2021-03-16 修回日期:2021-05-12 出版日期:2022-06-20 发布日期:2022-08-02
通讯作者: 陈小斌
作者简介:张赟昀, 女, 1994年生, 2019年于中国地质大学(武汉)获地球物理学专业硕士学位, 研究方向为大地电磁数据处理与解释, E-mail: yyz725@163.com。
基金资助:
应急管理部国家自然灾害防治研究院基本科研业务专项(ZDJ2019-26);国家重点研发计划项目(2017YFC1500204-0002)

MAGNETOTELLURIC TIME SERIES PROCESSING IN STRONG INTERFERENCE ENVIRONMENT

ZHANG Yun-yun¹⁾(), WANG Pei-jie²⁾, CHEN Xiao-bin¹^,²⁾^,^*(), ZHAN Yan²⁾, HAN Bing²⁾, WANG Li-feng²⁾, ZHAO Guo-ze²⁾

1) National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China
2) State Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration, Beijing 100029, China

Received:2021-03-16 Revised:2021-05-12 Online:2022-06-20 Published:2022-08-02
Contact: CHEN Xiao-bin

摘要/Abstract

摘要：

天然源的大地电磁信号易受干扰影响, 导致阻抗估计结果不准确, 这种难以克服的缺陷制约着大地电磁法的应用范围。随着工业化发展, 人文干扰越发严重, 传统的数据处理方法已经不能改善强电磁干扰环境下的数据质量。文中结合大地电磁数据处理的基本理论对中国东部强干扰地区实测数据进行了处理。分析了稳健估计(Robust)处理、分段叠加处理和分时处理等技术的处理效果, 总结了不同干扰情况下的数据处理方案。对于不同干扰特征的数据, 要综合分析Robust处理对数据的影响, 灵活应用Robust处理。为得到更好的处理结果, 应适当增加数据采集时间, 特别是夜间干扰较弱时段的数据采集时间。此外, 增加数据分段的个数, 提供更多可供编辑的功率谱也是得到优质数据的必要条件。

关键词: 大地电磁法, 强干扰, 数据处理, 远参考, 稳健估计

Abstract:

Magnetotelluric(MT)is a method of detecting electrical structures. The natural field source signal is weak, and there are many factors that affect the impedance estimation results, such as dead band, near-field interference, and random noise, so it is difficult to obtain accurate electromagnetic response in strong interference area. The stable and reliable impedance estimation is the premise for the follow-up inversion and interpretation. In order to suppress noise and improve the accuracy of impedance estimation, researchers have proposed various new data processing methods. However, these data processing methods are not widely used due to insufficient stability and poor applicability. The classic remote-reference method and robust estimation method are still the most widely used methods. This paper analyzes the characteristics of the strong interference data and the applicable scope of various data processing methods, combined with the processing effect of the measured magnetotelluric data in the strong interference area in eastern China, and summarizes a set of data processing strategies suitable for the strong interference area.

The remote-reference method can effectively suppress coherent noise. It is essential in data processing in strong interference areas. Usually, the results will be improved after processing by remote reference. The remote-reference site should be selected at a place far enough away from the measuring point without interference.

Robust estimation can highlight high-coherence signals and suppress low-coherence signals. In the dead band, the coherence of the natural field signal is higher than that of the background noise signal, so the robust estimation processing can improve the data processing result of the dead band. The intensity and coherence of the long-lasting near-field interference signal is higher than that of the natural-field signal. The robust estimation process will treat the near-field interference as the desired signal and suppress the natural source signal. Therefore, data containing long-term strong near-field interference is not suitable for using robust estimation but non-robust estimation. For data that is not well processed by the two methods, we can try a combination of the two. By carefully selecting the power spectrum obtained by the two methods, it is possible to improve the processing result.

Increasing the number of data segments can provide more sets of power spectra for selection, and also increase the probability of obtaining higher quality power spectra. Through careful selection of multiple power spectra, it is more likely to obtain better processing results than when the number of segments is smaller.

During the day when there is a lot of human activity, the interference signal is strong. And at night, the interference signal is weak. The measured data well proves this point, so we should extend the acquisition time at night as much as possible, and the data processing should also focus on the night data.

In general, it is more likely to obtain better data with longer acquisition time. Research on synthetic data shows that the maximum valid period of magnetotelluric theoretical data is 1/8 of the data duration. The measured data results of Fengning Station also support this conclusion. The longer the data acquisition time is, the more effective power spectra can be obtained, and the more likely it is to select a better quality spectrum from them, and obtain a stable impedance estimation result. Therefore, the data collection time should be adjusted reasonably according to the interference situation during the observation to ensure the stability of the impedance estimation result.

Magnetotelluric data processing methods are not invariable, and different data processing methods should be adopted according to the actual situation. When the better data processing method is not yet mature, flexible application of existing method is the necessary means for magnetotelluric data processing.

Key words: magnetotelluric, strong interference, data processing, remote reference, robust estimation

中图分类号:

P315.721

张赟昀, 王培杰, 陈小斌, 詹艳, 韩冰, 王立凤, 赵国泽. 强干扰环境下的大地电磁时间序列处理过程[J]. 地震地质, 2022, 44(3): 786-801.

ZHANG Yun-yun, WANG Pei-jie, CHEN Xiao-bin, ZHAN Yan, HAN Bing, WANG Li-feng, ZHAO Guo-ze. MAGNETOTELLURIC TIME SERIES PROCESSING IN STRONG INTERFERENCE ENVIRONMENT[J]. SEISMOLOGY AND GEOLOGY, 2022, 44(3): 786-801.

图/表 12

图 1 大地电磁测点及远参考点分布图

Fig. 1 Distribution of MT station and remote reference station.

图 2 不同远参考站的数据处理效果图红点、蓝点分别为xy、 yx向视电阻率和阻抗相位, 橙线、绿线分别为xy、 yx向Rhoplus反演曲线, 下同

Fig. 2 Data processing effect of different remote reference stations.

图 3 709测点的视电阻率和相位曲线

Fig. 3 Apparent resistivity and phase curves of MT station 709.

图 4 209测点的视电阻率和相位曲线

Fig. 4 Apparent resistivity and phase curves of MT station 209.

图 5 307测点稳健估计(Robust)处理、非稳健估计(非Robust)处理及二者叠加处理得到的视电阻率和相位曲线

Fig. 5 Apparent resistivity and phase curve of MT station 307 obtained by robust processing, non-robust processing and superposition processing.

图 6 503测点不同分段数对应的视电阻率和相位曲线从左至右对应的每段时长分别为800min、 400min、 200min和100min

Fig. 6 Apparent resistivity and phase curves of MT station 503 corresponding to different segment numbers.

图 7 504测点不同分段数对应的视电阻率和相位曲线从左至右对应的每段时长分别为800min、 400min、 200min和100min

Fig. 7 Apparent resistivity and phase curves of MT station 504 corresponding to different segment numbers.

图 8 305测点的视电阻率及相位曲线的昼夜对比图

Fig. 8 Comparison of day and night apparent resistivity and phase curve at MT station 305.

图 9 305测点昼夜不同时长的视电阻率及相位曲线对比图

Fig. 9 Comparison of apparent resistivity and phase curves of MT station 305 with different time and length.

图 10 305测点不同时长数据对应的视电阻率及相位曲线图

Fig. 10 Apparent resistivity and phase curves of MT station 309 with different duration.

图 11 采样率为4 096Hz、时长为8s的合成数据的处理结果 a 振幅谱; b 视电阻率; c 相位

Fig. 11 Synthetic data processing results with a sampling rate of 4 096Hz and a length of 8s.

图 12 丰宁台实测数据的处理结果 a 24h数据处理得到的视电阻率和相位曲线; b 获取有效阻抗所需的最短数据时长

Fig. 12 Measured data processing result of Fengning station.

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强干扰环境下的大地电磁时间序列处理过程

MAGNETOTELLURIC TIME SERIES PROCESSING IN STRONG INTERFERENCE ENVIRONMENT

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