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《地球科学与环境学报》[ISSN:1672-6561/CN:61-1423/P]

卷:

第45卷

期数:

2023年第05期

页码:

1270-1284

栏目:

庆贺汤中立院士从事地质工作七十周年专辑

出版日期:

2023-09-15

文章信息/Info

Title:

Airborne Transient Electromagnetic Noise Reduction Based on Curvelet Transform

文章编号:

1672-6561(2023)05-1270-15

作者:

蔺凯如¹; 张继锋¹; 2; 3*; 张富翔¹; 石 宇¹

(1. 长安大学 地质工程与测绘学院,陕西 西安 710054; 2. 海洋油气勘探国家工程研究中心,北京 100028; 3. 长安大学 地球物理场多参数综合模拟实验室,陕西 西安 710054)

Author(s):

LIN Kai-ru¹;  ZHANG Ji-feng¹; 2; 3*;  ZHANG Fu-xiang¹;  SHI Yu¹

(1. School of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, Shaanxi, China; 2. National Engineering Research Center of Offshore Oil and Gas Exploration, Beijing 100028, China; 3. Integrated Geophysical Simulation Laboratory, Chang'an University, Xi'an 710054, Shaanxi, China)

关键词:

航空瞬变电磁;  曲波变换;  去噪;  信号分析;  噪声干扰;  快速离散

Keywords:

airborne transient electromagnetism;  curvelet transform;  noise reduction;  signal analysis;  noise interference;  fast discrete

分类号:

P631.3⁺25

DOI:

10.19814/j.jese.2023.02019

文献标志码:

A

摘要:

噪声干扰严重影响着航空瞬变电磁的数据处理和成像解释,如何有效去噪成为航空瞬变电磁研究的重要内容。根据航空瞬变电磁噪声特点,结合曲波变换多尺度性,采用第二代快速离散曲波变换(FDCT),对航空瞬变电磁实测数据进行重构和去噪。首先建立带有异常体的三维理论模型,采用直接时间域瞬变电磁三维模拟程序进行正演; 然后对理论电磁响应数据添加3种不同噪声(随机噪声、方波噪声、工业噪声),通过曲波变换和重构,生成不同尺度的图像,低尺度反映大的背景场,高尺度反映局部细节或者高频噪声。通过信噪比和相对误差等参数,对重构后的数据进行去噪效果评估。最后将该方法应用到航空瞬变电磁实测数据中,并与其他3种传统去噪方法(中值滤波、奇异值分解、小波变换)进行对比。结果表明:对于含有随机噪声和工业噪声的原始数据,去噪后的相对误差在2.6%以下; 对于含有方波噪声的原始数据,去噪后的相对误差在6.5%以下,信噪比也高于传统去噪方法,证明第二代曲波变换可应用于航空瞬变电磁的数据去噪处理。

Abstract:

Noise interference seriously affects the data processing and imaging interpretation of aviation transient electromagnetic, and how to effectively denoise has become an important content of aviation transient electromagnetic research. Based on the characteristics of aviation transient electromagnetic noise and the multi-scale characteristics of curvelet transform, the second generation fast discrete curvelet transform(FDCT)was used to reconstruct and denoise actual aviation transient electromagnetic data. Firstly, a 3D theoretical model with anomalous bodies was established, and a direct time domain transient electromagnetic 3D simulation program was used for forward modeling. Then, three different types of noise, including random noise, square wave noise and industrial noise, were added to the theoretical electromagnetic response data, and images of different scales were generated through curvelet transform and reconstruction. Low scales reflect large background fields, while high scales reflect local details or high-frequency noise. Thirdly, the denoising effect of the reconstructed data was evaluated through parameters such as signal-to-noise ratio and relative error. Finally, the method was applied to the measured data of aviation transient electromagnetic and compared with several traditional denoising methods, including median filtering, singular value decomposition and wavelet transform. The results show that for the original data with random noise and industrial noise, the relative error after noise reduction is below 2.6%; for the original data with square wave noise, the relative error after noise reduction is below 6.5%, and the signal-to-noise ratio is also higher than traditional denoising methods, proving that the second generation curvelet transform can be applied to noise reduction of airborne transient electromagnetic data.

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相似文献/References:

备注/Memo

备注/Memo:

收稿日期:2023-02-22; 修回日期:2023-04-22投稿网址:http:∥jese.chd.edu.cn/
基金项目:国家自然科学基金项目(42174168); 陕西省自然科学基础研究计划项目(2021JM-159); 中央高校基本科研业务费专项资金项目(300102262201)
作者简介:蔺凯如(1999-),男,云南德宏人,工学硕士研究生,E-mail:3131697865@qq.com。
*通讯作者:张继锋(1978-),男,陕西蒲城人,长安大学教授,博士研究生导师,理学博士,E-mail:zjf0201@126.com。

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更新日期/Last Update: 2023-10-15