地球与行星物理论评（中英文）2025，Vol.56Issue(6)：665-673,9.DOI:10.19975/j.dqyxx.2024-055
基于逆自编码器和通道注意力机制的大地电磁信号去噪方法
Electromagnetic signal denoising method based on inverse autoencoder and channel attention mechanism
摘要
Abstract
The magnetotelluric(MT)method is a core technology widely used in geophysical exploration and commonly used in geological surveys,resource exploration and geodynamic research.However,MT data are sus-ceptible to complex noise,including nonlinear and non-stationary noise,which significantly reduces data quality and interpretation accuracy.Although traditional denoising methods(such as sparse representation and wavelet transform)can improve the quality of some data,they have limitations such as complex parameter adjustment and insufficient robustness when dealing with diverse noise types.In order to solve the above problems,this paper pro-poses an innovative MT data denoising method based on inverse autoencoder and channel attention mechanism.The inverse autoencoder enhances the ability to capture complex signal features through the process of dimension-ality increase and dimensionality reduction,achieving efficient signal-to-noise identification and signal fitting;the channel attention mechanism further improves denoising accuracy by dynamically adjusting the weight of feature channels.On this basis,an end-to-end deep learning framework is designed to process MT data in complex noisy environments.Experimental results show that this method exhibits superior denoising performance under a variety of noise conditions.It is significantly better than traditional methods in indicators such as correlation coefficient(CORC),normalized root mean square error(NRMSE)and signal-to-noise ratio(SNR);in addition,in the analysis of apparent resistivity-phase curve and electromagnetic field polarization direction,the method in this paper shows higher robustness and consistency.This shows that the method in this paper can effectively improve the quality and interpretability of MT data and provide reliable technical support for geophysical exploration.关键词
大地电磁信号去噪/深度学习/逆自编码器/通道注意力机制Key words
magnetotelluric signal denoising/deep learning/inverse autoencoder/channel attention mecha-nism分类
天文与地球科学引用本文复制引用
余年,计铭杰,张超..基于逆自编码器和通道注意力机制的大地电磁信号去噪方法[J].地球与行星物理论评（中英文）,2025,56(6):665-673,9.基金项目
国家自然科学基金优秀青年基金资助项目(42222404) （42222404）
国家重点研发项目课题(2023YFC2907104)Supported by the National Natural Science Foundation of China Excellent Young Scientist Fund Project(Grant No.42222404)and National Key Research and Development Program Project Topic(Grant No.2023YFC2907104) （2023YFC2907104）
