Buchumschlag

An Adaptive Decomposition Method with Low Parameter Sensitivity for Non-Stationary Noise Suppression in Magnetotelluric Data

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Veröffentlicht in:Minerals vol. 15, no. 8 (2025), p. 808-830
1. Verfasser: Guo Zhenyu
Weitere Verfasser: Huang, Cheng, Jiang, Wen, Hong, Tao, Han Jiangtao
Veröffentlicht:
MDPI AG
Schlagworte:
Mineral exploration
Kurtosis
Data processing
Wavelet transforms
Parameter sensitivity
Optimization
Signal processing
Data analysis
Statistical methods
Time series
Lagrange multiplier
Spectrum analysis
Fourier transforms
Time-frequency analysis
Noise sensitivity
Noise reduction
Frequency domain analysis
Decomposition
Algorithms
Synthetic data
Energy distribution
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Abstract:Magnetotelluric (MT) sounding is a crucial technique in mineral exploration. However, MT data are highly susceptible to various types of noise. Traditional data processing methods, which rely on the assumption of signal stationarity, often result in severe distortion when suppressing non-stationary noise. In this study, we propose a novel, adaptive, and less parameter-dependent signal decomposition method for MT signal denoising, based on time–frequency domain analysis and the application of modal decomposition. The method uses Variational Mode Decomposition (VMD) to adaptively decompose the MT signal into several intrinsic mode functions (IMFs), obtaining the instantaneous time–frequency energy distribution of the signal. Subsequently, robust statistical methods are introduced to extract the independent components of each IMF, thereby identifying signal and noise components within the decomposition results. Synthetic data experiments show that our method accurately separates high-amplitude non-stationary interference. Furthermore, it maintains stable decomposition results under various parameter settings, exhibiting strong robustness and low parameter dependency. When applied to field MT data, the method effectively filters out non-stationary noise, leading to significant improvements in both apparent resistivity and phase curves, indicating its practical value in mineral exploration.
ISSN:2075-163X
DOI:10.3390/min15080808
Quelle:ABI/INFORM Global