Dictionary learning and shift-invariant sparse coding denoising for controlled-source electromagnetic data combined with complementary ensemble empirical mode …

G Li, Z He, J Tang, J Deng, X Liu, H Zhu - Geophysics, 2021 - library.seg.org
Controlled-source electromagnetic (CSEM) data recorded in industrialized areas are
inevitably contaminated by strong cultural noise. Traditional noise attenuation methods are …

Mapping of fault and hydrothermal system beneath the seulawah volcano inferred from a magnetotellurics structure

M Marwan, M Yanis, GS Nugraha, M Zainal… - Energies, 2021 - mdpi.com
Magnetotellurics (MT) is an important geophysical method for exploring geothermal systems,
with the Earth resistivity obtained from the MT method proving to be useful for the …

Improved shift-invariant sparse coding for noise attenuation of magnetotelluric data

G Li, X Liu, J Tang, J Deng, S Hu, C Zhou… - Earth, Planets and …, 2020 - Springer
Magnetotelluric (MT) method is widely used for revealing deep electrical structure. However,
natural MT signals are susceptible to cultural noises. In particular, the existing data …

High-resolution LA-ICP-MS mapping of deep-sea polymetallic micronodules and its implications on element mobility

D Li, Y Fu, Q Liu, JR Reinfelder, P Hollings, X Sun… - Gondwana …, 2020 - Elsevier
Enrichments of REY (rare earth+ yttrium) and other trace metals (Co and Ni) in deep-sea
ferromanganese (Fesingle bond Mn) micronodules have received increasing attention in …

Research on a multiscale denoising method for low signal-to-noise magnetotelluric signal

Z Guo, X Gong, J Han, L Liu, Y Wu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Magnetotelluric (MT) impedance estimation requires a high signal-to-noise ratio (SNR).
When low-SNR data are processed, it is difficult to obtain a robust MT response. In this …

Deep learning optimized dictionary learning and its application in eliminating strong magnetotelluric noise

G Li, X Gu, Z Ren, Q Wu, X Liu, L Zhang, D Xiao… - Minerals, 2022 - mdpi.com
The noise suppression method based on dictionary learning has shown great potential in
magnetotelluric (MT) data processing. However, the constraints used in the existing …

[HTML][HTML] Synthesizing magnetotelluric time series based on forward modeling

P Wang, X Chen, Y Zhang - Frontiers in Earth Science, 2023 - frontiersin.org
The validity of magnetotelluric time-series processing methods has been lacking reasonable
testing criteria. Since the time series synthesized by existing techniques are not fully derived …

Low-Frequency Magnetotelluric Data Denoising Using Improved Denoising Convolutional Neural Network and Gated Recurrent Unit

G Li, X Gu, C Chen, C Zhou, D Xiao… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The magnetotelluric (MT) signals are susceptible to anthropogenic noise and the existing
denoising methods have significant shortcomings in low-frequency situations. To address …

Magnetotelluric noise attenuation using a deep residual shrinkage network

G Zuo, Z Ren, X Xiao, J Tang, L Zhang, G Li - Minerals, 2022 - mdpi.com
Magnetotelluric (MT) surveying is an essential geophysical method for mapping subsurface
electrical conductivity structures. The MT signal is susceptible to cultural noise, and the …

Identification and Suppression of Multi-component Noise in Audio Magnetotelluric based on Convolutional Block Attention Module

L Zhang, G Li, H Chen, J Tang, G Yang… - … on Geoscience and …, 2024 - ieeexplore.ieee.org
Audio magnetotelluric (AMT) is commonly used in mineral resource exploration. However,
the weak energy of AMT signals makes them susceptible to being overwhelmed by noise …