MFIEN: multi-scale feature interactive enhancement network for seismic data denoising in desert areas
Abstract Due to complex acquisition environments and geological conditions, in desert seismic data, the background noise is always intense and overlaps with the frequency range of the seismic signals. This severely blurs the seismic signals, bringing challenges to accurately extract desired reflecti...
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Nature Portfolio
2025-02-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-87481-y |
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| author | Tie Zhong Yuxin Ye |
| author_facet | Tie Zhong Yuxin Ye |
| author_sort | Tie Zhong |
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| description | Abstract Due to complex acquisition environments and geological conditions, in desert seismic data, the background noise is always intense and overlaps with the frequency range of the seismic signals. This severely blurs the seismic signals, bringing challenges to accurately extract desired reflection information. Effectively suppressing random noise and significantly optimizing the signal-to-noise ratio (SNR) is emerging as a key issue in seismic data processing. A Multi-scale Feature Interaction Enhancement Network (MFIEN) for intense background seismic noise attenuation in desert areas is proposed in this paper to address this problem. In general, MFIEN has a multi-scale feature interaction structure that combines feature information from different layers and captures distinct features through effective information integration. Furthermore, a fusion feature enhancement module (FFEM), incorporating dilated convolutions and convolutions with different kernel sizes, is proposed. This expands the receptive field without changing the size of the feature maps, thereby preserving the structural features of seismic records more effectively. Both synthetic and field desert data denoising results indicate that MFIEN can accurately suppress intense background noise and effectively recover weak signals, significantly enhancing the quality of seismic data. |
| format | Article |
| id | doaj-art-97c5340253984ffc9de04ebbf715e5a0 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-97c5340253984ffc9de04ebbf715e5a02025-02-02T12:21:39ZengNature PortfolioScientific Reports2045-23222025-02-0115111510.1038/s41598-025-87481-yMFIEN: multi-scale feature interactive enhancement network for seismic data denoising in desert areasTie Zhong0Yuxin Ye1Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology (Ministry of Education), Department of Communication Engineering, College of Electric Engineering, Northeast Electric Power UniversityKey Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology (Ministry of Education), Department of Communication Engineering, College of Electric Engineering, Northeast Electric Power UniversityAbstract Due to complex acquisition environments and geological conditions, in desert seismic data, the background noise is always intense and overlaps with the frequency range of the seismic signals. This severely blurs the seismic signals, bringing challenges to accurately extract desired reflection information. Effectively suppressing random noise and significantly optimizing the signal-to-noise ratio (SNR) is emerging as a key issue in seismic data processing. A Multi-scale Feature Interaction Enhancement Network (MFIEN) for intense background seismic noise attenuation in desert areas is proposed in this paper to address this problem. In general, MFIEN has a multi-scale feature interaction structure that combines feature information from different layers and captures distinct features through effective information integration. Furthermore, a fusion feature enhancement module (FFEM), incorporating dilated convolutions and convolutions with different kernel sizes, is proposed. This expands the receptive field without changing the size of the feature maps, thereby preserving the structural features of seismic records more effectively. Both synthetic and field desert data denoising results indicate that MFIEN can accurately suppress intense background noise and effectively recover weak signals, significantly enhancing the quality of seismic data.https://doi.org/10.1038/s41598-025-87481-ySeismic noise attenuationSpectrum-aliasing noiseLow signal-to-noise ratio (SNR)Multi-scale feature interaction enhancement networkDesert-area seismic data |
| spellingShingle | Tie Zhong Yuxin Ye MFIEN: multi-scale feature interactive enhancement network for seismic data denoising in desert areas Scientific Reports Seismic noise attenuation Spectrum-aliasing noise Low signal-to-noise ratio (SNR) Multi-scale feature interaction enhancement network Desert-area seismic data |
| title | MFIEN: multi-scale feature interactive enhancement network for seismic data denoising in desert areas |
| title_full | MFIEN: multi-scale feature interactive enhancement network for seismic data denoising in desert areas |
| title_fullStr | MFIEN: multi-scale feature interactive enhancement network for seismic data denoising in desert areas |
| title_full_unstemmed | MFIEN: multi-scale feature interactive enhancement network for seismic data denoising in desert areas |
| title_short | MFIEN: multi-scale feature interactive enhancement network for seismic data denoising in desert areas |
| title_sort | mfien multi scale feature interactive enhancement network for seismic data denoising in desert areas |
| topic | Seismic noise attenuation Spectrum-aliasing noise Low signal-to-noise ratio (SNR) Multi-scale feature interaction enhancement network Desert-area seismic data |
| url | https://doi.org/10.1038/s41598-025-87481-y |
| work_keys_str_mv | AT tiezhong mfienmultiscalefeatureinteractiveenhancementnetworkforseismicdatadenoisingindesertareas AT yuxinye mfienmultiscalefeatureinteractiveenhancementnetworkforseismicdatadenoisingindesertareas |