Strong Interference Elimination in Seismic Data Using Multivariate Variational Mode Extraction
Seismic data acquired in the presence of mechanical vibrations or power facilities may be contaminated by strong interferences, significantly decreasing the data signal-to-noise ratio (S/N). Conventional methods, such as the notch filter and time-frequency transform method, are usually inadequate fo...
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MDPI AG
2024-11-01
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| author | Zhichao Yu Yuyang Tan Yiran Lv |
| author_facet | Zhichao Yu Yuyang Tan Yiran Lv |
| author_sort | Zhichao Yu |
| collection | DOAJ |
| description | Seismic data acquired in the presence of mechanical vibrations or power facilities may be contaminated by strong interferences, significantly decreasing the data signal-to-noise ratio (S/N). Conventional methods, such as the notch filter and time-frequency transform method, are usually inadequate for suppressing non-stationary interference noises, and may distort effective signals if overprocessing. In this study, we propose a method for eliminating mechanical vibration interferences in seismic data. In our method, we extended the variational mode extraction (VME) technique to a multivariate form, called multivariate variational mode extraction (MVME), for synchronous analysis of multitrace seismic data. The interference frequencies are determined via synchrosqueezing-based time-frequency analysis of process recordings; their corresponding modes are extracted and removed from seismic data using MVME with optimal balancing factors. We used synthetic data to investigate the effectiveness of the method and the influence of tuning parameters on processing results, and then applied the method to field datasets. The results have demonstrated that, compared with the conventional methods, the proposed method could effectively suppress the mechanical vibration interferences, improve the S/Ns and enhance polarization analysis of seismic signals. |
| format | Article |
| id | doaj-art-ececeea65fef4798a4c5131d1994a5e6 |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj-art-ececeea65fef4798a4c5131d1994a5e62025-08-20T02:04:41ZengMDPI AGSensors1424-82202024-11-012422739910.3390/s24227399Strong Interference Elimination in Seismic Data Using Multivariate Variational Mode ExtractionZhichao Yu0Yuyang Tan1Yiran Lv2Key Laboratory of Deep Petroleum Intelligent Exploration and Development, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, ChinaFrontiers Science Center for Deep Ocean Multispheres and Earth System, Key Lab of Submarine Geosciences and Prospecting Techniques MOE, College of Marine Geosciences, Ocean University of China, Qingdao 266100, ChinaKey Laboratory of Deep Petroleum Intelligent Exploration and Development, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, ChinaSeismic data acquired in the presence of mechanical vibrations or power facilities may be contaminated by strong interferences, significantly decreasing the data signal-to-noise ratio (S/N). Conventional methods, such as the notch filter and time-frequency transform method, are usually inadequate for suppressing non-stationary interference noises, and may distort effective signals if overprocessing. In this study, we propose a method for eliminating mechanical vibration interferences in seismic data. In our method, we extended the variational mode extraction (VME) technique to a multivariate form, called multivariate variational mode extraction (MVME), for synchronous analysis of multitrace seismic data. The interference frequencies are determined via synchrosqueezing-based time-frequency analysis of process recordings; their corresponding modes are extracted and removed from seismic data using MVME with optimal balancing factors. We used synthetic data to investigate the effectiveness of the method and the influence of tuning parameters on processing results, and then applied the method to field datasets. The results have demonstrated that, compared with the conventional methods, the proposed method could effectively suppress the mechanical vibration interferences, improve the S/Ns and enhance polarization analysis of seismic signals.https://www.mdpi.com/1424-8220/24/22/7399mechanical vibrationinterference eliminationseismic datamultivariate variational mode extraction |
| spellingShingle | Zhichao Yu Yuyang Tan Yiran Lv Strong Interference Elimination in Seismic Data Using Multivariate Variational Mode Extraction Sensors mechanical vibration interference elimination seismic data multivariate variational mode extraction |
| title | Strong Interference Elimination in Seismic Data Using Multivariate Variational Mode Extraction |
| title_full | Strong Interference Elimination in Seismic Data Using Multivariate Variational Mode Extraction |
| title_fullStr | Strong Interference Elimination in Seismic Data Using Multivariate Variational Mode Extraction |
| title_full_unstemmed | Strong Interference Elimination in Seismic Data Using Multivariate Variational Mode Extraction |
| title_short | Strong Interference Elimination in Seismic Data Using Multivariate Variational Mode Extraction |
| title_sort | strong interference elimination in seismic data using multivariate variational mode extraction |
| topic | mechanical vibration interference elimination seismic data multivariate variational mode extraction |
| url | https://www.mdpi.com/1424-8220/24/22/7399 |
| work_keys_str_mv | AT zhichaoyu stronginterferenceeliminationinseismicdatausingmultivariatevariationalmodeextraction AT yuyangtan stronginterferenceeliminationinseismicdatausingmultivariatevariationalmodeextraction AT yiranlv stronginterferenceeliminationinseismicdatausingmultivariatevariationalmodeextraction |