Strong Interference Elimination in Seismic Data Using Multivariate Variational Mode Extraction.

IF 3.4 3区 综合性期刊 Q2 CHEMISTRY, ANALYTICAL
Sensors Pub Date : 2024-11-20 DOI:10.3390/s24227399
Zhichao Yu, Yuyang Tan, Yiran Lv
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引用次数: 0

Abstract

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.

利用多变量变异模式提取消除地震数据中的强干扰。
在存在机械振动或电力设施的情况下采集的地震数据可能会受到强烈干扰的污染,从而大大降低数据的信噪比(S/N)。传统方法,如陷波滤波器和时频变换法,通常不足以抑制非稳态干扰噪声,如果过度处理,可能会扭曲有效信号。在本研究中,我们提出了一种消除地震数据中机械振动干扰的方法。在我们的方法中,我们将变异模态提取(VME)技术扩展为多变量形式,称为多变量变异模态提取(MVME),用于多道次地震数据的同步分析。通过对过程记录进行基于同步queezing的时频分析,确定干扰频率;利用具有最佳平衡因子的 MVME,从地震数据中提取并去除其相应的模式。我们使用合成数据研究了该方法的有效性以及调谐参数对处理结果的影响,然后将该方法应用于野外数据集。结果表明,与传统方法相比,所提出的方法能有效抑制机械振动干扰,提高信噪比,并加强对地震信号的极化分析。
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来源期刊
Sensors
Sensors 工程技术-电化学
CiteScore
7.30
自引率
12.80%
发文量
8430
审稿时长
1.7 months
期刊介绍: Sensors (ISSN 1424-8220) provides an advanced forum for the science and technology of sensors and biosensors. It publishes reviews (including comprehensive reviews on the complete sensors products), regular research papers and short notes. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
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