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1- Kharazmi University , e.pegah@khu.ac.ir
2- Kharazmi University
Abstract:   (284 Views)
Random noise reduction has always been one of the most important issues in seismic data processing. This study investigates one of the most effective random noise reduction methods, the 2D multi-stage median filter. This filter is applied to seismic data by applying a series of 1D median filters in different directions and then selecting the output value corresponding to the center of the 2D window. By applying a 2D multi-stage median filter to both synthetic and real data, it is shown that the filter can effectively attenuate random spike-like noise in both pre-stack and post-stack data. Similarly, based on spectral analysis, it is shown that this filter does a good job of reducing the level of high frequency random noise in both synthetic and real data. In this study, a 2D median filter is applied to synthetic data containing random noise with a density of 10%. Since increasing the filter length can damage useful signals in addition to attenuating random noise, it is important to specify an appropriate filter length. For synthetic data, the error ratio plot shows that a filter length of 9 points is appropriate for the first stage. In the second stage, a 2D median filter with a length of 7 points was applied to the output of the first stage filter. The effect of this filter on random noise suppression can then be observed by spectral analysis. In addition, median filters of 7 points and 5 points were applied to the pre-stack and post-stack real data, respectively. The effect and efficiency of this filter is assessed by examining the resulting difference plots, sections and spectral analysis.
     
Type of Study: Original Research | Subject: En. Geophisic
Received: 2024/11/12 | Accepted: 2024/12/1

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