Automatic identification of fake patterns caused by short-width wavelets in seismic data |
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| Authors: | Ahmed Mohamed Tawfiek Guanzheng TAN Ali G Hafez Abdullah Al-Amri Nassir Alarif Kamal Abdelrahman |
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| Institution: | 1.School of Information Science and Engineering,Central South University,Changsha,China;2.Seismology Department,National Research Institute of Astronomy and Geophysics,Cairo,Egypt;3.Department of Electrical Engineering, Faculty of Engineering,Nahda University,Bani Sweif,Egypt;4.Geology and Geophysics Department,King Saud University,Riyadh,Saudi Arabia |
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| Abstract: | Despite the popularity of using the Haar wavelet filter in many applications, it sometimes introduces fake patterns into the multi resolution analysis (MRA) of seismic data. In this work, we compared different wavelet filters to demonstrate that these patterns are fake and not part of the original waveforms and to show that they are a result of using the Haar wavelet filter as a short-width wavelet. To achieve this, many seismic waveforms from two different sources: the Egyptian National Seismic Network (ENSN) and the High Sensitivity Seismograph Network Japan (Hi-net) are used with different wavelet filters. We propose an algorithm based on an autoregressive (AR) model to detect these patterns automatically and fully. |
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