Abstract
Conventional f−x empirical mode decomposition (EMD) is an effective random noise attenuation method for use with seismic profiles mainly containing horizontal events. However, when a seismic event is not horizontal, the use of f−x EMD is harmful to most useful signals. Based on the framework of f−x EMD, this study proposes an improved denoising approach that retrieves lost useful signals by detecting effective signal points in a noise section using local similarity and then designing a weighting operator for retrieving signals. Compared with conventional f−x EMD, f−x predictive filtering, and f−x empirical mode decomposition predictive filtering, the new approach can preserve more useful signals and obtain a relatively cleaner denoised image. Synthetic and field data examples are shown as test performances of the proposed approach, thereby verifying the effectiveness of this method.
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This research is supported by the National Natural Science Foundation of China (No. 41274137) and the National Engineering Laboratory of Offshore Oil Exploration.
Gan Shu-Wei is currently a postgraduate student of Geophysical Prospecting at the China University of Petroleum (Beijing). He received a B.S. in Mechanical Engineering at Nanjing University of Aeronautics and Astronautics in 2012. His research area is that of seismic signal processing, which mainly includes seismic data denoising, interpolation, and simultaneous source data deblending.
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Gan, SW., Wang, SD., Chen, YK. et al. Improved random noise attenuation using f−x empirical mode decomposition and local similarity. Appl. Geophys. 13, 127–134 (2016). https://doi.org/10.1007/s11770-016-0545-1
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DOI: https://doi.org/10.1007/s11770-016-0545-1