Abstract
In the field of seismic exploration, ground roll seriously affects the deep effective reflections from subsurface deep structures. Traditional curvelet transform cannot provide an adaptive basis function to achieve a suboptimal denoised result. In this paper, we propose a method based on empirical curvelet transform (ECT) for ground roll attenuation. Unlike the traditional curvelet transform, this method not only decomposes seismic data into multiscale and multi-directional components, but also provides an adaptive filter bank according to frequency content of seismic data itself. So, ground roll can be separated by using this method. However, as the frequency of reflection and ground roll components are close, we apply singular value decomposition (SVD) in the curvelet domain to differentiate the ground roll and reflection better. Examples of synthetic and field seismic data reveal that the proposed method based ECT performs better than the traditional curvelet method in terms of the suppression of ground roll.
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The authors thank Prof. Jerome Gilles for his useful Matlab package. We also express thanks to editor and anonymous reviewers who improved the manuscript with their comments.
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Yuan Huan is an engineer who received his B.S. in School of Geophysics and petroleum resources from Yangtze University in 2007, and gained his M.S. in China University of Petroleum (Beijing). Since 2010, he has been engaged in seismic data processing and method research in Research Institute of Petroleum Exploration and Development-Northwest.
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Yuan, H., Hu, ZD., Liu, Z. et al. Ground roll attenuation based on an empirical curvelet transform. Appl. Geophys. 15, 111–117 (2018). https://doi.org/10.1007/s11770-018-0658-9
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DOI: https://doi.org/10.1007/s11770-018-0658-9