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Volume 29 Issue 6
Nov 2018
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Yuqing Wang, Zhenming Peng, Yan Han, Yanmin He. Seismic Attribute Analysis with Saliency Detection in Fractional Fourier Transform Domain. Journal of Earth Science, 2018, 29(6): 1372-1379. doi: 10.1007/s12583-017-0811-z
Citation: Yuqing Wang, Zhenming Peng, Yan Han, Yanmin He. Seismic Attribute Analysis with Saliency Detection in Fractional Fourier Transform Domain. Journal of Earth Science, 2018, 29(6): 1372-1379. doi: 10.1007/s12583-017-0811-z

Seismic Attribute Analysis with Saliency Detection in Fractional Fourier Transform Domain

doi: 10.1007/s12583-017-0811-z
Funds:

the National Natural Science Foundation of China 40874066

the National Natural Science Foundation of China 41301460

the National Natural Science Foundation of China 61571096

the National Natural Science Foundation of China 61775030

the National Natural Science Foundation of China 41274127

More Information
  • Corresponding author: Zhenming Peng
  • Received Date: 30 Sep 2016
  • Accepted Date: 15 Apr 2017
  • Publish Date: 01 Dec 2018
  • Most image saliency detection models are dependent on prior knowledge and demand high computational cost. However, spectral residual (SR) and phase spectrum of the Fourier transform (PFT) models are simple and fast saliency detection approaches based on two-dimensional Fourier transform without the prior knowledge. For seismic data, the geological structure of the underground rock for-mation changes more obviously in the time direction. Therefore, one-dimensional Fourier transform is more suitable for seismic saliency detection. Fractional Fourier transform (FrFT) is an improved algo-rithm for Fourier transform, therefore we propose the seismic SR and PFT models in one-dimensional FrFT domain to obtain more detailed saliency maps. These two models use the amplitude and phase in-formation in FrFT domain to construct the corresponding saliency maps in spatial domain. By means of these two models, several saliency maps at different fractional orders can be obtained for seismic attribute analysis. These saliency maps can characterize the detailed features and highlight the object areas, which is more conducive to determine the location of reservoirs. The performance of the proposed method is assessed on both simulated and real seismic data. The results indicate that our method is effective and convenient for seismic attribute extraction with good noise immunity.

     

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