Journal of Earth Science

, Volume 29, Issue 6, pp 1372–1379 | Cite as

Seismic Attribute Analysis with Saliency Detection in Fractional Fourier Transform Domain

  • Yuqing Wang
  • Zhenming PengEmail author
  • Yan Han
  • Yanmin He
Geophysical Imaging from Subduction Zones to Petroleum Reservoirs


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 formation changes more obviously in the time direction. Therefore, one-dimensional Fourier transform is more suitable for seismic saliency detection. Fractional Fourier transform (FrFT) as an improved algorithm for Fourier transform, 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 information 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.

Key words

saliency detection spectral residual phase spectrum fractional Fourier transform (FrFT) attribute extraction seismic data 


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This work was supported by the National Natural Science Foundation of China (Nos. 61571096, 61775030, 41274127, 41301460, and 40874066). The final publication is available at Springer via

References Cited

  1. Achanta, R., Hemami, S., Estrada, F., et al., 2009. Frequency-Tuned Salient Region Detection. IEEE Conference on Computer Vision and Pattern Recognition, 1597–1604. Scholar
  2. Chen, Q., Sidney, S., 1997. Seismic Attribute Technology for Reservoir Forecasting and Monitoring. The Leading Edge, 16(5): 445–448. Scholar
  3. Chen, Y. P., Peng, Z. M., He, Z. H., et al., 2013. The Optimal Fractional Gabor Transform Based on the Adaptive Window Function and Its Application. Applied Geophysics, 10(3): 305–313. Scholar
  4. Chopra, S., Marfurt, K. J., 2005. Seismic Attributes—A Historical Perspective. Geophysics, 70(5): 3SO–28SO. Scholar
  5. Chopra, S., Marfurt, K. J., 2008. Emerging and Future Trends in Seismic Attributes. The Leading Edge, 27(3): 298–318. Scholar
  6. Ell, T. A., Sangwine, S. J., 2007. Hypercomplex Fourier Transforms of Color Images. IEEE Transactions on Image Processing, 16(1): 22–35. Scholar
  7. Goloshubin, G., Silin, D., Vingalov, V., et al., 2008. Reservoir Permeability from Seismic Attribute Analysis. The Leading Edge, 27(3): 376–381. Scholar
  8. Guo, C., Ma, Q., Zhang, L., 2008. Spatio-Temporal Saliency Detection Using Phase Spectrum of Quaternion Fourier Transform. IEEE Conference on Computer Vision and Pattern Recognition, 1–8. Scholar
  9. Hou, X., Zhang, L., 2007. Saliency Detection: A Spectral Residual Approach. IEEE Conference on Computer Vision and Pattern Recognition, 1–8. Scholar
  10. Kutay, A., Ozaktas, H. M., Ankan, O., et al., 1997. Optimal Filtering in Fractional Fourier Domains. IEEE Transactions on Signal Processing, 45(5): 1129–1143. Scholar
  11. Li, J., Levine, M. D., An, X. J., et al., 2013. Visual Saliency Based on Scale-Space Analysis in the Frequency Domain. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(4): 996–1010. Scholar
  12. Martin, G. S., 2004. The Marmousi 2 Model, Elastic Synthetic Data, and an Analysis of Imaging and AVO in a Structurally Complex Environment: [Dissertation]. University of Houston, Houston. 6–19Google Scholar
  13. Qi, S. X., Ma, J., Li, H., et al., 2014. Infrared Small Target Enhancement via Phase Spectrum of Quaternion Fourier Transform. Infrared Physics & Technology, 62: 50–58. Scholar
  14. Steeghs, P., Drijkoningen, G., 2001. Seismic Sequence Analysis and Attribute Extraction Using Quadratic Time-Frequency Representations. Geophysics, 66(6): 1947–1959. Scholar
  15. Tian, L., Peng, Z. M., 2014. Determining the Optimal Order of Fractional Gabor Transform Based on Kurtosis Maximization and Its Application. Journal of Applied Geophysics, 108: 152–158. Scholar
  16. Wang, C., Lu, Y. C., Huang, H. G., et al., 2015. New Seismic Attribute Technology for Predicting Dissolved Pore-Fracture of Deeply Buried Platform Margin Reef-Beach System in Northeast Sichuan Basin, China. Journal of Earth Science, 26(3): 373–383. Scholar
  17. Wang, Y. Q., Peng, Z. M., 2016. The Optimal Fractional S Transform of Seismic Signal Based on the Normalized Second-Order Central Moment. Journal of Applied Geophysics, 129: 8–16. Scholar
  18. Wang, Y. Q., Peng, Z. M., He, Y. M., 2015. Instantaneous Attributes Analysis of Seismic Signals Using Improved HHT. Journal of Earth Science, 26(4): 515–521. Scholar
  19. Yu, Y., Wang, B., Zhang, L., 2009. Pulse Discrete Cosine Transform for Saliency-Based Visual Attention. IEEE 8th International Conference on Development and Learning, 1–6. Scholar

Copyright information

© China University of Geosciences and Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  1. 1.School of Optoelectronic InformationUniversity of Electronic Science and Technology of China610054China
  2. 2.Center for Information GeoscienceUniversity of Electronic Science and Technology of ChinaChengduChina

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