Signal-to-noise ratio application to seismic marker analysis and fracture detection
Xu Hui-Qun1,2 and Gui Zhi-Xian1,2
1. Key Laboratory of Exploration Technologies for Oil and Gas Resources, Ministry of Education, Yangtze University, Hubei, Wuhan 430100, China.
2. School of Geophysics & Oil Resources, Yangtze University, Hubei, Wuhan 430100, China.
Abstract:
Seismic data with high signal-to-noise ratios (SNRs) are useful in reservoir exploration. To obtain high SNR seismic data, significant effort is required to achieve noise attenuation in seismic data processing, which is costly in materials, and human and financial resources. We introduce a method for improving the SNR of seismic data. The SNR is calculated by using the frequency domain method. Furthermore, we optimize and discuss the critical parameters and calculation procedure. We applied the proposed method on real data and found that the SNR is high in the seismic marker and low in the fracture zone. Consequently, this can be used to extract detailed information about fracture zones that are inferred by structural analysis but not observed in conventional seismic data.
XU Hui-Qun,GUI Zhi-Xian. Signal-to-noise ratio application to seismic marker analysis and fracture detection[J]. APPLIED GEOPHYSICS, 2014, 11(1): 73-79.
[1]
Abma, R., and Claerbout, J., 1995, Lateral prediction for noise attenuation by tx and fx techniques, Geophysics: 60(6), 1887 - 1896.
[2]
Alsdorf, D., 1997, Noise reduction in seismic data using Fourier correlation coefficient filtering: Geophysics, 62(5), 1617 - 1627.
[3]
aacute;lvarez-Díaz, M., López-Valcarce, R., and Mosquera, C., 2010, SNR estimation for multilevel constellations using higher-order moments: IEEE Transactions on Signal Processing, 58(3), 1515 - 1526.
[4]
Bagaini, C., Bunting, T., El-Emam, A., Laake, A., and Strobbia, C., 2010, Land seismic techniques for high-quality data: Oilfield Review, 22(2).
[5]
Bekara, M., and van der Baan, M., 2009, Random and coherent noise attenuation by empirical mode decomposition: Geophysics, 74(5), V89 - V98.
[6]
Canales, L. L., 1984, Random noise reduction: 54th Ann. Inter nat Mtg. Soc. Expl. Geophys., Expanded Abstracts, 525 - 527.
[7]
Chen, Z. D., Duan, T. Y., and Zhu, G. S., 1994, Improvement of singular value decomposition and the application: Oil Geophysical Prospecting, 29(6), 783 - 792.
[8]
Dash, B. P., and Obaidullah, K. A., 1970, Determination of signal and noise statistics using correlation theory: Geophysics, 35(1), 24 - 32.
[9]
Fountain, D. M., Hurich, C. A., and Smithson, S. B., 1984, Seismic reflectivity of mylonite zones in the crust: Geology, 12(4), 195 - 198.
[10]
Fu, L. Y., 2009, Quantitative assessment of the complexity of geological structures in terms of seismic propagators: Sci China Ser D-Earth Sci, 39(9), 1179 - 1190.
[11]
Herrmann, F. J., and Hennenfent, G., 2008, Non-parametric seismic data recovery with curvelet frames: Geophysical Journal International, 173(1), 233 - 248.
[12]
Hornbostel, S., 1991, Spatial prediction filtering in the tx and fx domains: Geophysics, 56(12), 2019 - 2026.
[13]
Hu, T. Y., Wang, R. Q., and White, R. E., 2000, Beam-forming in seismic data Processing: Chinese Journal of Geophysics, 43(1), 105 - 115.
[14]
Kelamis, P. G., and Verschuur, D. J., 2000, Surface-related multiple elimination on land seismic data-Strategies via case studies: Geophysics, 65(3), 719 - 734.
[15]
Larner, K., Chambers, R., Yang, M., Lynn, W., and Wai, W., 1983, Coherent noise in marine seismic data. Geophysics, 48(7), 854 - 886.
[16]
Li, Y., Yang, B. J., Lin, H. B., Yuan, Y., Hao, X., and Liu, X. H., 2008, Characteristics of hyperbolic time-distance relation filter in seismic prospecting and its ability increasing signal-to-noise ratio: Chinese Journal of Geophysics, 51(5), 1557 - 1566.
[17]
Lu, Y. H., and Lu, W. K., 2009, Edge-preserving polynomial fitting method to suppress random seismic noise: Geophysics, 74(4), V69 - V73.
[18]
Neelamani, R., Baumstein, A. I., Gillard, D. G., Hadidi, M. T., and Soroka, W. L., 2008, Coherent and random noise attenuation using the curvelet transform: The Leading Edge, 27(2), 240 - 248.
[19]
Rictsch, E., 1980, Estimation of the signal-to-noise ratio of seismic data with an application on to stacking: Geophysics prospecting, 28(4), 531 - 550.
[20]
Sejdi?, E., Djurovi?, I., and Stankovi?, L., 2011, Fractional Fourier transform as a signal processing tool: An overview of recent developments: Signal Processing, 91(6), 1351 - 1369.
[21]
Yu, S. P., Zha, Z. Q., and Liang, J., 1984, Frequency reinforcement filtering: Oil Geophysical Prospecting, 19(3), 200 - 209.
[22]
Zhang, J. H., Zang, S. T., Zhou, Z. X., Wang, J., Shan, L. Y., Xu, H., Fu, J. R., Yu, H. B., and Bu, C. C., 2009, Quantitative computation and comparison of S/N ratio in seismic data: Oil Geophysical Prospecting, 44(4), 48-486.