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Building a heterogeneous Q model: an approach using surface reflection data

JIN WANG1,2 WEI LIU1,2 JIANFENG ZHANG1 ZHONGHUA ZHAO3
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1 Institute of Geology and Geophysics, Key Laboratory of Petroleum Resources Research, Chinese Academy of Sciences, Beijing 100029, P.R. China. wangjin112@mails.uca s.ac.cn,
2 University of Chinese Academy of Sciences, Beijing 100029, P.R China.,
3 Exploration and Development Research Institute, Daqing Oilfield Company Ltd., Daqing 163712, P.R. China.,
JSE 2017, 26(4), 293–310;
Submitted: 15 August 2016 | Accepted: 27 November 2016 | Published: 1 August 2017
© 2017 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

Wang, J., Liu, W., Zhang, J. and Zhao, Z., 2017. Building a heterogeneous Q model: an approach using surface reflection data. Journal of Seismic Exploration, 26: 293-310. The anelasticity of a subsurface medium will cause dissipation of seismic energy. It is challenging to derive an interval Q model in the absence of VSP data and cross-well data. In this paper, we propose a method to derive the Q model using surface reflection data by introducing an effective Q model. Considering the existence of various types of noise, we estimate and evaluate the Q value in terms of compensation effects along with imaging resolution and noise level. Finally, we obtain an optimal compensation result with better resolution and wider bandwidth. Specifically, the effective Q model can be estimated using scanning technology at selected CDP locations to avoid the difficulties of determining a reference event and the thin-bed tuning effect in the conventional spectrum ratio method. The whole Q model can be obtained by a type of interpolation algorithm constrained by geological interfaces, which can be used in the de-absorption prestack time migration directly or in the de-absorption prestack depth migration with the proper time-to-depth conversion. Finally we demonstrate the effectiveness of the proposed approach using a field data example from eastern China. A high-resolution image is obtained.

Keywords
Q model
Q scanning
compensation effects
interpolation algorithm
References
  1. Aki, K. and Richards, P.G., 1980. Quantitative Seismology. W.H. Freeman & Co, San Francisco.
  2. Bickel, S.H. and Natarajan, R.R., 1985. Plane-wave Q deconvolution. Geophysics, 50: 1426-1437.
  3. Bleistein, N., 1984. Mathematical Methods for Wave Phenomena. Academic Press Inc., New York.
  4. Futterman, LW., 1962. Dispersive body waves. J. Geophys. Res., 67: 5279-5291.
  5. Hargreaves, N.D. and Calvert, A.J., 1991. Inverse Q filtering by Fourier transform. Geophysics,56: 519-527.
  6. Kjartansson, E. 1979. Constant Q-wave propagation and attenuation. J. Geophys. Res., 84:4737-4748.
  7. Lu, W.K., Zhang, W.P. and Liu, D.Q., 2006. Local linear coherent noise attenuation based on localpolynomial approximation. Geophysics, 71: V163-V169.310 WANG, LIU, ZHANG & ZHAO
  8. Cameron, M., Fomel, S. and Sethian, J., 2008. Time-to-depth conversion and seismic velocityestimation using time-migration velocity. Geophysics, 73: VE205-VE210.
  9. Mittet, R., Sollie, R. and Hokstak, K., 1995. Prestack depth migration with compensation forabsorption and dispersion. Geophysics, 60: 1485-1494.
  10. Youli, Q. and Harris, J.M., 1997. Seismic attenuation tomography using the frequency shift method.Geophysics, 62: 895-905.
  11. Dasgupta, R. and Clark,R.A., 1998. Estimation of Q from surface seismic reflection data.Geophysics, 63: 2120-2128.
  12. Rainer, T., 1989. Comparison of seven methods for the computation of Q. Phys. Earth Planet.Inter., 55: 259-268.
  13. Wang, Y., 2002. A stable and efficient approach of inverse Q filtering. Geophysics, 67: 657-663.
  14. Wang, S., Yang, D., Li, D.F. and Song, H.J., 2015. Q factor estimation based on the method oflogarithmic spectral area difference. Geophysics, 80: V157-V171.
  15. Waters, K.H., 1978. Reflection Seismology: A tool for Energy Resource Exploration. John Wileyand Sons, New York.
  16. Zhang, C.J. and Ulrych, T.J., 2002. Estimation of quality factors from CMP records. Geophysics,67: 1542-1547.
  17. Zhang, J.F. and Wapenaar, C.P.A.. 2002. Wavefield extrapolation and prestack depth migration inanelastic inhomogeneous media. Geophys. Prosp., 50: 629-643.
  18. Zhang, J.F., Wu, J.Z. and Li, X.Y., 2013. Compensation for absorption and dispersion in prestackmigration. An effective Q approach. Geophysics, 78: S1-S14.
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Journal of Seismic Exploration, Electronic ISSN: 0963-0651 Print ISSN: 0963-0651, Published by AccScience Publishing