Fracture prediction using prestack Q calculation and attenuation anisotropy
An Yong1,2
1. State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China.
2. CNPC Key Laboratory of Geophysical Prospecting, China University of Petroleum, Beijing 102249, China.
Abstract：
The analysis of fractured reservoirs is very important to hydrocarbon exploration. The quality factor Q is a parameter used to characterize the attenuation of seismic waves in subsurface media. Q not only reflects the inherent properties of the medium but also is used to make predictions regarding reservoir fractures. Compared with poststack seismic data, prestack seismic data contain detailed stratigraphic information of seismic attributes and data inversion in reservoirs. The extraction of absorption parameters from prestack data improves the accuracy of attenuation estimates. In this study, I present a new method for calculating Q based on the modified S transform (MST) using common midpoint (CMP) preprocessed gathers. First, I use the MST with adjustable time–frequency resolution to carry out a high-precision time–frequency analysis of prestack CMP gathers and derive the calculation formula for the improved S transform-based frequency spectrum ratio method. Then, I use the energy density ratio to calculate the slope of the frequency spectrum ratio instead of the conventional amplitude ratio. Thus, I establish the relation between the slope of the spectrum ratio and offset as well as eliminate the offset effect by multichannel linear fitting, obtaining accurate Q values from seismic prestack data. Finally, I use the proposed prestack Q extraction method to study the fractured reservoir in Qianjin burried hill and P-wave absorption and attenuation anisotropy with good results in the fracture characterization.
An Yong. Fracture prediction using prestack Q calculation and attenuation anisotropy[J]. APPLIED GEOPHYSICS, 2015, 12(3): 432-440.
[1]
Al- Marzoug, A., Neves, F. A., Kim, J. J., and Nebrija, E., 2006, P-wave anisotropy from azimuthal AVO and velocity estimates using 3D seismic data from Saudi Arabia: Geophysics, 71(2), E7-E11.
[2]
Askari, R., and Hejazi, S. H., 2014, Estimation of surface-wave group velocity using slant stack in the generalized S-transform domain: Geophysics, 80(4), EN83-EN92.
[3]
Bath, M., 1974, Spectral analysis in geophysics: Developments in solid Earth geophysics, vol. 7: Elsevier.
[4]
Behura, J., Tsvankin, I., Jenner, E., and Calvert, A., 2012, Estimation of interval velocity and attenuation anisotropy from reflection data at Coronation Field: The Leading Edge, 31(5), 580-587.
[5]
Clark, R. A., Benson, P. M., Carter, A. J., and Moreno, C. A. G., 2009, Anisotropic P-wave attenuation measured from a multi-azimuth surface seismic reflection survey: Geophysical Prospecting, 57, 835-845.
[6]
Dasgupta, R., and Clark, R. A., 1998, Estimation of Q from surface seismic reflection data: Geophysics, 63(6), 2120-2128.
[7]
Ekanem, A. M., Wei, J., Wang, S., Di, B., Li, X., and Chapman, M., 2009, Fracture detection using 2-D P-wave seismic data: A seismic physical modelling study: 79th SEG Annual Meeting, Expanded Abstracts, 2647-2651, Houston, USA.
[8]
Engelhard, L., 1996, Determination of the seismic wave attenuation by complex trace analysis: Geophysical Journal International, 125(2), 608-622.
[9]
Futterman, W. I., 1962, Dispersive body waves: Journal of Geophysical Research, 67(13), 5279-5291.
[10]
Li, D., and Castagna, J., 2013, Modified S-transform in time-frequency analysis of seismic data: 83rd Ann. Internat. Mtg., Soc. Explor. Geophys., Expanded Abstracts, 4629-4634.
[11]
Liu, E., Maultzsch, S., Chapman, M., Li, X., Queen, J., and Zhang, Z., 2003, Frequency-dependent seismic anisotropy and its implication for estimating fracture size in low porosity reservoirs, The Leading Edge, 22(7), 662-665.
[12]
Qu, S. L., Ji, Y. X., Wang, X., Wang, X. L., Chen, X. R., and Shen, G. Q., 2007, Fracture detection by using full azimuth P wave attributes: Applied Geophysics, 4(3), 238-243.
[13]
Quan, Y. L., and Harrisy, J. M., 1997, Seismic attenuation tomography using the frequency shift method: Geophysics, 62(3), 895-905.
[14]
Reine, C. M., van der Baan, and Clark, R., 2009, The robustness of seismic attenuation measurements using fixed- and variable-window timefrequency transforms: Geophysics, 74(2), WA123-WA135.
[15]
Ruger, A., 1998, Variation of P-wave reflectivity with offset and azimuth in anisotropic media: Geophysics, 63(3), 935-947.
[16]
Schoenberg, M. A., Dean, S., and Sayers, C. M., 1999, Azimuth dependent turning of seismic waves reflected from fractured reservoirs: Geophysics, 64(4), 1160-1171.
[17]
Shen, F., Sierra, J., Burns, D. R., and Toksöz, M. N., 2002, Azimuthal offsetdependent attributes applied to fracture detection in a carbonate reservoir: Geophysics, 67(2), 355-364.
[18]
Shekar, B., and Tsvankin, I., 2012, Anisotropic attenuation analysis of crosshole data generated during hydraulic fracturing: The Leading Edge, 31(5), 588-593.
[19]
Stockwell, R. G., Mansinha, L., and Lowe, R. P., 1996, Localization of the complex spectrum: The Stransform: IEEE Transactions on Signal Processing, 44(4), 998-1001
[20]
Wang, Z. J., Cao, S. Y., Zhang, H. R., Qu, Y. M., Yuan, D., Yang, J. H., and Shao, G. M., 2015, Estimation of quality factors by energy ratio method: Applied Geophysics, 12(1), 86-92.
[21]
White, R. E., 1992, The accuracy of estimating Q from seismic data: Geophysics, 57(1), 1508−1511.
[22]
Willis, M. E., Burns, D. R., Rao, R., Minsley, B., Toksöz, M. N., and Vetri, L., 2006, Spatial orientation and distribution of reservoir fractures from scattered seismic energy: Geophysics, 71(5), O43-O51.
[23]
Zhang, C., and Ulrych, T. J., 2002, Estimation of quality factor from CMP records: Geophysics, 67(5), 1542-1547.
[24]
Zheng, Y., Fang, X., Fehler, M. C., and Burns, D. R., 2013. Seismic characterization of fractured reservoirs by focusing Gaussian beams: Geophysics, 78(4), A23-28.
2015, Vol. 12 
