Influence of inaccurate wavelet phase estimation on seismic inversion
Yuan San-Yi1,2 and Wang Shang-Xu1,2
1. State Key Laboratory of Petroleum Resource and Prospecting, China University of Petroleum (Beijing), Beijing 102249, China.
2. CNPC Key Lab of Geophysical Exploration, China University of Petroleum (Beijing), Beijing 102249, China
Abstract On the assumption that the seismic wavelet amplitude spectrum is estimated accurately, a group of wavelets with different phase spectra, regarded as estimated wavelets,are used to implement linear least-squares inversion. During inversion, except for the wavelet phase, all other factors affecting inversion results are not taken into account. The inversion results of a sparse reflectivity model (or blocky impedance model) show that: (1) although the synthetic data using inversion results matches well with the original seismic data, the inverted refl ectivity and acoustic impedance are different from that of the real model. (2) the inversion result reliability is dependent on the estimated wavelet Z transform root distribution. When the estimated wavelet Z transform roots only differ from that of the real wavelet near the unit circle, the inverted reflectivity and impedance are usually consistent with the real model;(3) although the synthetic data matches well with the original data and the Cauchy norm (or modifi ed Cauchy norm) with a constant damping parameter has been optimized, the inverted results are still greatly different from the real model. Finally, we suggest using the L1 norm,Kurtosis, variation, Cauchy norm with adaptive damping parameter or/and modifi ed Cauchy norm with adaptive damping parameter as evaluation criteria to reduce the bad influence of inaccurate wavelet phase estimation and obtain good results in theory.
This research was financially supported by National Key Basic Research Development Program (Grant No. 2007CB209600) and National Major Science and Technology Program (Grant No. 2008ZX05010-002).
Cite this article:
YUAN San-Yi,WANG Shang-Xu. Influence of inaccurate wavelet phase estimation on seismic inversion[J]. APPLIED GEOPHYSICS, 2011, 8(1): 48-59.
[1]
Cooke, D. A., and Schneider, W. A., 1983, Generalized linear inversion of reflection seismic data: Geophysics, 48, 665 - 676.
[2]
Lu, W. K., and Liu, D. Q., 2007, Frequency recovery of bandlimited seismic data based on sparse spike train deconvolution: 77th Ann. Internat. Mtg., Soc. Explor. Geophys., Expanded Abstracts, 1977 - 1980.
[3]
Oldenburg, D. W., Scheuer, T., and Levy, S., 1983, Recovery of the acoustic impedance from reflection seismograms: Geophysics, 48, 1318 - 1337.
[4]
Puryear, C. I., and Castagna, J. P., 2008, Layer-thickness determination and stratigraphic interpretation using spectral inversion: Theory and application: Geophysics, 73, 37 - 48.
[5]
Sacchi, M. D., 1997, Reweighting strategies in seismic deconvolution: Geophysical Journal International, 129, 651 - 656.
[6]
Velis, D. R., 2008, Stochastic sparse-spike deconvolution: Geophysics, 73(1), R1 - R9.
[7]
Walker, C., and Ulrych, T. J., 1983, Autoregressive modeling of the acoustic impedance: Geophysics, 48(10), 1338 - 1350.
Yilmaz, O., 2001, Seismic data analysis: processing, inversion, and interpretation of seismic data (Volume I): Society of Exploration Geophysicists, 162 - 211.
[10]
Yuan, S. Y., and Wang, S. X., 2010, Noise attenuation without spatial assumptions about seismic coherent events: 80th Ann. Internat. Mtg., Soc. Explor. Geophys., Expanded Abstracts, 3524 - 3528.
[11]
Yuan, S. Y., Wang, S. X., and Tian, N., 2009, Swarm intelligence optimization and its application in geophysical data inversion: Applied Geophysics, 6(2), 166 - 174.
2011, Vol. 8 
