Abstract
Deconvolution is widely used to increase the resolution of seismic data. To compare the resolution ability of conventional spectrum whitening deconvolution to thin layers with that of well-driven deconvolution, a complex sedimentary geological model was designed, and then the simulated seismic data were processed respectively by each of the two methods. The amplitude spectrum of seismic data was almost white after spectrum whitening, but the wavelet resolution was low. The amplitude spectrum after well-driven deconvolution deviated from white spectrum, but the wavelet resolution was high. Further analysis showed that if an actual reflectivity series could not well satisfy the hypothesis of white spectrum, spectrum whitening deconvolution had a potential risk of wavelet distortion, which might lead to a pitfall in high resolution seismic data interpretation. On the other hand, the wavelet after well-driven deconvolution had higher resolution both in the time and frequency domains. It is favorable for high resolution seismic interpretation and reservoir prediction.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Baan M V. Time-varying wavelet estimation and deconvolution by kurtosis maximization. Geophysics. 2008. 73(2): 11–18
Baan M V and Pham D T. Robust wavelet estimation and blind deconvolution of noisy surface seismics. Geophysics. 2008. 73(5): 37–46
Chen C R and Zhou X X. Improving resolution of seismic data using wavelet spectrum whitening. Oil Geophysical Prospecting. 2000. 35(6): 703–709 (in Chinese)
Jia L H, Wu C J, Luo Y X, et al. High resolution seismic data processing techniques. Geophysical Prospecting for Petroleum. 2002. 41(4): 484–488 (in Chinese)
Kaderali A, Jones M and Howlett J. White Rose seismic with well data constraints: A case history. The Leading Edge. 2007. 26(6): 742–754
Li G F, Mou Y G and Wang P. A interactive technique for seismic wavelet extraction. Journal of China University of Petroleum (Edition of Natural Science). 2005. 29(5): 33–36 (in Chinese)
Li G F, Mou Y G, Liu Y Q, et al. Spectrum-modulated technique. Oil Geophysical Prospecting. 2001. 36(5): 597–601 (in Chinese)
Li G F, Xiong J L, Zhou H, et al. Seismic reflection characteristics of fluvial sand and shale interbedded layers. Applied Geophysics. 2008. 5(3): 219–229
Mou Y G, Chen X H, Li G F, et al. Seismic Data Processing. Beijing: Petroleum Industry Press. 2007. 70–75 (in Chinese)
Rosa A L R and Ulrych T J. Processing via spectral modeling. Geophysics. 1991. 56(8): 1244–1251
Spikes K, Dvorkin J and Schneider M. From seismic traces to reservoir properties: Physics-driven inversion. The Leading Edge. 2008. 27(4): 456–461
Velis D R. Stochastic sparse-spike deconvolution. Geophysics. 2008. 73(1): 1–9
Walden A T and Hosken J W J. An investigation of the spectral properties of primary reflection coefficients. Geophysical Prospecting. 1985. 33(3): 400–435
Wang Y H. Inverse Q-filter for seismic resolution enhancement. Geophysics. 2006. 71(3): 51–60
Zhao B, Yu S P, Nie X B, et al. Spectral-modeled deconvolution and its application. Oil Geophysical Prospecting. 1996. 31(1): 101–113 (in Chinese)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Li, G., Zhou, H. & Zhao, C. Potential risks of spectrum whitening deconvolution — Compared with well-driven deconvolution. Pet. Sci. 6, 146–152 (2009). https://doi.org/10.1007/s12182-009-0023-y
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12182-009-0023-y