Abstract
Signal to noise ratio (SNR) and resolution are two important but contradictory characteristics used to evaluate the quality of seismic data. For relatively preserving SNR while enhancing resolution, the signal purity spectrum is introduced, estimated, and used to define the desired output amplitude spectrum after deconvolution. Since a real reflectivity series is blue rather than white, the effects of white reflectivity hypothesis on wavelets are experimentally analyzed and color compensation is applied after spectrum whitening. Experiments on real seismic data indicate that the cascade of the two processing stages can improve the ability of seismic data to delineate the geological details.
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This research was financially supported by the National Natural Science Foundation of China (Grant No. 41174117) and PetroChina Innovation Foundation (Grant No. 2010D-5006-0301).
Li Guo-Fa received a B. S. in Geophysics from Changchun Geology College in 1987, PhD from China University of Petroleum (Beijing) in 2002, and Postdoctoral from China University of Mining (Beijing) in 2005. He currently works in China University of Petroleum (Beijing) as an Associate Professor. His research work mainly focuses on high resolution seismic data processing and complex structure seismic imaging.
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Li, GF., Peng, GX., Yue, Y. et al. Signal-purity-spectrum-based colored deconvolution. Appl. Geophys. 9, 333–340 (2012). https://doi.org/10.1007/s11770-012-0346-0
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DOI: https://doi.org/10.1007/s11770-012-0346-0