Abstract Sparsity constrained deconvolution can improve the resolution of band-limited seismic data compared to conventional deconvolution. However, such deconvolution methods result in nonunique solutions and suppress weak reflections. The Cauchy function, modified Cauchy function, and Huber function are commonly used constraint criteria in sparse deconvolution. We used numerical experiments to analyze the ability of sparsity constrained deconvolution to restore reflectivity sequences and protect weak reflections under different constraint criteria. The experimental results demonstrate that the performance of sparsity constrained deconvolution depends on the agreement between the constraint criteria and the probability distribution of the reflectivity sequences; furthermore, the modified Cauchy-constrained criterion protects the weak reflections better than the other criteria. Based on the model experiments, the probability distribution of the reflectivity sequences of carbonate and clastic formations is statistically analyzed by using well-logging data and then the modified Cauchy-constrained deconvolution is applied to real seismic data much improving the resolution.
This work was partly supported by the Major Basic Research Development Program of China (973 Program) (No. 2013CB228606), the National Science foundation of China (No. 41174117), the National Major Science-Technology Project (No. 2011ZX05031-001), and Innovation Fund of PetroChina (No. 2010D-5006-0301)
Cite this article:
LI Guo-Fa,QIN De-Hai,PENG Geng-Xin et al. Experimental analysis and application of sparsity constrained deconvolution[J]. APPLIED GEOPHYSICS, 2013, 10(2): 191-200.
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