Title :
Sparsity- and continuity-promoting seismic image recovery based on split Bregman method
Author :
Jinjie Liu ; Hongxia Wang ; Donyun Yi ; Lei Sun
Author_Institution :
Sch. of Sci., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
Recovering the subsurface reflectivity from the surface recorded seismic data is necessary to improve the resolution of a seismic image. However, this inversion process is ill-posed by nature. To tackle the ill-posedness, we assume the reflectivity series is sparse in the time domain but continuous in the space domain, and encode such information in the form of l1-norm constraints within the trace and spatial smoothing constraints across the trace in the inverse problem. In particular, split Bregman method is used to solve this constrained optimization problem. Theoretical simulations are performed to verify the validity and feasibility of our method.
Keywords :
geophysical image processing; image resolution; inverse problems; optimisation; seismology; smoothing methods; time-domain analysis; constrained optimization problem; continuity-promoting seismic image recovery; inverse problem; inversion process; l1-norm constraints; reflectivity series; seismic image resolution improvement; sparsity-promoting seismic image recovery; spatial smoothing constraints; split Bregman method; subsurface reflectivity recovery; time domain; trace smoothing constraints; Deconvolution; Genetics; Mathematical model; Noise; Optimization; Reflectivity; Wiener filters; seismic inversion; sparsity; spatial smoothing; split Bregman;
Conference_Titel :
Image and Signal Processing (CISP), 2012 5th International Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-0965-3
DOI :
10.1109/CISP.2012.6469976