COMPARISON OF BASIS PURSUIT INVERSION WITH SIMULATED ANNEALING INVERSION USING POST-STACK SEISMIC DATA

Seismic inversion using global optimization algorithms is a non-linear, model-driven process. It yields an optimal solution of the cost function – reflectivity, when prior information is sparse. The reconstructed reflectivity series offers detailed interpretations of thin layers, internal stratigraphy, and lateral continuity and connectivity of sand bodies. This study compared two stable and robust global optimization techniques, Simulated Annealing (SA) and Basis Pursuit Inversion (BPI) as applied to post-stack seismic data from the Gulf of Mexico. Both methods use different routines to search for the minimum error energy function. Estimation of inversion parameters in SA is rigorous and more reliable because it depends on prior knowledge of subsurface geology. The BPI algorithm is more robust and was developed as an alternative method than incorporating a priori information, although computing time is longer by a factor of 5. Results for the Gulf of Mexico show that BPI gives a better stratigraphic and structural actualization due to its capacity to delineate layers thinner than the tuning thickness. The SA algorithm generates both absolute and relative impedances, which provide both qualitative and quantitative characterization of thin-bed reservoirs.