Date of Award

Summer 8-10-2016

Degree Type


Degree Name


Degree Program




Major Professor

Dr Abu K.M. Sarwar

Second Advisor

Dr Juliette W. Ioup

Third Advisor

Dr Ashok Puri

Fourth Advisor

Dr Arslan Tashmukhambetov


Seismic inversion using a global optimization algorithm is a non-linear, model-driven process. It yields an optimal solution of the cost function – reflectivity/acoustic impedance, when prior information is sparse. The inversion result 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 and constraints 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 a more robust deterministic process. It was developed as an alternative method to incorporating a priori information. 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.


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