A Deconvolution-based Objective Function For Wave-equation Inversion

Luo, Simon (Colorado School of Mines) | Sava, Paul (Colorado School of Mines)

OnePetro 

We propose a new objective function for wave-equation inversion that seeks to minimize the norm of the weighted deconvolution between synthetic and observed data. Compared to more the conventional difference-based objective function which minimizes the norm of the residual between synthetic and observed data, the deconvolution-based objective function is less susceptible to cycle skipping and local minima. Compared to a crosscorrelation-based objective function, the deconvolution-based objective function is less sensitive to a bandlimited or non-impulsive source function, which may result in a nonzero gradient of the objective function even when the constructed velocity model matches the true model.