Regularized least-squares theory is the fundamental basis for solving the geometry regularization problem in this work. To preserve the resolution of dipping events in the final image, the regularization term includes a transformation by Azimuth Moveout Biondi and Vlad (2001). Additionally, Biondi and Vlad's method is computationally efficient because they apply the AMO operator in the Fourier domain and precondition the least-squares problem.

For this work, we use an AMO operator designed for converted waves Rosales and Biondi (2001). Regularization with this operator intends to: 1) preserve the resolution of the dipping events, 2) correct for the spatial lateral shift of the common conversion point, and 3) handle the amplitudes properly.

We present a general overview of the AMO regularization theory and
discuss special considerations for converted waves regularization.
We present an iterative methodology to regularize the *PS* data
due to the dependency of the PSAMO operator on the ratio
between the *P* and the *S* velocities.

11/11/2002