This work quantifies the error created during seismic processing when isotropic approach is used to normal moveout correction and velocity analysis and the seismic data is anisotropic. This quantification is made by performing velocity analysis in several synthetic seismograms built from a simple (but realistic) geological model with some horizontal layers, one of them being anisotropic (VTI), representing a common deep water sedimentary sequence. The anisotropy in the model is known and the difference between the NMO velocities found by seismic processing (semblance analysis) is quantified for each model. The result is also shown through the difference in depth obtained from time-depth conversion with NMO velocity. Depending on the anisotropic degree, the velocity (and/or depth) error produced when the anisotropy is not considered can be up to 10-15 percent for anisotropic values commonly found in nature. This quantification analysis also concludes that delta parameter influences more on velocity error than e parameter and layer depth. To complement this work, the best anisotropic approach for normal moveout correction to be used in real data is investigated, by comparing some NMO functions found in technical papers, analyzing the data correction and the parameter estimation. The usage of NMO equation with anisotropic approach in anisotropic seismic data allows a better normal moveout correction and the anisotropic parameters ( épsilon and delta) can be estimated from velocity analysis. The estimated anisotropic parameters were applied in a pre-stack anisotropic depth migration algorithm and it was verified that when delta is well estimated, the migrated position of a seismic reflector is not very distorted from its real position. It is also proposed in this Thesis one alternate technique for velocity analysis using one linear discriminant function called gradient descendent. This methodology allows adopting several normal moveout functions and obtaining all the equation parameters (t0 , VNMO and eta) at once, differently from semblance method used in conventional velocity analysis that only allows obtaining two parameters at the same time (t0 and VNMO ), which requires a second velocity analysis to obtain all equation parameters. The proposed gradient descendent method was tested with four NMO equations and it was shown to be fast, robust and efficient.