The accuracy of near surface velocity fields significantly affects the quality of the land seismic data including static corrections, full-waveform inversion, and depth imaging. P-wave refraction tomography is a robust method to characterize the near surface but it lacks resolution in the very shallow and encounters difficulties if velocity inversions exist. Recent advances in Surface Wave Inversion (SWI) algorithms and workflows have demonstrated that SWI can produce high-resolution, S-wave, near-surface velocity models. However, one limitation of SWI is that a priori information is needed to convert the resulting S-wave velocity model into a P-wave velocity model that can be utilized in advanced imaging workflows. This information may come from up-holes (Successive sources at varying depths in a borehole in order to determine the velocities of the nearsurface formations) or shallow well logs but they are not always readily available. Recently, an approach is introduced Bardainne to jointly invert P-wave first arrivals, surface wave dispersion curves and reflectivity images to estimate a high resolution Pwave and S-wave velocity model of the near-surface. The aim of this thesis is to test this method on an area in the south of Oman (Nimr South) with a complex near-surface, consisting of velocity inversions and slow velocity in-filled sink holes. It is hoped that this method will generate an accurate near-surface P-wave velocity model. The shallow P-wave velocity model obtained from the joint inversion is used for seismic Depth Migration Imaging in order to improve the seismic resolution in both the shallow and deeper sections (i.e. thousands of meters). The shallow P-wave model is merged with the tomographic velocity model obtained from non-linear slope tomography. This merged velocity gave a robust model which has a better positioning of the low velocity anomaly structure and captured the challenging shallow velocity inversion. The difficult part was to get an accurate primary velocity (Vp) from Vp/Vs Ratio and capture a deeper velocity inversions.