It can be challenging to pick high quality first arrivals on noisy seismic datasets. The stability and smoothness criteria of the picked first arrival are not satisfied for datasets with shingles and interferences from unexpected and backscattered events. To improve first arrival picking, we propose an automatic first arrival picking workflow using global path tracing to find a global solution for first arrival picking with the condition of smoothness of the traced path. The proposed methodology is composed of data preconditioning, global path tracing, and final addition of traced and piloted travel times to compute the total picked travel time. We propose several ways to precondition the dataset, including the use of amplitude and amplitude ratio with and without a pilot. 2D global path tracing is comprised of two steps, namely, accumulation of energy on the potential path and backtracking of the optimal path with a strain factor for smoothness. For higher dimensional datasets, two strategies were adopted. One was to split the higher-dimension data into sub-domains of two dimensions to which 2D global path tracing was applied. The alternative method was to smooth the preconditioned dataset in directions except for the one used to trace the path before applying 2D global path tracing. Next, we discussed the importance of choosing proper parameters in both data preconditioning and constraining global path tracing. We demonstrated the robustness and stability of the proposed automatic first arrival picking via global path tracing using synthetic and field data examples.