Bending Ray tracing is a technique for finding the shortest travel path from a fixed source to a fixed receiver. Ray tracing is a time-consuming computing technique in applications such as tomography, which involves a large number of source-receiver pairs. In this regard, parallel programming makes it possible to reduce the running time of a serial program significantly by breaking it into a discrete series and solve it by different processing units simultaneously. Along with the rapid development of parallel computing technologies in both hardware architecture and system software, parallel computing is growing rapidly in a broad range of scientific computing applications. In this paper, the parallelization of pseudo-bending Ray tracing algorithm is presented using both task and data parallelization strategies. In the task parallelization, the bending calculation of each path section is distributed to different processors, while in the data parallelization, due to the independent calculation for each pair of source-receiver, the data parts are distributed to different processors. The performance results of the parallelizations of the pseudo-bending algorithm for Ray tracing in a 3D velocity model are shown using OpenMP, which is an application programming interface for shared memory multiprocessing programming. The advantage of OpenMP programming model is its simplicity to parallelize an existing serial code. This is especially useful now that multi-core CPUs are common. The results show the effectiveness and efficiency of the approach. A significant speedup in the Ray tracing implementation is achieved. This reduction in computation time allows more Rays to be traced, which directly affects the accuracy of tomography results. Sufficient Ray coverage is needed to obtain tomography images with perfect resolution.