Seismic crosswell tomography is recognized as a robust method for characterizing subsurface structures in oil field exploration. In this study, the effectiveness of structured and unstructured meshing strategies is evaluated for inverting seismic crosswell tomography data to enhance subsurface velocity imaging. A synthetic layered model, representative of oil field geology and incorporating gas, oil, and saline water anomalies with distinct velocity contrasts, is utilized to simulate wave propagation and reconstruct velocity distributions through a finite element-based approach. Structured meshing is found to provide computational stability and uniform resolution, suitable for simpler geological settings, though artifacts may be introduced in complex anomaly regions. In contrast, unstructured meshing is adapted to geological heterogeneity, thereby improving the resolution of anomaly-related velocity contrasts, albeit with increased computational requirements. Comparative analysis of velocity reconstructions, misfit distributions, and ray path coverage is conducted to elucidate the trade-offs between these meshing strategies, informing optimal mesh design for accurate subsurface characterization. The findings derived from this research significantly enhance the field of seismic crosswell tomography, particularly in the context of oil field investigations. This study is limited to synthetic 2D modeling, and the absence of field validation and 3D modeling warrants further investigation to confirm real-world applicability. By providing valuable insights into the intricacies of mesh optimization, this study paves the way for achieving exceptionally high-resolution geophysical imaging of subsurface hydrocarbon anomalies.