Surface wave methods (SWM) are widely used in non-invasive site investigations, near-surface geophysics, geotechnical site characterization, pavement quality monitoring, and non- destructive evaluation of structures. By utilizing the natural or induced surface waves, SWM can provide valuable information about the sub-surface conditions, such as soil layering, thickness, and stiffness. The use of surface waves in all the abovementioned applications involves simulating wave propagation in stratified media, also known as the forward model. The traditional free vibration-based forward models generate all the possible theoretical dispersion curves under the assumption of planar waves. Although the free vibration-based methods are computationally faster, they cannot accurately represent all the phenomena observed in field data, such as source-receiver effect, mode jump, near-field effect, and body wave effects. On the other hand, 2D/3D discretization-based numerical forward wavefield modeling approaches offer a closer approximation to real scenarios but suffer from computational inefficiency.
This research focuses on bridging the gap between computational efficiency and accuracy in wavefield modeling. A 2D dispersive staggered grid finite difference method is proposed, which is more than two times faster than the conventional one. Subsequently, this study introduces an active sourced semi-analytical wavefield approach. The method considers a cylindrically spreading wavefront instead of the planer wave assumption. The model captures the complete wavefield, including source-offset effects and leaky waves, while maintaining computational efficiency comparable to free vibration-based approaches. The method solves the eigenvalue problem constructed through the higher-order thin layer method. The proposed method’s performance is investigated on regularly dispersive media, low-velocity layer models, pavement models, and thin plate structures. It is at least two orders of magnitude faster than the 2D numerical approach. Furthermore, this study presents a systematic methodology for computing surface wave effective mode and demonstrates its efficacy through inversion techniques applied to several synthetic and field data. Overall, this research provides valuable

tools and methodologies that promise to enhance the accuracy and efficiency of surface wave methods across a spectrum of engineering applications.