Seismic Analysis of Sediments in the Tabriz Plain Using Metaheuristic Algorithms and Shear Wave Velocity Modeling

Surface waves are a cornerstone of geophysical studies for deriving shear wave velocity profiles. Inverting dispersion curves, however, poses a significant challenge for traditional local search methods due to the problem’s nonlinearity and the objective function’s multiple extrema. This study introduces a metaheuristic approach Ant Colony Optimization (ACO) implemented in MATLAB to tackle these complexities. The algorithm’s effectiveness was assessed using synthetic datasets, testing three distinct six-layer models with varying shear wave velocities, compressional wave velocities, and layer thicknesses, assuming a variable Poisson’s ratio and constant density. Compared to the neighborhood algorithm in Geopsy software, ACO exhibited superior reliability and computational efficiency. The method was further validated using an experimental dispersion curve from the Tabriz Plain, yielding results closely aligned with borehole data. Subsequently, a two-dimensional shear wave velocity model was constructed for the study area based on these inversion outcomes. This work underscores the promise of metaheuristic optimization techniques in enhancing the accuracy and robustness of surface wave dispersion curve inversion.

کلیدواژه ها:

Metaheuristic optimization ، neighborhood algorithm ، surface waves ، dispersion curve inversion