Abstract:

The seismic refraction method is an effective geophysical method used in engineering geophysics, engineering geology, and geotechnical engineering research fields, especially having an important role in revealing the properties of the soil before the construction of engineering structures. This study is the first example to find the 1D velocity model that minimizes the difference between the observed and calculated arrival times in the seismic refraction method of the MVBO algorithm. The introduced inversion algorithm, the Manta Rays Foraging Optimization (MRFO) algorithm, is a biological-based metaheuristic alternative optimization approach developed for the solution of engineering problems. It uses different foraging strategies (chain foraging, cyclone foraging, and somersault foraging) that manta rays exhibit to survive in order to solve different optimization problems. This study is the first example of using the MRFO algorithm to optimize the 1D distribution of seismic refraction data. In order to evaluate the effectiveness of the presented method, it was first applied to different multilayer synthetic seismic models and then the efficiency of the method was examined by adding noise to this data set. Finally, the MRFO inversion algorithm was applied to real-field data. A real seismic refraction dataset collected at the Leylanchay dam site in the Malekan district of the East Azerbaijan province of Iran was used. In order to determine the reliability of the model parameters of both synthetic and field data, the estimation parameters were also tested statistically through relative frequency distributions and probability density functions (PDF). The findings show that the study area consists of three layers, with the first two layers representing alluvium and the last layer being bedrock. The results reveal that the MRFO inversion algorithm gives appropriate and reliable results in the interpretation of seismic refraction data.