The High-Speed Inversion of Rayleigh Wave and its Microtremor Application Analysis

Abstract

The application of Rayleigh waves in geological prospecting and engineering has been widely tested and used as a new method of shallow seismic exploration. The previous method of surface wave inversion needed to calculate the corresponding phase velocity that satisfied the dispersion function. This process increases the computation amount and reduces the surface wave inversion efficiency. This paper proposes a method to solve the problem by using different definition methods of the objective function. The method greatly reduces the amount of computation while results in approximately equal results with traditional method. This cuts the inversion time to 1% of conventional methods and provides favorable conditions for multiple inversions to suppress multiple solutions. We set artificial initial parameters with linear constraints in our velocity increasing model test to accelerate the convergence rate of the target function and obtain accurate results quicker. Finally, this method is applied to the microtremor dispersion data with a strong disturbance, and the inversion results are consistent with the high-density electrical profile and geological survey data. INDEX TERMS Rayleigh wave, Genetic algorithm, High-speed inversion, Microtremor explorationThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.

Inversion of Rayleigh Wave Dispersion Curves Via BP Neural Network and PSO

“…the difference between the inversion result and the observed dispersion curves, as the major constraint term to evaluate the inversion result. While recently some new objective functions have also been applied to Rayleigh wave inversion, such as the wave equation (Zhang & Alkhalifah, 2019) and the dispersion equation (Wang & Yan, 2021). Thirdly, joint inversion can be considered as an important approach to improve the inversion accuracy.…”