Search

For the problems of seismic wave propagation, scale effects will appear while considering the microstructures of medium. Scale effects mean that new components of wave fields appear in the seismograms due to the microstructure interactions in the medium and vary with the change of the characteristic length scale parameters. The generalized continuum mechanics (GCM) theory which introduces the intrinsic length scales of the microstructures is suitable for analyzing the scale effects of seismic wave propagation. We adopt the concept of multi-scale microstructure interactions, that is, the modified couple stress theory, and the one-parameter second strain gradient theory, as two branches of the GCM theory, have the same definition characteristic length scale parameters of medium, to describe the microstructure interactions at different scales. Through the quantitative relationship between the characteristic length scale parameters of the medium and the micropore, the layered model of the characteristic length scale parameters of the micropore is constructed for numerical modeling in a unified framework, and the scale effects of seismic wave propagation is analyzed. More specifically, the asymmetric elastic wave equations under a unified framework are derived, and the physical definition of the characteristic length scale parameters of medium is given. And the influence of the characteristic length scale parameter of the micropore on the seismic wave propagation is focused on. Finally, the scale effects of seismic waves excited by high-speed trains under the viaduct system are analyzed, and some conclusions are drawn. • The influence of microstructures on seismic wave propagation needs to be considered. • The GCM theory containing scale parameters is suitable for analyzing scale effects. • The interface information of the scale parameter can be reflected in seismic records. [ABSTRACT FROM AUTHOR]

The finite-difference (FD) scheme is extensively applied in seismic modelling, imaging and inversion due to its advantages of large-scale parallel computing and programming. However, numerical dispersion caused by using a difference operator in substitution for the differential operator is non-negligible, which reduces the accuracy of the modelling and can lead to some misinterpretations. In addition, the computing resources required by the FD scheme is highly demanding when dealing with large models, which limits its applicability. In this paper, a new optimised FD scheme is proposed, which is based on an improved particle swarm optimisation (PSO) algorithm. We improve the conventional PSO algorithm by introducing strategies related to local learning and global learning, which contribute to accelerating the convergence rate and effectively avoiding getting trapped in local extrema. Then, the improved PSO algorithm is used to improve the conventional FD scheme. Dispersion analysis and numerical modelling demonstrate that the low-order optimised FD scheme can achieve higher accuracy than a high-order conventional operator. Compared with the conventional FD scheme and a FD scheme based on the Remez exchange algorithm, the optimised FD scheme based on the improved PSO algorithm can more efficiently suppress numerical dispersion and increase computational efficiency. [ABSTRACT FROM AUTHOR]