一种有效的适合F-J方法从背景噪声资料中提取多阶频散曲线的台阵划分方法

Efficient array partitioning method for F-J transform to extract multimode dispersion curves from ambient noise data

近年发展起来的从地震背景噪声提取多阶频散曲线的F-J方法是一种台阵分析方法,对某一特定的研究区域内台阵的划分方式直接影响成像的效果.当研究区域地下结构较简单,且台站间距比较均匀时,可以使用简单的平移式移动阵列法;然而若研究区域地下结构复杂多变,尤其是台站间距疏密不均时,就需要根据具体的地域特征灵活划分台阵.本文介绍了一种适用于地下结构复杂及台站间距不均匀区域的台阵划分方法,具有一定的普适性.我们将其应用于美国阿拉斯加及加拿大西北部,验证了相比于简单的沿经纬度移动阵列,我们的分区方法确实大大提高了结果的分辨率,为后续反演研究区域三维速度结构提供了坚实的保障.

The recently developed F-J transform method relies on the array configuration of seismic stations,which directly affects the imaging results of the velocity structure beneath a specific study area.When the underground structure of the study area varies gently and the station spacing is relatively uniform,it is sufficient to simply move a fixed-size rectangular box gradually along the latitude and longitude.However,if the subsurface structure of the study area is complex and variable,especially when the station spacing is uneven,the array needs to be divided flexibly according to the specific geographical features.This paper introduces an array partitioning method suitable for regions characterized by complex subsurface structures and non-uniform station spacing,exhibiting a certain level of generality.By applying this method to the Alaskan and northwestern Canadian regions,we have validated that our partitioning approach significantly enhances the resolution of the results compared to the simplistic latitude and longitude-based moving array method.This improvement provides a solid foundation for subsequent inversion studies aiming to investigate the three-dimensional velocity structure of the research area.