# Moho Imaging with Fiber Borehole Strainmeters Based on Ambient Noise Autocorrelation

## TL;DR

This paper introduces a new method for imaging the Moho layer using fiber borehole strainmeters by analyzing ambient noise, without needing multiple stations.

## Contribution

A novel Moho imaging method for fiber borehole strainmeters using ambient noise autocorrelation is proposed.

## Key findings

- S-wave reflection signals were successfully extracted using phase autocorrelation and phase-weighted stacking.
- The calculated crustal thickness matched previous research results in Lu’an, China.
- The method works effectively with a small number of fiber borehole strainmeters.

## Abstract

Moho tomography is important for studying the deep Earth structure and geodynamics, and fiber borehole strainmeters are broadband, low-noise, and attractive tools for seismic observation. Recently, many studies have shown that fiber optic seismic sensors can be used for subsurface structure imaging based on ambient noise cross-correlation, similar to conventional geophones. However, this array-dependent cross-correlation method is not suitable for fiber borehole strainmeters. Here, we developed a Moho imaging scheme for the characteristics of fiber borehole strainmeters based on ambient noise autocorrelation. S-wave reflection signals were extracted from the ambient noise through a series of processing steps, including phase autocorrelation (PAC), phase-weighted stacking (PWS), etc. Subsequently, the time-to-depth conversion crustal thickness beneath the station was calculated. We applied our scheme to continuous four-component recordings from four fiber borehole strainmeters in Lu’an, Anhui Province, China. The obtained Moho depth was consistent with the previous research results. Our work shows that this method is suitable for Moho imaging with fiber borehole strainmeters without relying on the number of stations.