← Back to Sessions

Comparing Ambient Noise Methods for Estimating Dispersion Curves at the Local-to-regional Scale

Description: 

The Nevada National Security Site (NNSS) hosts a network of strike-slip faults known as the Rock Valley Fault Zone (RVFZ). A series of shallow (<3 km) earthquakes in 1993 challenge our understanding of how shallow earthquakes occur, where fault orientations, regional stress fields, and regional groundwater flow may be important factors but are not well characterized, especially in the shallow subsurface. The focus of this work is to improve a local-to-regional model of seismic velocities of the southern NNSS region using Rayleigh wave dispersion curves extracted from ambient noise data. We process continuous seismic data during a three-month period from February through April 2023, combining a large-N array seismic network over central Rock Valley with regional Northern Nevada and Southern Nevada network stations. The variable interstation distances ranging from 6 to 62 m and limitations in the bandwidth of noise signal pose a methodological challenge, potentially limiting feasibility of a one-size-fits-all solution. We therefore explore multiple methods of extracting dispersion curves from station pair cross correlations and compare results at different interstation distances, with the goal of improving dispersion estimates at close (<10 km) interstation distances. We compare the results of multiple methods, including frequency time analysis (FTAN), Aki’s cross-spectral method, a continuous wavelet transform (CWT) method, and a recent machine learning method. We quantify the strengths and weaknesses of each, where each method agrees and disagrees, and expound on the potential of machine learning methods to overcome some of the challenges of conventional methods.

SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.

Session: New Directions in Environmental, Seismic Hazard and Mineral Resource Exploration Studies [Poster]

Type: Poster

Date: 4/17/2025

Presentation Time: 08:00 AM (local time)

Presenting Author: Jennifer

Student Presenter: No

Invited Presentation: 

Poster Number: 112

Authors