Real-time processing of distributed acoustic sensing data for earthquake monitoring operations

TL;DR

This paper presents a modular software framework that integrates distributed acoustic sensing data into earthquake monitoring systems, enabling real-time analysis and hazard assessment using fiber-optic networks.

Contribution

The authors develop a standardized, compatible software solution that incorporates DAS data into existing seismic monitoring infrastructure for real-time earthquake detection.

Findings

Successful integration of DAS data with existing seismic systems

Real-time waveform streaming and machine-learning-based traveltime picking demonstrated

Potential for enhanced hazard assessment using fiber-optic DAS arrays

Abstract

We introduce a modular software framework designed to integrate distributed acoustic sensing (DAS) data into operational earthquake monitoring systems. Building on the infrastructure of the Advanced National Seismic System (ANSS) and the Southern California Seismic Network (SCSN), which employs the ANSS Quake Monitoring Software (AQMS), our solution supports real-time DAS waveform streaming and machine-learning-based traveltime picking to leverage the dense spatial sampling of DAS arrays. To enable seamless compatibility with the AQMS, our approach uses standardized seismic data formats to incorporate predetermined DAS channels. We demonstrate the integration of data from a 100-km-long DAS array deployed in Ridgecrest, California, and provide a detailed description of the software components and deployment strategy. This work represents a step toward incorporating DAS into routine seismic monitoring and opens new possibilities for real-time hazard assessment using fiber-optic networks.