Advanced Real-Time Seismic Monitoring Platform

Distributed acoustic sensing (DAS) systems generate vast amounts of data at high throughputs, leading to data management challenges and hindering the deployment of large-scale, distributed seismic monitoring networks. This project addresses these issues by developing advanced data compression and real-time event detection techniques, implemented on edge computing hardware, to reduce data transmission requirements and enable cost-effective, real- time monitoring of seismic activity. In Phase I, Sequent Logic investigated state-of-the-art lossy compression algorithms and event detection methods, optimizing them for DAS data and demonstrating their effectiveness in reducing data volumes while preserving signal fidelity for reliable event detection. The team also explored the feasibility of accelerating these algorithms on CPU, GPU, and FPGA hardware. The Phase-II project will focus on further optimizing and integrating the developed compression and event detection techniques into a hardware unit with integrated edge computing capabilities. The system will be validated through real-world deployments in collaboration with academic and industry partners, demonstrating its ability to enable cost-effective, real-time seismic monitoring in remote locations with limited connectivity. The advanced real-time seismic monitoring platform developed in this project will facilitate the adoption of DAS technology in various applications, including earthquake early warning systems, subsurface resource exploration, and infrastructure monitoring. By enabling the deployment of large-scale, distributed seismic sensor networks in remote and underserved areas, this technology will contribute to improved seismic risk assessment, disaster response, and scientific understanding of Earth's subsurface processes.