Low-Frequency Blast Detection Using a Large-N Dark Fiber in Noisy Environments: Template Matching and Optimal Channel Selection

• DOI: 10.1785/0220230223
• Publication Date: 2024-01-17T14:12:51Z
• Authors: Michal Chamarczuk; Jonathan B. Ajo-F...; Avinash Nayak; Veronica Rodrigue...
• Keywords: Seismometer; Aperture (computer memory)

Abstract Distributed acoustic sensing (DAS), deployed on dark telecom fiber, is well-positioned to play a significant role in seismic monitoring networks because of the combination large aperture, fine spatial resolution, broadband sensitivity, and ubiquitous presence unused telecommunication fibers many areas world. In this study, we explore feasibility dark-fiber array noisy environment for detecting small explosions. We test effectiveness template matching detection low-frequency blasts generated by mining activities Imperial Valley, California. first evaluate performance analyzing relationship between threshold (DT) number DAS channels used. find that although, as expected, increasing yields higher significance lowers DT, gain far from linear, with local anomalies across cable associated zones noise. focus investigating types noise affecting practical approaches mitigating anthropogenic lower performance. Using median absolute deviation, identify two sources Next, design voting scheme selects contributing lowering DT ensures improvement when adding sequential channels. Finally, compare nearby conventional seismometers single station can outperform up ∼10 However, using full aperture our transect allows obtain ∼10% fewer false-positive detections than an four seismometers. Methodological solutions assessment channel selection allow us fully benefit dense sampling offered fiber. The findings study are step toward incorporating existing into novel explosion-monitoring workflows.