Rapid Fault Detection in Terrestrial and Submarine Environments with Fiber-Optic Sensing

[LINK]The spatial distribution of faults provides a critical basis for seismic hazard assessment, since the presence of faults directly reflect potential earthquake sources. Infrastructure and buildings located above or near active faults face heightened seismic risks, including severe structural damage from both static fault displacement and amplified ground shaking. Accurate and efficient fault detection is therefore an indispensable step for seismic hazard mitigation and for guiding civil engineering design. Conventional geological surveys, while effective, are often labor-intensive, time-consuming, and limited in urban or offshore environments. Seismic reflection imaging and tomography methods provide high-resolution subsurface characterization but are costly and difficult to implement at large scale. Consequently, there is a critical need for alternative approaches that are rapid, low-cost, and broadly applicable in both terrestrial and submarine settings. In this study, we propose a general framework for rapid fault detection using distributed acoustic sensing (DAS) on existing fiber-optic communication networks. DAS technology transforms standard telecommunication cables into dense seismic arrays capable of recording ground motion with meter-scale spatial sampling. Its high sensitivity to scattered seismic waves from faults makes it uniquely suited for large-scale fault mapping. Building on this advantage, we design a scatter source localization algorithm that automatically identifies fault-related scattering by backtracking seismic energy. The method requires minimal assumptions and simple preprocessing, making it computationally efficient and highly portable across different datasets. We tested this approach on six publicly available DAS arrays, including three on land (Ridgecrest, Arcata Bay, and Long Valley) and three offshore (Monterey Bay, Cook Inlet, and València). The combined length of these arrays exceeds 330 km, covering diverse tectonic and environmental settings. In Ridgecrest, California, the method successfully identified five fault segments intersecting the DAS arrays, consistent with the U.S. Geological Survey Quaternary Fault Database. At Arcata Bay and Long Valley, the algorithm detected both well-mapped faults and clusters of small faults, demonstrating its ability to resolve distributed fault networks. In Monterey Bay, the method identified not only cataloged submarine faults but also uncataloged fault zones, in agreement with earlier high-resolution marine geophysical studies. Applications in Cook Inlet and València further highlighted its potential to detect previously unmapped structures in regions where existing fault databases are sparse. Beyond natural earthquakes, we also tested the framework using ambient noise correlograms and active source records. In the Ridgecrest region, the method yielded consistent results across three independent datasets—earthquake records, ambient noise correlations, and controlled active sources—confirming its robustness and versatility. Even with a small number of events, significant scattering anomalies corresponding to fault locations were reliably detected, underscoring the efficiency of the approach. The algorithm achieved high computational performance, requiring only seconds per event on a standard workstation, which makes it suitable for near-real-time or large-scale applications. Overall, our results demonstrate that DAS-based scatter source localization enables accurate, rapid, and low-cost fault detection at engineering scale. The method provides reliable constraints on fault positions across varied geological settings, including urban areas where surface investigations are restricted and submarine environments where conventional surveys are expensive or impractical. By leveraging existing fiber-optic communication infrastructure, this framework minimizes both economic and temporal costs while extending fault detection capabilities to regions that are otherwise inaccessible. This study demonstrates the potential of DAS to complement and, in certain contexts, substitute traditional geophysical methods for seismic hazard assessment. With expanding urbanization and offshore infrastructure, DAS-based fault detection provides an efficient tool for fault mapping and site assessment, and is expected to play an important role in future large-scale fault surveys and infrastructure siting.

Recommended citation: Hu, M., & Li, Z. (2025). Rapid Fault Detection in Terrestrial and Submarine Environments with Fiber-Optic Sensing. Chinese Science Bulletin-Chinese. [胡敏哲, 李泽峰. 基于分布式光纤振动传感的陆地和海底断层快速探测. 科学通报]. (https://doi.org/10.1360/CSB-2025-0624).
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