A Framework for Stress Detection and Fault Zone Characterization Using Optical Distributed Acoustic Sensing (DAS) Data

This study presents a practical workflow for extracting and analyzing stress from Distributed Acoustic Sensing (DAS) measurements. The main contribution is the direct use of DAS signals to obtain quantitative, localized stress estimates and to evaluate how human activities― specifically construction and traffic―affect faults, an application that has received limited attention in prior DAS-based studies. Raw DAS data (Rayleigh backscattered intensity) are first preprocessed to remove noise and long-term trends. The signals are then demodulated using Hilbert-based analysis to obtain an unwrapped, unambiguous phase and to estimate phase changes. After converting phase variations to strain (or strain rate), stress is computed using the shear modulus of the optical fiber. Results indicate that stress perturbations induced by construction and traffic are clearly distinguishable and measurable, and that their magnitudes vary with source distance and local geological conditions. The extracted stress patterns can be used to identify vulnerable fault segments and potential hazard zones, providing actionable information for geological risk assessment and urban planning. Overall, the proposed procedure offers strong potential for scalable, continuous DAS-based monitoring in diverse settings.

کلیدواژه ها:

Fiber-Optic Sensor ، Distributed Acoustic Sensing (DAS) ، Stress Analysis ، Fault Zone Monitoring