16 Dec 2025

Fiber-Optic Distributed Acoustic Sensing for Nondestructive Monitoring of Permafrost

Fiber-optic distributed acoustic sensing (DAS) has gained traction in recent years as a geophysical monitoring tool. Advancements in commercially available DAS have allowed for sub-10 m data resolution and high sampling rates (over 10 kHz), leading to the use of DAS for infrastructure change detection and localization monitoring. Using this technology, a team from the US Army Engineer Research and Development Center–Cold Regions Research and Engineering Laboratory (ERDC-CRREL) built a field campaign around monitoring changes in permafrost using DAS via a dispersion analysis of surface wave propagation. In May 2024, active seismic testing was performed on a rapidly deployed, surface-laid, nondestructive DAS array above CRREL’s permafrost tunnel. Active source testing was repeated in September 2024 to collect data that may indicate changes in the seismic response due to permafrost changes. DAS response data was also collected from an unmanned aerial system (UAS) to evaluate for potential use in standoff assessment of permafrost changes. The field campaign results indicate that nondestructive DAS arrays are likely useful in detecting and localizing changes in near-surface properties of the permafrost.

30 Jul 2021

Geotechnical Effects on Fiber Optic Distributed Acoustic Sensing Performance

Abstract: Distributed Acoustic Sensing (DAS) is a fiber optic sensing system that is used for vibration monitoring. At a minimum, DAS is composed of a fiber optic cable and an optic analyzer called an interrogator. The oil and gas industry has used DAS for over a decade to monitor infrastructure such as pipelines for leaks, and in recent years changes in DAS performance over time have been observed for DAS arrays that are buried in the ground. This dissertation investigates the effect that soil type, soil temperature, soil moisture, time in-situ, and vehicle loading have on DAS performance for fiber optic cables buried in soil. This was accomplished through a field testing program. Signal to Noise Ratio (SNR) of the DAS response was used for all the tests to evaluate the system performance. The results of the impact testing program indicated that the portions of the array in gravel performed more consistently over time. The results also indicated that time DAS performance does change somewhat over time. Performance variance increased in new portions of array in all material types through time. Overall, this dissertation provides guidance that can help inform the civil engineering community with respect to installation design recommendations related to DAS used for infrastructure monitoring.