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Distributed Dynamic Strain Sensing (DDSS), also known as Distributed Acoustic Sensing (DAS), is becoming a popular tool for volcano monitoring. The sensing method relies on sending coherent light pulses into an optical fibre and measuring the phase-shift of Rayleigh back-scattered light due to strain on the fibre. This provides distributed strain rate measurements at high temporal and spatial sampling rates. Standard telecom fibres have been conventionally used for this purpose, however engineered fibres are being developed to enhance the back-scattered light, providing up to 100 times improved sensitivity in contrast to the conventional standard fibre. Despite the technical advantages of engineered fibres, standard fibres already have extensive coverage around the Earth surface, and so there is an interest in using the existing telecommunication infrastructure. In this study we compare stack DDSS data from a fibre loops made of several fibres within the same optical fibre cable, with DDSS data measured on an engineered fibre. We analyse how stacking can improve the signal quality of the recorded DDSS data. In an area located 2.5 km NE from the craters of Mt. Etna, we spliced 9 standard fibres together from a 1.5 km long cable to create a single optical path and interrogated using an iDAS unit. At the same time, we interrogated with a Carina unit a 0.5 km engineered fibre installed parallel to the standard multi-fibre cable. Both fibres were interrogated in a common period of 5 days. We use a spatial cross-correlation function to find the channel equivalences between each fibre and then stack them to evaluate the changes in the DDSS data and compare with the engineered fibre data. Our results show that, despite engineered fibres have lower noise, a stack of 5 fibres can achieve a maximum noise reduction of 20% outside of the optical noise band, in comparison to the engineered fibre. We achieved this noise reduction for our specific configuration, and so we show how the stack improvement is dependent on the type of configuration in terms of fibres stacked and length of the fibres. Our findings motivate the exploitation of multi-fibre cables in existing infrastructures, so-called dark fibres, for monitoring volcano and applications to other environments.

Carbon Capture and Storage (CCS) technology offers an opportunity to reduce the concentration of CO2 in the atmosphere. Typically, CO2 is injected underground into depleted oil and gas fields, coalbeds or deep saline geological formations, where it is securely stored. For a formation to be suitable for CO2 storage three main requirements need to be fulfilled; capacity, injectivity and containment.

Earthen dams and embankments are prone to internal erosion, their most significant source of failure. Standard monitoring techniques often measure erosion effects when they appear at the surface, reducing the potential response time to address the problem before failure. Through their integrative sensitivity along their propagation, seismic signals are well suited to assess mechanical changes in the bulk of a dam. Moreover, seismic velocities are strongly sensitive to porosity, pore pressure, and water saturation, physical properties that vary the most for internal erosion. Here, we used fiber optics and a Distributed Acoustic Sensing (DAS) array installed on an experimental dam with built-in defects to record the ambient seismic wavefield for one month while the dam reservoir is gradually filled up. The position and nature of the dam defects are unknown to us, to allow an actual blind-detection experiment. We computed cross-correlations between equidistant channels along the dam every 15 minutes and monitored the relative seismic velocity changes at each location for the whole month. The results show a strong correlation of the velocity changes with the water level in the reservoir at all locations along the dam. We also observe systematic deviations from the average velocity change trend. We interpret these anomalies as the effects of the built-in defects placed at different positions in the bulk of the dam. The careful analysis of the residual velocity changes allows us to hypothesize on the position and nature of the defects.