Mathematical methods for enhancing distributed acoustical sensing and fibre optics devices

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Distributed acoustical sensing (DAS) is an advanced sensing technology that provides remote, real-time access to closely-spaced data collection sites spread across tens of kilometres of linear infrastructure, including pipelines, railways, and perimeters of factories or resource infrastructure. The DAS system works by converting a single optical fibre into tens of thousands of individual highly-sensitive vibrational sensors. Utilizing optical fibres results in a system that is immune to electromagnetic or radio frequency interface, requires no power along the entire sensing length, and is relatively inexpensive to deploy over large distances. Applications for the sensing system include securing facility perimeters from third party intrusion, monitoring railway lines, railway right-of-ways, pipelines, oil field facilities, and specific implementations for well production and hydraulic fracturing operations. DAS systems are useful in a diverse range of applications that depend on the detection of vibrations in installations spread across large geological areas. This project addresses the mathematical and computational challenges that arise in advancing the DAS technology. The focus is on the development of accurate and high speed signal processing method to analyze the raw laser interferometry signal, optimizing the geometric and physical placement of the optical fibres to maximize vibrational sensitivity, adapting the DAS sensor output to industry-standard imaging algorithms for seismic exploration and oil field production monitoring, and down-well sensing for well integrity, fracturing monitoring, and time-lapse recording of the field.