Optical to Seismic Signal Processing for the Fiber-Optic Distributed Sensing System
Abstract
Fiber-optic cables have traditionally been used for high-speed data transmission in the telecommunication systems. Optical fibers are not susceptible to electromagnetic interference. In recent years, the fiber-optic distributed strain and vibration sensing systems have found applications in many fields including hydrocarbon resource explorations, homeland security and military.Main advantages of using a distributed fiber-optic sensing (FOS) system over standard electromechanical-based geophones are minimum electromagnetic interference, ability to operate in harsh environments (high-temperature and pressure), minimally invasive in terms of deployment, measurements and extraction. The FOS technology have been used for distributed real-time vibration measurements for monitoring target movements along the perimeter of border and critical infrastructure; reservoir properties monitoring for oil and gas applications; and monitoring structural integrity of buildings, roads and bridges. The main bottleneck of the applications of the FOS technology in distributed real-time measurements is processing huge amount of data.
In this abstract, we focused on efficient processing of optical data collected using a fiber-optic distributed acoustic sensing (DAS) system for vertical seismic profile (VSP) application. The collected VSP data is from inside a borehole with the DAS interrogator located on the surface. In a typical phase-OTDR (optical time domain reflectometry) based DAS system, the phase change of the backscattered Rayleigh signal is related to the strain rate of the medium surrounding the fiber along the axis. The axial-strain is due to localized vibrations of the medium surrounding the fiber. The standard Fourier Transform (FT), Wavelet Transform (WT), and Fractional Fourier Transform (FrFT) are separately applied on the raw optical data (phase-shift) and the resulted strain rate were compared with each other. Performance, SNR (signal-to-noise ratio) and accuracy of these transformations on the optical-to-strain signals are compared.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.S43E0661M
- Keywords:
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- 7294 Seismic instruments and networks;
- SEISMOLOGY