Field demonstration of a 1 x 4 Fiber Sensor Array for Sub-Surface Carbon Dioxide Monitoring for Carbon Sequestration

Loading...
Thumbnail Image

Date

2014-01

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

A fiber sensor array for subsurface CO 2 concentration measurements was developed for monitoring geologic carbon sequestration sites. The fiber sensor array uses a single temperature-tunable distributed feedback (DFB) laser operating with a nominal wavelength of 2.004 μm. Light from this DFB laser is directed to one of the four probes via an inline 1×4 fiber optic switch. Each of the four probes is buried and allows the subsurface CO 2 to enter the probe through Millipore filters that allow the soil gas to enter the probe but keeps out the soil and water. Light from the DFB laser interacts with the CO 2 before it is directed back through the inline fiber optic switch. The DFB laser is tuned across two CO 2 absorption features, where a transmission measurement is made allowing the CO 2 concentration to be retrieved. The fiber optic switch then directs the light to the next probe where this process is repeated, allowing subsurface CO 2 concentration measurements at each of the probes to be made as a function of time. The fiber sensor array was deployed for 58 days beginning from June 19, 2012 at the Zero Emission Research Technology field site, where subsurface CO 2 concentrations were monitored. Background measurements indicate that the fiber sensor array can monitor background levels as low as 1000 parts per million (ppm). A 34-day subsurface release of 0.15 tones CO 2 /day began on July 10, 2012. The elevated subsurface CO 2 concentration was easily detected by each of the four probes with values ranging over 60,000 ppm, a factor of greater than 6 higher than background measurements.

Description

Keywords

Citation

Soukup, Benjamin, Kevin S. Repasky, John L. Carlsten, and Geoff Wicks. “Field Demonstration of a 1×4 Fiber Sensor Array for Subsurface Carbon Dioxide Monitoring for Carbon Sequestration.” Journal of Applied Remote Sensing 8, no. 1 (January 2, 2014): 083699. doi:10.1117/1.jrs.8.083699.
Copyright (c) 2002-2022, LYRASIS. All rights reserved.