Controlling atmospheric levels of greenhouse gases is required to mitigate the effects of anthropogenic climate change. A promising solution to reduce emissions of carbon dioxide (CO2) to the atmosphere is carbon capture and storage (CCS). These technologies comprise methods to isolate CO2 at its point of production, and inject it underground into a suitable geological formation for long-term storage. While CCS has been demonstrated at a number of sites across the world, there are challenges involved in monitoring the fate of CO2 in the subsurface after its injection. Muon tomography has been suggested as a monitoring technique that can compliment other methods such as repeat seismic surveys. It is proposed that muon detectors, which can be deployed in underground boreholes beneath a storage site, will measure changes in muon intensity caused by variations in the density distribution of the overburden due to the presence of CO2. In this thesis, muon simulations of a geological repository are presented to determine the feasibility of muon tomography for monitoring carbon storage sites. In addition, simulations of the local radioactive backgrounds for borehole detectors have been developed to understand their setup and operating conditions. It is found that the constant injection of CO2 into a typical storage formation leads to changes in density that are observable as a statistically significant change in muon intensity within 50 days of data taking. While cosmic-ray muons provide a signal for muon tomography, they are an unwanted background for underground experiments searching for rare physics events. Backgrounds from radioactivity in the vicinity of a sensitive detector may also obscure potential signals and limit sensitivity. Using the models developed for muon tomography simulations, the muon-induced and laboratory backgrounds for the LUX-ZEPLIN (LZ) dark matter experiment have been characterised. It is found that the rate from these sources is subdominant to internal detector backgrounds.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:739840 |
| Date | January 2017 |
| Creators | Woodward, David |
| Contributors | Kudryavtsev, Vitaly |
| Publisher | University of Sheffield |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.whiterose.ac.uk/19916/ |
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