About the Project
Over the last two decades, the development of ambient seismic noise methods has provided new, cheap and ubiquitous tools to image and monitor the subsurface using the Earth’s natural background vibrations (Larose et al., 2015). Analysing ambient seismic noise for reservoir characterization has three major advantages over active seismics or earthquake seismology: 1) it doesn’t require active sources, which are expensive, 2) it doesn’t require earthquakes, which can be rare and unfeasibly located, and 3) it can be repeated over time, which facilitates monitoring. For example, seismic noise measurements have been shown to contain valuable information about seismic velocity variations at depths, thermally or hydrologically induced subsurface changes, and oriented faults and fractures. This project aims at drawing on the combined potential of different seismic noise methods for characterizing potential geothermal sites in order to investigate if an ambient noise “pre-scan” can help decide about where more potent (and more expensive) methods are worth applying. By quantifying validity, sensitivity and uncertainty of different ambient noise methods in the context of near-surface characterisation, this project will provide new means to analyse the earth’s subsurface and its resources. While tailored for geothermal systems, the envisaged workflow will be transferable to a range of applications, including monitoring of groundwater levels, or assessing geologically suitable sites for wind farms and subsurface storage solutions (CCUS).
The project comprises analysing seismic noise data recorded at different geothermal sites (UK and international) available from public sources or industry, as well as setting up a new seismic network at a site in the UK, for example, at Hill of Fares near Banchory, Aberdeenshire, where an initial feasibility study had been conducted in 2016 (Milligan et al., 2016). The student will be trained in a common and powerful programming language such as Matlab or Python and benefit from the high-performance computing cluster in Aberdeen. There is a strong possibility that the student will be involved in the deployment of seismometers in the field gaining expertise in seismic data acquisition and management.
More project details are available here: https://www.quadrat.ac.uk/projects/towards-an-integrated-workflow-for-geothermal-reservoir-characterisation-with-seismic-noise/
How to apply: https://www.quadrat.ac.uk/how-to-apply/
Before applying please check full funding and eligibility information: View Website
Larose, E., Carrière, S., Voisin, C., Bottelin, P., Baillet, L., Guéguen, P., ... & Gimbert, F., 2015. Environmental seismology: What can we learn on earth surface processes with ambient noise?. Journal of Applied Geophysics, 116, 62-74.
Schmelzbach, C., Greenhalgh, S., Reiser, F., Girard, J. F., Bretaudeau, F., Capar, L., & Bitri, A., 2016. Advanced seismic processing/imaging techniques and their potential for geothermal exploration. Interpretation, 4(4), SR1-SR18.
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