QUADRAT DTP: Towards an integrated workflow for geothermal reservoir characterisation with seismic noise

Geothermal energy is recognised as a low-carbon and constant source of heat (and energy) compatible with meeting net zero emission targets in the UK’s future energy mix. Exploration and exploitation of geothermal sites thus play an important role in facing the challenges of climate change mitigation. The feasibility of a site for geothermal usage depends on a number of parameters such as the geothermal gradient, permeability, fault reactivation risk, and geological challenges for drilling. Having an informed knowledge about these helps choosing a site. While active seismic surveys, as routinely used in oil and gas exploration, are the most advanced and most capable methods for providing images of subsurface structures (Schmelzbach et al., 2016), they are also the most expensive ones and can be difficult to apply in urban environments.

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/