Insights and guidance for offshore CO2 storage monitoring based on the QICS, ETI MMV, and STEMM-CCS projects

Dean, M; Blackford, JC; Connelly, DP; Hines, R. 2020 Insights and guidance for offshore CO2 storage monitoring based on the QICS, ETI MMV, and STEMM-CCS projects. International Journal of Greenhouse Gas Control, 100. 103120. https://doi.org/10.1016/j.ijggc.2020.103120

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Official URL: http://dx.doi.org/10.1016/j.ijggc.2020.103120

Abstract/Summary

Carbon Capture and Storage (CCS) is a collective term for technologies that allow society to unlock the benefits of energy intensive processes like fertiliser production and combustion of fuels (fossil or biologically sourced) without releasing the CO2 to the atmosphere. Hence, CCS could assist in accelerating decarbonisation while society pursues a just energy transition. This paper aims to summarise the learnings of three research projects that all investigated aspects of marine monitoring for CCS from a CO2 storage operator’s perspective. The QICS (Quantifying and Monitoring Potential Ecosystem Impacts of Geological Carbon Storage), ETI MMV (Energy Technologies Institute Measurement, Monitoring and Verification of CO2 Storage), and STEMM-CCS (Strategies for Environmental Monitoring of Marine CCS) projects collectively represent over twelve years of dedicated research to assess environmental impacts and to develop technologies for detection, location, and quantification of potential leakage from offshore geological storage of CO2. Each project used controlled releases in representative environments to test their methods and technologies. QICS as the first of the three projects, focused on the understanding of sensitivities of the UK marine environment to a potential leak from a CO2 storage complex and tested technologies to detect such emissions. The ETI MMV project brought together research and industry partners to develop and sea trial an operational, integrated and cost-effective marine monitoring system for geological CO2 storage. As a commercial project, these results have never been published before and this paper shares for the first-time insights from this work. In February 2020, STEMM-CCS, completed its quest to test techniques for environmental monitoring over a marine CO2 storage site in the UK North Sea, further improved near seabed leakage characterisation capabilities, and delivered a first marine CCS demonstration level ecological baseline. This paper aims to summarise some of the key insights from the three projects and provides references where available for the interested reader. The key finding of all three projects is that the impacts of small to medium CO2 leakages from large-scale storage are limited and localised. Technology capabilities exist for integrated marine CO2 storage monitoring and their performance has been benchmarked at controlled release trials. Even small leakages of 10− 50 L/min can be detected at unknown locations in a large area of interest. Finally, the first important steps towards automated monitoring data analysis have been made, including automated leakage signal detection from Side Scan Sonar data (ETI MMV project) and automated species identification from marine biology images (STEMM-CCS project). Some remaining challenges include missed/ false alerts because of large variations in the background signal, the cost of monitoring large areas over long periods, and making real-time decisions based on big data. Continued work to reduce the cost of marine monitoring technologies and advancing automation of data processing and analysis will be important in order to support safe and efficient offshore CCS deployment at large scale.

Item Type: Publication - Article
Additional Keywords: Monitoring Verification CCS Offshore CO2 storage Detection Location Attribution Quantification Impact assessment Regulation
Divisions: Plymouth Marine Laboratory > National Capability categories > NMOD-NC modelling
Plymouth Marine Laboratory > National Capability categories > Single Centre NC - CLASS
Plymouth Marine Laboratory > Science Areas > Marine Ecosystem Models and Predictions
Depositing User: S Hawkins
Date made live: 19 Aug 2020 17:02
Last Modified: 19 Aug 2020 17:02
URI: http://plymsea.ac.uk/id/eprint/9027

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