Insights and guidance for offshore CO2 storage monitoring based on the QICS, ETI MMV, and STEMM-CCS projects
Insights and guidance for offshore CO2 storage monitoring based on the QICS, ETI MMV, and STEMM-CCS projects
复制标题
DOI：
10.1016/j.ijggc.2020.103120
复制
发表时间：
2020-09
影响因子：
3.9
通讯作者：
M. Dean;J. Blackford;D. Connelly;R. Hines
中科院分区：
文献类型：
--
作者：
M. Dean;J. Blackford;D. Connelly;R. Hines
碳捕获和封存(CCS)是一种技术，它允许社会在不向大气中排放二氧化碳的情况下，释放化肥生产和燃料(化石或生物来源)燃烧等能源密集型过程的好处。因此，在社会追求公正的能源转型的同时，CCS可以帮助加速脱碳。本文旨在总结三个研究项目的经验教训，这些项目都是从二氧化碳储存运营商的角度对CCS海洋监测的各个方面进行调查的。QICS(量化和监测地质碳储存的潜在生态系统影响)、ETI MMV(能源技术研究所二氧化碳储存的测量、监测和核实)以及STEMM-CCS(海洋碳储存环境监测战略)项目共同代表了超过12年的专门研究，以评估环境影响并开发检测、定位和量化近海二氧化碳地质储存潜在泄漏的技术。每个项目都在典型的环境中使用受控发布来测试他们的方法和技术。QICS是三个项目中的第一个，重点是了解英国海洋环境对二氧化碳储存设施潜在泄漏的敏感性，并测试检测此类排放的技术。ETI MMV项目汇集了研究和行业伙伴，以开发和试航一种可操作的、综合的、成本效益高的二氧化碳地质储存海洋监测系统。作为一个商业项目，这些结果以前从未发表过，本文分享了这项工作的首次见解。2020年2月，STEMM-CCS完成了对英国北海一个海洋二氧化碳储存点环境监测技术的测试，进一步提高了近海底泄漏的特征能力，并提供了第一个海洋CCS示范级生态基线。本文旨在总结这三个项目的一些重要见解，并为感兴趣的读者提供参考。这三个项目的关键发现是，大规模储存的中小型二氧化碳泄漏的影响是有限的，而且是局部性的。海洋二氧化碳储存综合监测的技术能力已经存在，其性能已经在受控释放试验中进行了基准测试。即使是10−50 L/分钟的微小泄漏也可以在感兴趣的大范围内的未知位置检测到。最后，在实现自动化监测数据分析方面迈出了重要的第一步，包括从侧扫声纳数据自动检测泄漏信号(ETI MMV项目)和从海洋生物图像自动识别物种(STEMM-CCS项目)。一些剩余的挑战包括由于背景信号的巨大变化而导致的漏报/误报，长期监控大片区域的成本，以及基于大数据做出实时决策。继续努力降低海洋监测技术的成本，提高数据处理和分析的自动化程度，对于支持大规模安全、高效地部署近海CCS将十分重要。
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 CO2to 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 CO2storage 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 CO2Storage), 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 CO2storage 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 CO2storage. 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 CO2storage 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 CO2leakages from large-scale storage are limited and localised. Technology capabilities exist for integrated marine CO2storage 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.