Environmental Monitoring using off-shore wind and tidal power optical fibres

使用海上风能和潮汐能光纤进行环境监测

• 批准号: 2888269
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2888269
• 关键词: Environmental; Monitoring; using; off; shore

The International Energy Agency states that we cannot achieve net zero ambitions by 2050 without Carbon Capture, Use & Storage (CCUS). Subsurface geological storage reservoirs must be monitored so that regulators can ensure security of the store, and operators can engineer reservoirs to avoid CO2 leakage. So there is a need to develop accurate and economical subsurface monitoring techniques. In parallel, tidal and particularly wind energy generation quadrupled in the past decade, with the expected capacity for wind energy to double again by 2030, according to Scottish Renewables. Yet three major off-shore areas proposed for wind farm development occupy areas related to CCUS (NSTA, 2022). Seismic subsurface CO2 monitoring vessels cannot operate close to wind farm infrastructure, and turbine noise raises concerns over signal to noise and repeatability requirements for seismic data. Novel technology from NOC has for the first time allowed signals from acoustic and seismic waves to be recorded every metre and every millisecond along optical fibres bound to power cables. They cross the seabed from land to tidal and wind farms, even up to individual turbines above the water surface. The ability to detect waves along the length of each fibre creates a new, densely distributed network of big-data sensors to monitor the solid Earth, ocean acoustics, and atmospheric sound off-shore. This relatively unexplored capability allows wind-farm noise to be recorded in real time so that it can be removed from seismic data to improve subsurface monitoring. The turbine noise itself is potentially a seismic source to monitor the subsurface, using seismic gradiometry, interferometry and neural network tomography of the recorded noise (Cao et al., 2020; Zhang et al., 2020; Zhang et al., 2022). This project will investigate these methods and develop others to improve subsurface CO2 monitoring, to monitor ocean acoustic signals from marine life and human activity, and to analyse acoustics in air above the sea and on land around power cable landing stations to detect human and other activity. Research questionsThe project aims to use signals recorded by optical fibres deployed at wind farms for environmental monitoring. This can include monitoring of the subsurface, marine life, ocean dynamics or human activity, and will develop as the project progresses. MethodologyYou will begin by exploring the signals of wind turbine noise recorded on optical fibres deployed on the seabed and on the turbines themselves. You will then explore using this noise as a seismic source to monitor the subsurface. You will also explore other signals recorded by the optical fibres, which could include signals from marine life, human activity, ocean currents and microseismicity. A variety of tools are available to assist in this analysis.

国际能源署表示，如果没有碳捕获、利用和封存（CCUS），我们就无法在2050年实现净零排放的目标。地下地质储存库必须受到监控，以便监管机构能够确保储存库的安全，操作人员可以设计储存库以避免二氧化碳泄漏。因此，需要开发准确、经济的地下监测技术。与此同时，据苏格兰可再生能源公司称，在过去十年中，潮汐能，特别是风能的发电量翻了两番，预计到2030年风能的发电量将再翻一番。然而，建议用于风电场开发的三个主要海上区域占据了与CCUS相关的区域（NSTA, 2022）。地震地下二氧化碳监测船不能在靠近风力发电场基础设施的地方工作，涡轮机的噪音引起了人们对信号噪声和地震数据可重复性要求的担忧。挪威国家石油公司的新技术首次允许声波和地震波的信号沿着连接电缆的光纤记录每米和每毫秒。它们穿过海床，从陆地到潮汐和风力发电场，甚至到水面上的单个涡轮机。探测每根光纤长度上的波的能力创造了一个新的、密集分布的大数据传感器网络，用于监测固体地球、海洋声学和近海大气声音。这种相对未开发的功能可以实时记录风电场的噪音，从而可以从地震数据中去除噪音，从而改善地下监测。涡轮噪声本身是监测地下的潜在震源，可以使用地震梯度测量法、干涉测量法和记录噪声的神经网络断层扫描（Cao等人，2020；Zhang等人，2020；Zhang等人，2022）。该项目将研究这些方法并开发其他方法，以改进地下二氧化碳监测，监测海洋生物和人类活动发出的海洋声学信号，并分析海上空气和电缆登陆站周围陆地的声学，以探测人类和其他活动。研究问题该项目旨在利用部署在风力发电场的光纤记录的信号进行环境监测。这可以包括对地下、海洋生物、海洋动态或人类活动的监测，并将随着项目的进展而发展。方法：您将首先探索在海底部署的光纤和涡轮机本身上记录的风力涡轮机噪声信号。然后，您将探索使用这种噪声作为震源来监测地下。你还将探索由光纤记录的其他信号，包括来自海洋生物、人类活动、洋流和微地震活动的信号。有各种各样的工具可以帮助进行这种分析。