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Autonomous Techniques for anthropogenic Structure Ecological Assessment (AT-SEA)

Autonomous Techniques for anthropogenic Structure Ecological Assessment (AT-SEA)
人为结构生态评估自主技术(AT-SEA)
批准号:
NE/T010592/1
负责人:
Blair Thornton
金额:
$21.3万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2021
资助国家:
英国
项目状态:
未结题
起止时间:
2021 至 --

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中文摘要
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英文摘要
Thousands of Oil & Gas industry structures in the sea are approaching the end of their lives. At this time, they typically need to be removed and the environment returned to a safe state. This process is known as decommissioning. As many of these sites are old (typically 20+ years) and originally were drilled before the current environmental regulations existed, there has often been some contamination of the seabed around these sites. To ensure that no harmful effects will occur, decommissioning operations need to be supported by an environmental assessment and subsequent monitoring. Monitoring may be required over many years after decommissioning, especially if some structures are left in place. Monitoring surveys in the offshore environment are expensive and time-consuming, requiring ships and many specialist seagoing personnel. This requirement, although vital, will have a considerable cost for industry and the public.Ocean robots, which use computer systems to carry out survey missions by themselves, are regularly used in detailed scientific assessments of the environment. As they collect very high-quality data quickly, such robots have recently been adopted for some tasks by industry but these still require an expensive support ship as they are not capable of long-range missions. Recent technological developments have cut the cost and expanded the range of these robots to thousands of kilometres, making it possible for long-range assessments of multiple sites to be undertaken with a robot launched from the shore. This would have many advantages, improving the quality and quantity of environmental information while cutting the costly requirement for a survey ship and crew. We will carry out the first fully autonomous environmental assessment of multiple decommissioning sites. The Autosub long-range ocean robot submarine ("Boaty McBoatface") will be launched from the shore in Shetland, visit and carry out an environmental assessment at three decommissioning sites in the northern North Sea, before returning around 10 days later with the detailed survey information onboard. The robot will take photographs of the seabed, and these will be automatically stitched together to make a map of the seafloor, structures present, and the animals that live there. Established sensor systems will measure a range of properties of the water, including the presence of oil and gas. As well as the decommissioned sites, the robot will visit a special marine protected area where we know there are natural leaks of gas, to check the robot can reliably detect a leak if it did occur.On return to shore, the project will examine all the data obtained and compare it to that gathered using standard survey ship methods. We will test if the same environmental trends can be identified from both datasets to determine if the automated approach would be a suitable replacement for standard survey ship operations. The project will also produce a fully documented case study, which includes detailed information on the costs and benefits, practical information on deployments and approaches to reduce the risks and improve the efficiency of operations. This will be used by industry, scientists and government regulators, to demonstrate the techniques and will provide the necessary information to potential users to aid in their adoption. The overall goal of the project is to improve the environmental protection of the North Sea at a reduced cost and to demonstrate how this leading UK robotic technology could be used worldwide.
期刊论文(6)
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会议论文
High-resolution visual seafloor mapping and classification using long range capable AUV for ship-free benthic surveys
使用远程 AUV 进行高分辨率视觉海底测绘和分类,以进行无船海底调查
DOI: --
发表时间: 2023
期刊:
影响因子: --
作者: [Bodenmann A]
通讯作者: Bodenmann A
DOI: 10.55417/fr.2022037
发表时间: 2021-08
期刊: ArXiv
影响因子: --
作者: [Takaki Yamada;A. Prügel-Bennett;Stefan B. Williams;O. Pizarro;B. Thornton]
通讯作者: Takaki Yamada;A. Prügel-Bennett;Stefan B. Williams;O. Pizarro;B. Thornton
Leveraging Metadata in Representation Learning With Georeferenced Seafloor Imagery
利用地理参考海底图像的表示学习中的元数据
DOI: 10.1109/lra.2021.3101881
发表时间: 2021
期刊: IEEE Robotics and Automation Letters
影响因子: 5.2
作者: [Yamada T]
通讯作者: Yamada T
Auto-calibration of line-laser structured-light seafloor mapping systems
线激光结构光海底测绘系统的自动校准
DOI: 10.23919/oceans44145.2021.9705873
发表时间: 2021
期刊:
影响因子: --
作者: [Stanley D]
通讯作者: Stanley D
RamaCam - In situ holographic imaging and chemical spectroscopy for long term scalable analysis of marine particles in deep-sea environments
  • 批准号:
    NE/R01227X/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $10.26万
  • 财政年份:
    2018
  • 负责人:
    Blair Thornton
  • 依托单位:
BioCam - Mapping of Benthic Biology, Geology and Ecology with Essential Ocean Variables
  • 批准号:
    NE/P020887/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $74.87万
  • 财政年份:
    2017
  • 负责人:
    Blair Thornton
  • 依托单位:
国内基金
海外基金
EstimatingLarge Demand Systems with MachineLearning Techniques
  • 批准号:
    --
  • 项目类别:
    外国学者研究基金
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    IoshuaAlex
  • 依托单位: