RCN: Distributed Acoustic Sensing (DAS) in Geosciences and Engineering

研究协调网络（RCN）的目的是促进和扩展分布式声传感（DAS）在地球科学和工程中的应用。DAS沿着埋在地下或钻孔中的光纤，以1米的间隔感知地面振动。DAS已经在数十公里的距离上成功实施，用于探测地震、监测地热储层和碳封存点，以及监测交通和民用基础设施。RCN将接触光电子学和机器学习领域的研究人员，以发展这些社区与地球科学和工程之间的协同作用。RCN的活动将集中在年度，多天的研讨会和短期课程，以及专题网络研讨会。一门课程将是实地密集的，另一门课程将致力于数据分析。社区活动的指导和方向将由主要调查人员和一个多学科指导委员会负责。RCN指导委员会由在DAS应用、技术、数据分析、数据解释和数据管理方面具有广泛专业知识的成员组成。指导委员会包括几位职业生涯早期的成员。早期职业科学家和研究生是RCN许多活动的目标受众。RCN还将努力将来自不同国际研究组织、工业、技术公司和政府机构的DAS研究人员和用户聚集在一起，在DAS开发和应用中发挥协同作用，提高资源的有效利用。RCN将加速DAS应用的技术转移和社会重要监测技术的发展，如自然灾害和工程基础设施。DAS可以感知连续光纤阵列的变形，这些光纤阵列可以跨越数十公里，空间分辨率为米，宽带响应从毫赫到千赫兹。DAS已应用于1)利用环境噪声对近地表成像，2)垂直地震剖面（VSP）， 3)地震地震学，4)碳氢化合物、碳封存和地热储层的地球物理监测，以及5)交通和工业设施的基础设施监测。机器学习和利用电信网络中的暗光纤（不用于通信的多余光纤）是令人兴奋的新发展。即将到来的其他应用包括监测冰川和雪崩的变形，斜坡稳定性，以及长距离的民用基础设施，如道路，管道和铁路。同时，DAS技术本身也是研究的对象，并且正在迅速改进。RCN将为管理和归档每天tb级的数据提供指导，以应对负责提供开放数据访问的研究团队和联邦机构面临的DAS数据挑战。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The purpose of the Research Coordination Network (RCN) is to advance and extend the applications of Distributed Acoustic Sensing (DAS) in geosciences and engineering. DAS senses ground vibration at one-meter spacing along optical fiber that is buried in the ground or in a borehole. DAS has been successfully implemented over distances of tens of kilometers for detecting earthquakes, monitoring geothermal reservoirs and carbon sequestration sites, and monitoring traffic and civil infrastructure. The RCN will reach out to researchers in optoelectronics and machine learning to develop synergies between these communities and geosciences and engineering. The RCN activities will be focused around annual, multi-day workshops and short courses, and topical webinars. One course will be field intensive and one will be devoted to data analysis. Guidance and direction for the community activities will be by the principal investigators and a multidisciplinary steering committee. The RCN steering committee is comprised of members with broad expertise in DAS applications, technology, data analysis, data interpretation, and data management. The steering committee includes several early-career members. Early-career scientists and graduate students are the target audience for many of the RCN activities. The RCN will also strive to bring together DAS researchers and users from a diverse international base of research organizations, industry, technology companies, and government agencies to exploit synergies and enhance efficient utilization of resources in DAS development and applications. The RCN will speed the development of technology transfer of DAS applications and technology to societally important monitoring, such as natural hazards and engineering infrastructure.DAS senses deformation in continuous fiber-optic arrays, which can span tens of kilometers with a spatial resolution of meters and with a broadband response from millihertz to kilohertz. DAS has been applied to 1) imaging the near-surface using ambient noise, 2) Vertical Seismic Profiling (VSP), 3) earthquake seismology, 4) geophysical monitoring of hydrocarbon, carbon sequestration and geothermal reservoirs, and 5) infrastructure monitoring of traffic and industrial facilities. Machine learning and utilization of dark fiber in telecommunication networks (excess fiber not used for communication) are exciting new developments. Other applications on the horizon include monitoring deformation in glaciers and snow avalanches, slope stability, and long-distance, civil infrastructure such as roads, pipelines, and rail. Meanwhile DAS technology itself is the subject of research and is rapidly improving. The RCN will provide guidance for managing and archiving terabytes per day of data to meet the challenges DAS data present to research teams and federal agencies charged with providing open data access.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.