CyberSEES: Type 2: Collaborative Research: Real-time Ambient Noise Seismic Imaging for Subsurface Sustainability

Cyber​​SEES：类型 2：协作研究：用于地下可持续性的实时环境噪声地震成像

• 批准号: 1442635
• 负责人: Yao Xie
• 金额: $ 26.95万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-01-15 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1442635&HistoricalAwards=false
• 关键词: CyberSEES; Type; Collaborative; Research; Real

This project creates a real-time Ambient Noise Seismic Imaging system, to study and monitor the subsurface sustainability and potential hazards of geological structures. Understanding and addressing the subsurface sustainability has significant impact on the natural, social, and economic issues of the region and across the globe. The system is comprised of a self-sustainable sensor network of geophones that can autonomously perform in-network computing of the 3D shallow earth structure images based on ambient noise alone. The project will study the subsurface sustainability of Long Beach, California and Yellowstone using their existing seismic array datasets and design the imaging system accordingly. In the late stages of the project, a field demonstration of the prototype system in Yellowstone expects to image the subsurface of some geysers. The techniques developed find further utility in monitoring and understanding the dynamics of subsurface oil, mine and geothermal resources, alongside concomitant hazards in oil exploration, mining, hydrothermal eruption, and volcanic eruption). Real-time imaging of shallow earth structures is essential to assess the sustainability and potential hazards of geological structures. The ability to deploy large wireless sensor arrays in challenging environments is significant for any real-time hazard monitoring and early warning system. The new approach taken is general, and can be implemented as a new field network paradigm for real-time imaging of highly dynamic and complex environments, including both natural and man-made structures. Results from this research will be shared with Yellowstone National Park management (NPS), rangers, and staff. The real-time subsurface images can be used in visitor education centers, official handouts, ranger led field trips, and for public safety management. The educational activities of this project include enhancing undergraduate and graduate curricula and research programs at the three collaborative universities, and the project provides many opportunities for a collaborative cross-disciplinary exchange of ideas among them.

该项目创建了一个实时环境噪声地震成像系统，以研究和监测地质结构的地下可持续性和潜在危害。了解和解决地下可持续性问题对该地区乃至全球的自然、社会和经济问题具有重大影响。该系统由一个自我维持的地震检波器传感器网络组成，可以仅根据环境噪声自主执行 3D 浅地地球结构图像的网络内计算。该项目将利用现有的地震阵列数据集研究加利福尼亚州长滩和黄石公园的地下可持续性，并相应地设计成像系统。在该项目的后期阶段，黄石公园原型系统的现场演示预计能够对一些间歇泉的地下进行成像。所开发的技术可进一步用于监测和了解地下石油、矿山和地热资源的动态，以及石油勘探、采矿、热液喷发和火山喷发中的伴随危害。浅层地球结构的实时成像对于评估地质结构的可持续性和潜在危害至关重要。在具有挑战性的环境中部署大型无线传感器阵列的能力对于任何实时危险监测和预警系统都具有重要意义。所采用的新方法是通用的，并且可以作为新的现场网络范例来实现，用于对高度动态和复杂的环境（包括自然和人造结构）进行实时成像。这项研究的结果将与黄石国家公园管理部门 (NPS)、护林员和工作人员分享。实时地下图像可用于游客教育中心、官方讲义、护林员带领的实地考察以及公共安全管理。该项目的教育活动包括加强三所合作大学的本科生和研究生课程以及研究项目，该项目为它们之间的跨学科协作交流思想提供了许多机会。