Collaborative Research: 3D Ambient Noise Tomography (3D ANT) for Natural Hazards Engineering

合作研究：用于自然灾害工程的 3D 环境噪声断层扫描 (3D ANT)

• 批准号: 2120155
• 负责人: Brady Cox
• 金额: $ 38.79万
• 依托单位: Utah State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2120155&HistoricalAwards=false
• 关键词: Collaborative; Research; 3D; Ambient; Noise

Despite significant progress in medical imaging, subsurface imaging for infrastructure engineering lags far behind. For example, many engineering analyses are still based on 1D profiles of the subsurface, or pseudo-2D/3D profiles constructed from several 1D soundings. When true 3D imaging is performed, the depth and resolution of exploration is often limited. While the problem of subsurface imaging is quite complex, the ability to develop rapid, realistic, 3D images of the subsurface, with accompanying engineering properties (e.g., shear modulus), would significantly advance engineering for more resilient and sustainable infrastructure. This research aims to develop a new 3D subsurface imaging method using recordings of ambient noise obtained from a grid of surface sensors. The new 3D Ambient Noise Tomography (3D ANT) method will provide a rapid, non-intrusive, robust way of imaging the subsurface in 3D at m-scales over the top 50- to 100-m of the subsurface. While numerous example applications for accurate and deep 3D subsurface imaging exist within infrastructure engineering, this project will specifically address two needs related to natural hazards: (1) the need for developing realistic 3D subsurface models for use in earthquake ground motion studies, and (2) the need for improved 3D in-situ imaging for anomaly (e.g., void/sinkhole) detection. Furthermore, significant and broad benefits for society, both anticipated and unanticipated, will result from developing deeper, higher-resolution 3D subsurface imaging methods. The ability to look inside the earth and retrieve rapid and reliable models using ambient noise will impact fields as diverse as: natural resource exploration, subsurface hydrology, pure earth science, archeology, underground development, military/security studies, and space/planet exploration. The intellectual merit of this research center around testing the hypothesis that accurate 3D subsurface P- and S-wave velocity models can be extracted at m-scales down to 50- to 100-m depth from surface recordings of ambient noise. To test this hypothesis, the research will develop a novel 3D ANT method and verify the method with numerical simulations and field experiments. The use of ambient noise for 3D subsurface imaging presents inherent challenges related to the uncontrollable frequency content and propagation direction of ambient noise. However, ambient noise is rich in low frequency energy, allowing for deeper imaging than what is currently possible using active-source 3D full waveform inversion (FWI) methods. Hence, 3D ANT, when coupled with active-source 3D FWI, will provide high resolution images to depths presently unobtainable. The 3D ANT method will require collecting ambient noise recordings from a 2D grid of closely spaced surface sensors. The noise recordings will be used to extract experimental correlation functions between every possible pair of sensors. 3D viscoelastic wave equations will then be used to obtain synthetic correlation functions, which will be matched with the experimental ones using a Gauss-Newton FWI approach for extracting 3D subsurface models. Optimization of the 3D ANT algorithm will include parametric studies on field testing configurations (i.e., number and spacing of sensors) and ambient noise characteristics (i.e., frequency content and azimuthal distribution). Ultimately, two well-characterized field sites with ground truth have been selected to test the methodology under real-world conditions. This research will only achieve its broadest impact if we are successful at training students to carry it into the future, disseminating results, and developing tools that practitioners can use in industry. We aim to tackle these challenges while simultaneously broadening the participation of women in natural hazards engineering. Hazards engineering is about transforming how civil infrastructure can be designed and rehabilitated such that communities and individuals are more resilient to the devastating effects of natural hazards, and studies have shown that women are more interested in STEMM fields when they have direct societal impacts. This work will help foster a natural intersection of interest and purpose in a diverse and talented group of future engineers with skills that will be critical for revolutionizing natural hazards engineering, such as coding, analyzing big-data, and supercomputing.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.

尽管医学成像取得了重大进展，但基础设施工程的地下成像远远落后。 例如，许多工程分析仍然基于地下的1D剖面，或由若干1D探测构造的伪2D/3D剖面。 当执行真正的3D成像时，探测的深度和分辨率通常是有限的。 虽然地下成像的问题是相当复杂的，但是开发具有伴随的工程特性（例如，剪切模量），将大大推进更具弹性和可持续基础设施的工程。 本研究的目的是开发一种新的三维地下成像方法，使用从网格的表面传感器获得的环境噪声的记录。新的3D环境噪声层析成像（3D ANT）方法将提供一种快速、非侵入性、鲁棒的方式，在地下50至100米的顶部以m尺度对地下进行3D成像。虽然在基础设施工程中存在许多用于精确和深层3D地下成像的示例应用，但该项目将专门解决与自然灾害相关的两个需求：（1）开发用于地震地面运动研究的逼真3D地下模型的需求，以及（2）改进异常3D原位成像的需求（例如，空隙/陷孔）检测。 此外，开发更深、更高分辨率的3D地下成像方法将为社会带来预期和未预期的重大和广泛的利益。 使用环境噪声观察地球内部并检索快速可靠模型的能力将影响不同的领域：自然资源勘探，地下水文学，纯地球科学，考古学，地下开发，军事/安全研究和空间/行星探索。该研究中心的智力价值在于测试以下假设：可以从环境噪声的表面记录中提取m尺度下至50至100 m深度的精确三维地下P波和S波速度模型。 为了验证这一假设，本研究将开发一种新的3D ANT方法，并通过数值模拟和现场实验验证该方法。 将环境噪声用于3D地下成像提出了与环境噪声的不可控频率内容和传播方向相关的固有挑战。 然而，环境噪声富含低频能量，允许比当前使用有源3D全波形反演（FWI）方法可能的成像更深的成像。 因此，3D ANT在与有源3D FWI耦合时，将向目前无法获得的深度提供高分辨率图像。 3D ANT方法将需要从紧密间隔的表面传感器的2D网格收集环境噪声记录。 噪声记录将用于提取每对可能的传感器之间的实验相关函数。三维粘弹性波动方程，然后将用于获得合成的相关函数，这将是匹配的实验使用高斯-牛顿FWI方法提取三维地下模型。 3D ANT算法的优化将包括对现场测试配置的参数研究（即，传感器的数量和间隔）和环境噪声特性（即，频率含量和方位角分布）。 最后，两个良好的特点与地面实况现场已被选定在现实世界的条件下测试的方法。 这项研究将只实现其最广泛的影响，如果我们成功地培训学生进行到未来，传播成果，并开发从业者可以在行业中使用的工具。我们的目标是应对这些挑战，同时扩大妇女对自然灾害工程的参与。 灾害工程是关于改变民用基础设施的设计和恢复方式，使社区和个人对自然灾害的破坏性影响更具弹性，研究表明，当它们具有直接的社会影响时，女性对STEM领域更感兴趣。 这项工作将有助于培养一个多元化和有才华的未来工程师群体的兴趣和目的的自然交叉点，这些工程师的技能对于革命性的自然灾害工程至关重要，例如编码，分析大数据和超级计算。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

项目成果

Using convolutional neural networks to develop starting models for near-surface 2-D full waveform inversion

使用卷积神经网络开发近地表二维全波形反演的起始模型

• DOI: 10.1093/gji/ggac179
• 发表时间: 2022
• 期刊: Geophysical Journal International
• 影响因子: 2.8
• 作者: Vantassel, Joseph P.;Kumar, Krishna;Cox, Brady R.
• 通讯作者: Cox, Brady R.

In-situ characterization of the near-surface small strain damping ratio at the Garner Valley Downhole Array through surface waves analysis

通过表面波分析对加纳谷井下阵列近地表小应变阻尼比进行原位表征

• 发表时间: 2022
• 期刊: 4th International Conference on Performance-based Design in Earthquake Geotechnical Engineering
• 作者: • Aimar, M.;Francavilla, M.;Cox., B.R.;Foti, S.
• 通讯作者: Foti, S.

SWprocess: a workflow for developing robust estimates of surface wave dispersion uncertainty

• DOI: 10.1007/s10950-021-10035-y
• 发表时间: 2022-04
• 期刊: Journal of Seismology
• 影响因子: 1.6
• 作者: J. Vantassel;B. Cox

Influence of different starting models on near-surface two-dimensional full waveform inversion

不同启动模型对近地表二维全波形反演的影响

• 发表时间: 2022
• 期刊: 20th International Conference on Soil Mechanics and Geotechnical Engineering
• 作者: Vantassel, J.P.;Cox, B.R.
• 通讯作者: Cox, B.R.

Distributed Acoustic Sensing for Extracting High-Resolution, Multi-Mode Surface Wave Dispersion Data using Multi-channel Analysis of Surface Waves

使用表面波多通道分析提取高分辨率、多模式表面波色散数据的分布式声学传感

• 发表时间: 2022
• 期刊: 4th International Conference on Performance-based Design in Earthquake Geotechnical Engineering
• 作者: Vantassel, J.P.;Cox, B.R.;Hubbard, P.;Yust, M.;Menq, F-Y.;Spikes, K.;Fratta, D.
• 通讯作者: Fratta, D.