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CAREER: Real-time In-situ Characterization of Evolving Rock Systems for Smart-controlled Subsurface Engineering

职业：智能控制地下工程演化岩石系统的实时现场表征

基本信息

批准号：
1944812
负责人：
Fatemeh Pourahmadian
金额：
$ 50万
依托单位：
University of Colorado at Boulder
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：
2020-06-01 至 2025-05-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1944812&HistoricalAwards=false
关键词：
CAREER Real time situ Characterization

项目摘要

This Faculty Early Career Development (CAREER) grant will establish an integrated research and education program aimed at the next generation of physics-based data analytics to enable holistic (multiscale and multiphysics) characterization of the subsurface in real time. Coupled physics processes driven by engineered stimulation of the subsurface underlie many emerging technologies germane to advanced geo-infrastructures; examples include sustainable energy mining from enhanced geothermal systems and intelligent mitigation of the affiliated environmental impacts. Optimal design and closed-loop control of such operations require real-time feedback on the nature of progressive variations in the target subterranean regions. 3D in-situ tracking of multiphysics processes in such environments is, however, exceptionally challenging; engineered treatments (such as fluid or gas injection) are often induced in a complex domain whose structure and material properties are unknown (or uncertain) across multiple scales. Nevertheless, existing approaches to in-situ monitoring mostly rely on simplistic characterization of the subsurface, and mainly ignore the multiscale and coupled-physics nature of the induced processes in data inversion. Moreover, these tools are by and large computationally expensive and inapplicable for real-time sensing, or only amenable to ad hoc sensory configurations. Therefore, there exists a critical need for fast (yet robust) holistic data processing tools that transcend some of these limitations. In light of the fast-paced developments in sensing instruments, furnishing high-resolution spatiotemporal measurements and big data sets, such advances in data analytics is paramount for engineered systems of the future.The research component of this project aims to establish a comprehensive (analytical, computational, and experimental) platform for: (1) real-time geometric reconstruction of advancing interfaces and volumetric process zones in multiphasic subterranean domains of a-priori unknown properties, (2) high-fidelity hydro-mechanical characterization of thus-recovered regions, and (3) verification and validation of these developments in a laboratory setting for better understanding of injection-induced multiphasic variations in randomly fractured rock masses pertinent to enhanced geothermal systems. This will be accomplished by taking advantage of the most recent advances in applied mathematics, geophysics, biomedical engineering, and sensor technology. In particular, the inverse solution is built upon three fundamental lynchpins: (i) inverse scattering and the theory of transmission eigenvalues, (ii) Marchenko integral equations and the generalized autofocusing concept, and (iii) non-iterative solutions to full-field inversion. The education component of this project aims at: (1) integration of the interdisciplinary knowledge underpinning state-of-the-art data processing tools for complex environments into the curriculum of science and engineering students at CU-Boulder and outreach activities, and (2) cultivating an effective knowledge transfer from research to academia and practice that includes all the stakeholders. In this vein, a three-tier educational program will be developed, involving: (i) engineering outreach to K-12 students with emphasis on underrepresented minorities, (ii) introducing WISE: wave-based inversion in subterranean environments as a new thrust in the engineering program at CU Boulder, and (iii) multilateral collaborations among scientists, engineers, and practitioners at regional, national and international levels.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.

这笔学院早期职业发展(Career)赠款将建立一个综合研究和教育计划，旨在实现基于物理的下一代数据分析，以实现对地下表面的全面(多尺度和多物理)实时表征。地下工程刺激所驱动的耦合物理过程是与先进的地质基础设施密切相关的许多新兴技术的基础；例如，从强化的地热系统中进行可持续能源开采以及智能地减轻相关的环境影响。此类作业的优化设计和闭环控制需要对目标地下区域的渐进变化的性质进行实时反馈。然而，在这样的环境中对多物理过程进行3D原位跟踪是非常具有挑战性的；工程处理(如流体或气体注入)通常是在一个复杂的领域中进行的，其结构和材料特性在多个尺度上是未知的(或不确定的)。然而，现有的现场监测方法大多依赖于对地下的简单化描述，主要忽略了数据反演中诱发过程的多尺度和耦合物理性质。此外，总的来说，这些工具的计算成本很高，不适用于实时检测，或者仅适用于特殊的感官配置。因此，迫切需要快速(但健壮)的整体数据处理工具，以超越其中一些限制。鉴于传感仪器、提供高分辨率时空测量和大数据集的快速发展，这种数据分析方面的进展对于未来的工程系统至关重要。该项目的研究部分旨在建立一个综合的(分析、计算和实验)平台：(1)先验未知性质的多相地下区域中推进界面和体积过程区域的实时几何重建，(2)由此恢复的区域的高保真流体力学表征，以及(3)在实验室环境中验证和确认这些发展，以便更好地了解与增强型地热系统相关的随机裂隙岩体中注入引起的多相变化。这将通过利用应用数学、地球物理、生物医学工程和传感器技术的最新进展来实现。特别地，逆解建立在三个基本的基础上：(I)逆散射和传输本征值理论，(Ii)Marchenko积分方程和广义自聚焦概念，以及(Iii)全场反演的非迭代解。该项目的教育部分旨在：(1)将支持最先进的复杂环境数据处理工具的跨学科知识融入博尔德大学理工科学生的课程和外联活动，(2)培养从研究到学术和实践的有效知识转移，包括所有利益攸关方。在这一背景下，将制定一个三级教育计划，涉及：(I)面向K-12学生的工程推广，重点是未被充分代表的少数族裔；(Ii)引入WISE：在地下环境中基于波的反演作为CU Boulder工程计划的新重点；以及(Iii)在地区、国家和国际层面的科学家、工程师和从业人员之间的多边合作。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。