Collaborative Research: Improving the Interpretability of Tomographic Images Using Geologically Motivated Parametrizations

合作研究：利用地质驱动的参数化提高断层扫描图像的可解释性

基本信息

批准号：
2011079
负责人：
Victor Tsai
金额：
$ 25.59万
依托单位：
Brown 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：
2020-08-01 至 2024-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2011079&HistoricalAwards=false
关键词：
Collaborative Research Improving Interpretability Tomographic

项目摘要

Geophysical imaging is one of the cornerstones of the Earth Sciences. Tomographic imaging techniques provide spatial descriptions of geologic features of the interior of the Earth that are otherwise inaccessible, and thus comprises a primary source of insight into the geometry of structures inside the Earth. These images are essential to understanding the evolution and dynamics of the Earth, from the relatively short length and timescales that govern natural hazards such as seismicity and volcanism, to fundamental questions of the origins of first order features such as patterns of continental motion and mountain building. This project investigates ways to fundamentally improve geophysical imaging by incorporating geological knowledge into imaging tools rather than relying solely on standard mathematical tools for imaging. Specific imaging targets include the Los Angeles, San Gabriel and San Bernardino basins, which are essential to accurately define to improve seismic hazard calculations at high frequencies and will help characterize earthquake risk in this societally important region. Another target is imaging the Yellowstone Caldera, where improved imaging can lead to better understanding of the dynamics of crustal magma emplacement and volcanic eruption dynamics. The work also brings together diverse communities of geophysicists and mathematicians and supports the education of graduate and undergraduate students.Geophysical imaging problems are fundamentally ill-posed so careful choices of parametrization and regularization are required to produce sensible results, especially at regional and global length scales where data are particularly scarce. Parametrizations in terms of blocks, pixels or spherical harmonics are typically driven by mathematical utility. These parametrizations ignore the fact that the end goal of tomographic imaging is typically to categorize the subsurface into discrete structures. Previous improvements in geophysical imaging have been driven by advancements in the solution of forward problems, the development of adjoint methods for large scale optimization and methods for uncertainty quantification, but comparatively little progress has been made regarding development of effective parametrization strategies for the Earth. This work melds together an innovative geometric and level set parametrization strategy for specifying Earth structure with a best-in-class derivative-free optimization scheme based on the Ensemble Kalman Filter. The project focuses on two problems that are impactful and provide complementary test cases of the team's methodology. The first application focuses on geometric optimization of geological units in the Los Angeles, San Gabriel and San Bernardino basins, from which better calculations of earthquake ground motions within the basin may be calculated. A second application at Yellowstone Caldera allows better quantification of the tradeoffs between magma chamber volume and melt fraction estimates, as determined by velocity perturbations using local and teleseismic body wave tomography.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.

地球物理成像是地球科学的基石之一。断层成像技术提供了无法接近地球内部的地质特征的空间描述，因此包括对地球内部结构几何形状的主要见解。这些图像对于理解地球的演变和动态至关重要，从统治自然危害（例如地震性和火山主义）的相对较短的时间和时间尺度到对一级特征的起源的基本问题，例如大陆运动和山区建筑的模式。该项目通过将地质知识纳入成像工具，而不是仅依靠标准的数学工具来进行成像，从而研究了从根本上改善地球物理成像的方法。特定的成像目标包括洛杉矶，圣加布里埃尔和圣贝纳迪诺盆地，这对于准确定义以改善高频的地震危险计算至关重要，并将有助于在这个社会重要地区表征地震风险。另一个目标是成像黄石火山口，改进的成像可以更好地理解地壳岩浆增压和火山喷发动力学的动力学。这项工作还汇集了各种地球物理学家和数学家的社区，并支持研究生和本科生的教育。地球物理成像问题从根本上讲是根本上不足的，因此需要仔细的参数化和正则化选择以产生明智的结果，尤其是在区域和全球长度尺度上，数据尤其稀少。块，像素或球形谐波的参数化通常是由数学实用程序驱动的。这些参数忽略了以下事实：断层成像的最终目标通常是将地下分类为离散结构。地球物理成像的先前改进是由解决方案问题的进步，大规模优化的伴随方法的发展以及不确定性量化的方法的发展，但是在开发地球有效参数策略方面取得了相对较少的进步。这项工作融合了一种创新的几何和水平设定参数化策略，用于用基于集合卡尔曼滤波器的一流衍生品优化方案来指定地球结构。该项目着重于两个有影响力的问题，并提供了团队方法论的互补测试案例。第一个申请的重点是洛杉矶，圣加布里埃尔和圣贝纳迪诺盆地的地质单位的几何优化，可以从中计算出盆地内地震地面运动的更好计算。黄石火山口的第二次应用程序可以更好地量化岩浆室数量和熔体分数估计之间的权衡，这是通过使用本地和伸展性人体波浪层析成像的速度扰动来确定的。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识功能和广泛影响的评估来评估的，并被认为是值得的。