Markov chain Monte Carlo inversion of Rock Deformation Data: Applications to the Dynamics of Oceanic Mantle

岩石变形数据的马尔可夫链蒙特卡罗反演：在大洋地幔动力学中的应用

基本信息

批准号：
1736563
负责人：
Jun Korenaga
金额：
$ 16.12万
依托单位：
Yale University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-15 至 2020-01-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1736563&HistoricalAwards=false
关键词：
Markov chain Monte Carlo inversion

项目摘要

The dynamics of Earth's mantle are responsible for all kinds of geological activities including earthquakes, volcanic eruptions, continental drift, and even the long-term carbon cycle that regulates the surface temperature. The most important parameter of mantle dynamics is viscosity, which dictates how fast rocks can deform, but viscosity is also among the least understood properties of Earth materials. Rock deformation experiments provide important constraints on viscosity, but laboratory conditions are vastly different from mantle conditions; the rate of deformation for the mantle is 10 orders of magnitude slower than that for the laboratory experiments. By combining recent progress in the analysis of experimental data with a new kind of geodynamical modeling, the proposed project will build a theoretical framework that effectively bridges rock deformation experiments and geophysical observations and allows an improved understanding of mantle viscosity. Owing to its relatively simple tectonic setting, the dynamics of the oceanic mantle will serve as an ideal test bed for this multidisciplinary project. The project supports the training of a graduate student and provides topics for undergraduate students conducting senior research projects.The deformation of silicate rocks depends on a number of factors, including temperature, pressure, stress, grain size, water content, melt fraction, and oxygen fugacity. Incorporating such factors into geophysical modeling has become increasingly more common in recent years. At the same time, there have been two important threads of development in experimental rock mechanics, both of which can directly impact such efforts to incorporate the knowledge of rock mechanics into geophysical modeling. First, the rheology of olivine aggregates, which is usually thought to control the dynamics of the upper mantle, has long been considered to be governed mostly by the combination of diffusion creep and dislocation creep, but recent experimental studies suggest that grain boundary sliding may play a more important role than previously thought. Second, we have seen the development of a new statistical framework, using Markov Chain Monte Carlo (MCMC) sampling, that helps us to tackle the full complexity of estimating flow laws from deformation data. The improved command of MCMC inversion puts us into a unique position to conduct a new kind of geophysical modeling for the dynamics of suboceanic mantle by taking advantage of recent progress in both experimental rock mechanics and observational seismology. This project has three major objectives: (1) construct candidate flow-law models for olivine aggregates based on published experimental data; (2) conduct probabilistic modeling for the dynamics of suboceanic mantle; and (3) identify key flow-law uncertainties and design possible experimental setups that can resolve such uncertainties. The approach based on probabilistic modeling has potential to bring a better understanding of not only the dynamics of suboceanic mantle but also the rheology of olivine aggregates.

地球地幔的动力学负责各种地质活动，包括地震，火山喷发，大陆漂移，甚至是调节表面温度的长期碳循环。地幔动力学的最重要参数是粘度，它决定了岩石的变形速度，但粘度也是地球材料的最不理知识的特性之一。岩石变形实验对粘度提供了重要的限制，但是实验室条件与地幔条件大不相同。地幔的变形速率比实验室实验慢10个数量级。通过将实验数据分析的最新进展与一种新型的地球动力模型结合在一起，该项目将建立一个理论框架，有效地桥接了岩石变形实验和地球物理观察结果，并可以提高对地幔粘度的理解。由于其相对简单的构造设置，海洋披风的动力学将成为这个多学科项目的理想测试床。该项目支持研究生的培训，并为从事高级研究项目的本科生提供主题。硅酸盐岩石的变形取决于许多因素，包括温度，压力，压力，谷物尺寸，水分，水分，融化分数和氧气散发性。近年来，将这些因素纳入地球物理建模已变得越来越普遍。同时，实验性岩石力学中已经有两个重要的发展线索，这两者都可以直接影响将岩石力学知识纳入地球物理建模中的这种努力。首先，通常认为橄榄石聚集体的流变学一直被认为主要由扩散蠕变和脱位蠕变的组合所控制，但最近的实验研究表明，晶粒边界滑动可能比以前想到的更重要。其次，我们已经看到了使用马尔可夫链蒙特卡洛（MCMC）采样的新统计框架的发展，这有助于我们解决从变形数据中估算流量法的全部复杂性。 MCMC反演的改进命令使我们处于独特的位置，通过利用实验性岩石力学和观察性地震学的最新进展，对次生地幔动态进行一种新型的地球物理建模。该项目具有三个主要目标：（1）基于已发表的实验数据构建橄榄石聚集体的候选流量法模型；（2）进行次生套的动力学进行概率建模；（3）确定可以解决此类不确定性的关键流程不确定性和设计可能的实验设置。基于概率建模的方法不仅可以更好地理解底层地幔的动力学，而且还可以使橄榄石聚集体的流变学有所了解。