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

• 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

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.

地幔的动力学导致了各种地质活动，包括地震、火山喷发、大陆漂移，甚至是调节地表温度的长期碳循环。地幔动力学最重要的参数是粘度，它决定了岩石变形的速度有多快，但粘度也是地球物质最不被了解的属性之一。岩石变形实验对粘度提供了重要的限制，但实验室条件与地幔条件有很大不同；地幔的变形速度比实验室实验慢10个数量级。通过将实验数据分析方面的最新进展与一种新的地球动力学模型相结合，拟议的项目将建立一个理论框架，有效地将岩石变形实验和地球物理观测联系起来，并使人们能够更好地了解地幔粘度。由于其相对简单的构造环境，大洋地幔的动力学将成为这一多学科项目的理想试验台。该项目支持研究生的培养，并为本科生进行高级研究项目提供主题。硅酸盐岩石的变形取决于许多因素，包括温度、压力、应力、颗粒大小、水分含量、熔体分数和氧逸度。近年来，将这些因素纳入地球物理建模已变得越来越普遍。与此同时，在实验岩石力学方面有两条重要的发展线索，这两条线索都可以直接影响将岩石力学知识纳入地球物理模型的努力。首先，橄榄石集合体的流变性通常被认为控制了上地幔的动力学，长期以来一直被认为主要由扩散蠕变和位错蠕变共同控制，但最近的实验研究表明，晶界滑动可能起到比之前认为的更重要的作用。其次，我们看到了使用马尔科夫链蒙特卡罗(MCMC)抽样的新统计框架的发展，该框架帮助我们解决了从变形数据估计流动规律的全部复杂性。MCMC反演方法的改进使我们能够利用实验岩石力学和观测地震学的最新进展，对海底地幔动力学进行一种新的地球物理模拟。该项目有三个主要目标：(1)根据已公布的实验数据建立橄榄石聚集体的候选流动规律模型；(2)对海底地幔动力学进行概率模拟；(3)确定关键的流动规律不确定性，并设计能够解决这种不确定性的可能的实验装置。这种基于概率模拟的方法不仅可以更好地了解海底地幔的动力学，而且还可以更好地了解橄榄石集合体的流变性。

项目成果

Global Analysis of Experimental Data on the Rheology of Olivine Aggregates

橄榄石聚集体流变学实验数据的全局分析

• DOI: 10.1029/2018jb016558
• 发表时间: 2019
• 期刊: Journal of Geophysical Research: Solid Earth
• 作者: Jain, Chhavi;Korenaga, Jun;Karato, Shun‐ichiro
• 通讯作者: Karato, Shun‐ichiro