Collaborative Research: Wave Equation Tomography and Data Assimilation: A New Approach to Estimating P and S Speed Variations in Earth's Lower Mantle

主要研究人员寻求合作研究资金，旨在通过明确整合地震数据分析和解释的观测、理论和计算方面，开发一类新的层析模型。这项工作扩展了他们以前在断层扫描方面的工作，涉及新数据集的测量和波传播理论和多网格技术的发展，这些技术允许对地球结构具有不同灵敏度的数据进行联合解释。在我们看来，这些组成部分的定量集成是实现弹性特性、温度和组成的空间变化精确映射的可行和必要的一步。在这里，PI将关注地球下地幔底部~1000公里处VP和VS的相对变化，他们认为，这包含了理解地幔对流和地球在地质时期的热化学演化的关键线索。知识价值：在过去的几十年里，全球断层扫描产生了壮观的图像，例如地幔流动轨迹和地幔底部附近的结构复杂性。然而，不均匀的数据覆盖和异构的数据质量导致非唯一的模糊图像，在可靠性方面存在很大的空间差异。即使在采样似乎足够的情况下，正则化和使用不准确的波传播理论也可能产生不正确的弹性参数估计，并且波速变化的幅度通常受到很差的约束。此外，基于不同数据集的结果往往在重要方面存在分歧，正确联合解释对地球结构具有不同灵敏度的数据（例如，以不同频率测量的体波和面波，P波或S波）仍然是一项重大挑战。“红蓝”图像的近似性质阻碍了定量解释和与其他地球物理约束的整合，并使断层扫描无法充分发挥其作为地球深层内部定量探测的潜力。这是PI想要改变的。为了更好地估计参数，他们需要利用宽带波形的丰富性，他们需要更强大的理论框架来整合和联合解释不同的数据集。我们对全球断层扫描的多分辨率数据融合方法的最终目标是通过改进（并明确链接）成像的三个基本方面，在一系列长度尺度和各种地震数据上产生更好的地球深层三维模型：数据质量和覆盖范围：使用自动化程序和多分辨率概念（如时频小波），他们将通过从国际数据中心提供的大量波形中提取相速度和到达时间信息来增强空间和光谱数据覆盖。波传播理论：认识到需要考虑（并从中受益）所考虑的数据的不同采样特性，并受到最近在理解有限频率效应方面的进展的启发，他们将为新测量数据的反投影计算准确的灵敏度核。参数化和正则化：为了保持和利用三维灵敏度核的局部化特性，我们将使用自适应多网格参数化和正则化技术进行联合反演。本文的研究重点是(1)测量远震P型和S型体波传播时间，(2)反演. lnvs /的三维变化。地幔中的lnVP（或相关参数），以及（iii）完善或反驳关于最下层地幔成分非均质性的现有观点。他们可以建立在观测地震学和断层扫描（Van der Hilst， MIT）和波传播和反演理论（De Hoop， CSM）的经验基础上，在自动化数据处理方面，他们将与Ritsema（法国IPGP）合作，并涉及一名博士后助理（寻求一些基金匹配）。更广泛的影响：除了矿物物理数据外，还需要对弹性参数进行准确估计，以限制成分和温度的空间变化，从而建立地幔动力学和矿物学模型。此外，这里开发的数据融合概念和工具为处理和解释USARRAY数据的大型数据集做了准备。拟议的工作构成了麻省理工学院博士项目的第一部分，但麻省理工学院和CSM的学生将参与研究的各个方面，要么作为本科研究机会（UROP），要么满足一般考试要求。

The Principal Investigators seek funding for collaborative research that aims to develop a new class of tomographic model by explicit integration of observational, theoretical, and computational aspects of seismic data analysis and interpretation. This effort extends their previous work in tomography and involves the measurement of new data sets and the development of wave propagation theory and multi-grid technology that allowsjoint interpretation of data with different sensitivities to Earth's structure. Quantitative integration of thesecomponents is, in our view, a viable and essential step toward the accurate mapping of spatial variations in elastic properties, temperature, and composition. Here the PI's will focus on relative variations in VP and VS in the bottom ~1000 km of Earth's lower mantle, which, they believe, contains critical clues tounderstanding mantle convection and Earth's thermo-chemical evolution over geological time.Intellectual Merit: Over the past decades global tomography has produced spectacular images of, for instance, mantle flow trajectories and structural complexity near the base of the mantle. However, uneven data coverage and heterogeneous data quality render non-unique, fuzzy images, with substantial spatial variations in reliability. Regularization and the use of inaccurate wave propagation theory probably produce incorrect estimates of elastic parameters even where sampling seems adequate, and the magnitude of wavespeed variations is usually poorly constrained. Moreover, results based on different data sets often disagree in important aspects, and correct joint interpretation of data with different sensitivities to Earth's structure (e.g., body- and surface waves, P or S waves measured at different frequencies) remains a major challenge. The approximate nature of the "red and blue" images impedes quantitative interpretation and integration with other geophysical constraints and keeps tomography from reaching its full potential as a quantitative probe of Earth's deep interior. This the PI's seek to change. For better parameter estimation they need to exploit the richness of broad-band waveforms and they need more powerful theoretical frameworks for integration and joint interpretation of diverse data sets. The ultimate objective of our approach toward multi-resolution data fusion for global tomography is to produce better 3-D models of Earth's deep interior - on a range of length scales and from a variety of seismological data - by improving (and explicitly linking) three essential aspects of imaging: Data quality and coverage: using automated procedures and multi-resolution concepts (such as time frequency wavelets) they will enhance spatial and spectral data coverage by extracting phase velocity and arrival time information from the vast number of waveforms available through international data centers. Wave propagation theory: recognizing the need to account for (and benefit from) the different sampling properties of the data considered, and inspired by recent advances in understanding finite frequency effects, they will compute accurate sensitivity kernels for the back-projection of the newly measured data. Parameterization and regularization: to preserve and exploit the localization properties of 3-D sensitivity kernels we will use adaptive multi-grid parameterization and regularization techniques for joint inversion.The research proposed here focuses on (i) measuring teleseismic P and S type body-wave travel times, (ii) inversion for 3-D variations in .lnVS/.lnVP (or related parameters) in Earth's mantle, and (iii) refining - or refuting - existing views on compositional heterogeneity in the lowermost mantle. They can build on experience in observational seismology and tomography (Van der Hilst, MIT) and wave propagation and inversion theory (De Hoop, CSM), and for the automated data processing they will collaborate with Ritsema (IPGP, France) and involve a postdoctoral associate (for which some fund matching is sought). Broader Impact: Along with mineral physics data, accurate estimates of elastic parameters are needed to constrain spatial variations in compositon and temperature and, thus, models of mantle dynamics and mineralogy. Furthermore, the concept of and tools for data fusion developed here prepare for the handling and interpretation of large data sets of USARRAY data. The proposed work constitutes the first part of a PhD project at MIT, but students at MIT and CSM will be involved in aspects of the research,either as a Undergraduate Research OPportunity (UROP) or in fulfillment of General Exam requirements.