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

合作研究：波动方程断层扫描和数据同化：估计地球下地幔 P 和 S 速度变化的新方法

• 批准号: 0630493
• 负责人: Maarten de Hoop
• 金额: $ 2.94万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-08-20 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0630493&HistoricalAwards=false
• 关键词: Collaborative; Research; Wave; Equation; Tomography

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.

首席研究员为合作研究寻求资金，旨在通过地震数据分析和解释的观测、理论和计算方面的明确整合来开发新型层析成像模型。这项工作扩展了他们之前在层析成像方面的工作，涉及新数据集的测量以及波传播理论和多重网格技术的发展，该技术允许联合解释对地球结构具有不同敏感性的数据。我们认为，这些成分的定量积分是准确绘制弹性、温度和成分空间变化的可行且重要的一步。在这里，PI 将重点关注地球下地幔底部约 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。 智力优点：过去几十年来，全球层析成像技术已经产生了令人惊叹的图像，例如地幔流动轨迹和地幔底部附近结构的复杂性。然而，不均匀的数据覆盖范围和异构的数据质量导致图像不唯一、模糊，并且可靠性存在很大的空间变化。正则化和不准确的波传播理论的使用可能会产生对弹性参数的错误估计，即使采样似乎足够，并且波速变化的幅度通常很难受到限制。此外，基于不同数据集的结果往往在重要方面存在分歧，对地球结构具有不同敏感性的数据（例如体波和表面波、在不同频率下测量的 P 波或 S 波）的正确联合解释仍然是一个重大挑战。 “红色和蓝色”图像的近似性质阻碍了定量解释以及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。 PI 寻求改变这一点。为了更好地估计参数，他们需要利用宽带波形的丰富性，并且需要更强大的理论框架来集成和联合解释不同的数据集。我们针对全球层析成像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）三个模型，在一系列长度尺度上并根据各种地震数据，生成更好的地球深层内部 3D 模型。成像的基本方面： 数据质量和覆盖范围：使用自动化程序和多分辨率概念（例如时频小波），他们将通过从国际上可用的大量波形中提取相速度和到达时间信息来增强空间和频谱数据覆盖范围。数据中心。波传播理论：认识到需要考虑（并从中受益）所考虑数据的不同采样属性，并受到理解有限频率效应的最新进展的启发，他们将为新测量的反投影计算准确的灵敏度内核数据。参数化和正则化：为了保留和利用 3-D 灵敏度核的定位特性，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。这里提出的研究重点是（i）测量远震 P 和 S 型体波旅行时间，(ii) 反演地幔中 .lnVS/.lnVP（或相关参数）的 3-D 变化，以及 (iii) 完善或反驳关于地幔中成分异质性的现有观点最底层的地幔。他们可以利用观测地震学和层析成像（Van der Hilst，MIT）以及波传播和反演理论（De Hoop，CSM）方面的经验，并且在自动化数据处理方面，他们将与 Ritsema（IPGP，法国）合作并聘请博士后合伙人（为此寻求一些资金匹配）。更广泛的影响：除了矿物物理数据之外，还需要精确估计弹性参数来限制成分和温度的空间变化，从而限制地幔动力学和矿物学模型。此外，这里开发的数据融合的概念和工具为处理和解释 USARRAY 数据的大型数据集做好了准备。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，无论是作为本科生研究机会 (UROP) 还是满足普通考试要求。