Extracting Earth Models from Body-Wave Microseisms

从体波微震中提取地球模型

• 批准号: 0944109
• 负责人: Peter Gerstoft
• 金额: $ 31.4万
• 依托单位: University of California-San Diego Scripps Inst of Oceanography
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0944109&HistoricalAwards=false
• 关键词: Extracting; Earth; Models; Body; Wave

This project will study seismic noise and nontraditional seismic sources using advanced array signal processing algorithms that can extract information from weak signals. The work will help to characterize seismic noise sources and develop new methods to use them for resolving Earth structure. The main focus will be on P-wave microseisms from storms but the researchers will also examine non-volcanic tremor (NVT). One exciting aspect of the research is that noise analysis methods have the potential to be very useful in improving body-wave tomography for Earth structure, just as noise cross-correlation methods have recently proven successful in surface-wave tomography. A preliminary test examining teleseismic P waves recorded in southern California shows that similar arrival-time anomalies can be obtained both from direct P waves from a natural earthquake and P-wave noise generated by a large storm. In this case,the noise can be processed using waveform cross-correlation among different station pairs and optimal P relative arrival-time estimates can be computed using the same approach traditionally used to analyze earthquake arrival times. The investigators plan to experiment with taking advantage of non-traditional seismic sources(storms) to improve tomographic images by filling in the ray path coverage over certain azimuths. In addition, OBS observations may eventually provide the chance to extract absolute timing information of storm-generated P-wave microseisms, i.e., empirical Green?s functions, from ambient noise crosscorrelation.The proposed research will fundamentally advance our understanding of microseism generation and what microseisms tell us about storm activity and Earth structure. This research has the potential to track storms via a non-satellite approach, monitor intensities of storms, and contribute to inversions for deep Earth structure.

该项目将使用先进的阵列信号处理算法来研究地震噪声和非传统震源，这些算法可以从弱信号中提取信息。这项工作将有助于描述地震噪声源的特征，并开发新的方法来利用它们来解决地球结构问题。主要的焦点将是风暴引起的p波微地震，但研究人员也将研究非火山震颤（NVT）。这项研究的一个令人兴奋的方面是，噪声分析方法有可能在改善地球结构的体波断层扫描方面非常有用，就像噪声互相关方法最近在表面波断层扫描中被证明是成功的一样。对南加州记录的远震P波的初步测试表明，从自然地震产生的直接P波和大风暴产生的P波噪声中都可以获得类似的到达时间异常。在这种情况下，可以使用不同台站对之间的波形互相关来处理噪声，并且可以使用传统上用于分析地震到达时间的相同方法来计算最佳P相对到达时间估计。研究人员计划利用非传统震源（风暴）进行实验，通过填充特定方位角上的射线路径覆盖来改善层析成像图像。此外，OBS观测可能最终提供提取风暴产生的纵波微震的绝对定时信息的机会，即经验Green？S函数，从环境噪声互相关。提出的研究将从根本上推进我们对微震产生的理解，以及微震告诉我们关于风暴活动和地球结构的信息。这项研究有可能通过非卫星方法跟踪风暴，监测风暴的强度，并为地球深部结构的逆温做出贡献。