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用压缩感知方法研究大地震的破裂过程——方法与研究进展

Compressive sensing of great earthquake rupture process: Methodology and research advances

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【作者】 姚华建

【Author】 YAO Huajian;Laboratory of Seismology and Physics of Earth’s Interior,School of Earth and Space Sciences, University of Science and Technology of China;Mengcheng National Geophysical Observatory;

【机构】 中国科学技术大学地球和空间科学学院地震与地球内部物理实验室蒙城地球物理国家野外科学观测研究站

【摘要】 通过观测方法来研究大地震的破裂过程是认识地震破裂物理规律最重要的手段之一.本文较为详细地介绍了基于稀疏反演理论的压缩感知方法及其在研究大地震破裂过程中不同频率能量释放的时空分布中的应用,着重介绍了采用压缩感知算法所获得的俯冲带特大逆冲型地震与频率及深度相关的能量释放过程,并讨论了该过程与随深度变化的同震断层滑移量和早期余震分布之间的关系.这为认识俯冲板块表面随深度变化的摩擦性质和俯冲带大地震的破裂规律提供了重要的观测结果.最后本文讨论了通过观测手段研究大地震破裂过程的现状和未来,并展望了压缩感知算法在研究地震破裂能量释放及其他地震学和地球物理学领域中的应用.

【Abstract】 The use of observational methods to investigate great earthquake rupture processes has been one of the most important tools to study earthquake rupture physics.This review article gave a fairly detailed description about the compressive sensing technique,a method based on sparse inverse theory,and its application in studying the spatial and temporal distribution of seismic radiation at different frequencies during great earthquake ruptures.In particular,the main results about the frequency-and depth-dependent seismic radiation during rupture processes of subduction zone megathrust earthquakes that were revealed by the compressive sensing technique were reviewed as well as its correlation with depth-dependent co- seismic slip and early aftershocks distribution.These may provide important observational results for understanding the frictional properties of the subducting slab interface and rupture mechanisms of subduction zone great earthquakes.Finally,the current status and future directions on studying earthquake rupture process using observational methods were discussed.Some perspective researches about the use of the compressive sensing technique for studying seismic radiation during earthquake ruptures were also discussed as well as its application in some other fields in seismology and geophysics.

【基金】 国家自然科学基金(41374055);中国科学院创新团队项目资助
  • 【文献出处】 中国科学技术大学学报 ,Journal of University of Science and Technology of China , 编辑部邮箱 ,2013年11期
  • 【分类号】P315.61
  • 【被引频次】3
  • 【下载频次】163
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