Natural earthquakes occur on faults. The relationship between fault zone structures and earthquake behaviors remains one of the most interesting problems in seismology. As an important tool to detect earthquakes and image the Earth’s interior, seismic arrays have been widely used since the 1960s. Recordings from closely spaced uniform seismometers improved imaging resolution of the Earth’s interior and enhanced detection of small-magnitude earthquakes. However, such an increase in data size also poses a challenge in the way that we used to handle and processing seismic data. Visual inspection and manual selection become less practical and sometimes impossible. My PhD research focuses on obtaining high-resolution seismic properties (e.g., seismic anisotropy and velocity contrast) along major fault zones in California and Turkey, and detecting seismic events/phases multi-scale dense seismic arrays. To process large-size seismic data, I developed several tools to automatically pick P, S and fault zone head waves. Using recently emerging ultra-dense arrays, I proposed a new metric, termed local similarity, to detect weak microseismic signals that are barely above noise level. These studies share the same feature, i.e., using automatic techniques to extract earthquake and structure information from big seismic data recorded by dense or ultra dense arrays. The results are expected to provide valuable information on fault zone structures and microseismic behaviors. The tools developed in these studies can be applied to a wide range of research topics.
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Fault zone imaging and earthquake detection with dense seismic arrays
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