Title:
Fault zone imaging and earthquake detection with dense seismic arrays

dc.contributor.advisor Peng, Zhigang
dc.contributor.author Li, Zefeng
dc.contributor.committeeMember Newman, Andrew
dc.contributor.committeeMember Dufek, Josef
dc.contributor.committeeMember Ferrier, Ken
dc.contributor.committeeMember McClellan, James
dc.contributor.department Earth and Atmospheric Sciences
dc.date.accessioned 2018-08-20T15:30:21Z
dc.date.available 2018-08-20T15:30:21Z
dc.date.created 2017-08
dc.date.issued 2017-07-13
dc.date.submitted August 2017
dc.date.updated 2018-08-20T15:30:21Z
dc.description.abstract 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.
dc.description.degree Ph.D.
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/60154
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Seismology
dc.subject Earthquakes
dc.subject Fault zone
dc.subject Earthquake detection
dc.subject Seismic array
dc.title Fault zone imaging and earthquake detection with dense seismic arrays
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Peng, Zhigang
local.contributor.corporatename School of Earth and Atmospheric Sciences
local.contributor.corporatename College of Sciences
relation.isAdvisorOfPublication 7220160b-4bb7-4e32-8ef2-c985b71df08b
relation.isOrgUnitOfPublication b3e45057-a6e8-4c24-aaaa-fb00c911603e
relation.isOrgUnitOfPublication 85042be6-2d68-4e07-b384-e1f908fae48a
thesis.degree.level Doctoral
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
LI-DISSERTATION-2017.pdf
Size:
29.45 MB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
LICENSE.txt
Size:
3.86 KB
Format:
Plain Text
Description: