3D Imaging of the Earth’s Lithosphere Using Noise from Ocean Waves
Yingjie Yang, Jun Xie and Kaifeng Zhao
ASEG Extended Abstracts
2016(1) 1 - 5
Published: 2016
Abstract
The lithosphere is the rigid outer shell of the Earth, composed of the crust and the rigid uppermost mantle. The lateral variation of lithosphere is believed to be closely related to the foci of intraplate earthquakes and volcanism, the location of large ore deposits and diamond-bearing kimberlites, and the formation of oil/gas-bearing sedimentary basins. Understanding the fine-scale structure of the lithosphere is therefore one of the most fundamental tasks in Earth sciences, and has important implications for society in terms of economic prosperity and hazard mitigation.Seismic tomography is the main technique available to image the subsurface structure of the Earth across a range of scales. Conventional seismic tomography exploits the seismic waves emitted by earthquakes. However, because most large earthquakes occur at plate boundaries and most continents, including Australia, are not seismically active, earthquake-based tomography suffers from uneven distributions of earthquakes and has difficulties in deciphering fine-scale structures of the Earth in seismically quiet continents.
In the past decade, the advent of ambient noise tomography (ANT) has revolutionized seismic tomography because it can overcome the limitations of conventional earthquake surface wave tomography. This technique uses diffuse background seismic energy, mostly comes from the interaction of ocean waves with the crust. Empirical Green’s functions of surface waves passing between a pair of stations are extracted by cross-correlating continuous time series of ambient noise. Within a regional seismic array, all inter-station measurements of surface-wave dispersion can be measured and tomography can be performed to image the underling lithospheric structure. In this study, we demonstrate the applications of broadband ANT in mapping fine-scale lithosphere structures around the world using continuous seismic data.
https://doi.org/10.1071/ASEG2016ab202
© ASEG 2016