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Titel |
Wave-equation-based travel-time seismic tomography – Part 1: Method |
VerfasserIn |
P. Tong, D. Zhao, D. Yang, X. Yang, J. Chen, Q. Liu |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1869-9510
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Digitales Dokument |
URL |
Erschienen |
In: Solid Earth ; 5, no. 2 ; Nr. 5, no. 2 (2014-11-26), S.1151-1168 |
Datensatznummer |
250115350
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Publikation (Nr.) |
copernicus.org/se-5-1151-2014.pdf |
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Zusammenfassung |
In this paper, we propose a wave-equation-based travel-time seismic
tomography method with a detailed description of its step-by-step process.
First, a linear relationship between the travel-time residual Δt = Tobs–Tsyn and the relative velocity perturbation
δ c(x)/c(x) connected by a finite-frequency travel-time
sensitivity kernel K(x) is theoretically derived using the adjoint
method. To accurately calculate the travel-time residual Δt, two
automatic arrival-time picking techniques including the envelop energy ratio
method and the combined ray and cross-correlation method are then developed
to compute the arrival times Tsyn for synthetic seismograms. The
arrival times Tobs of observed seismograms are usually determined
by manual hand picking in real applications. Travel-time sensitivity kernel
K(x) is constructed by convolving a~forward wavefield u(t,x)
with an adjoint wavefield q(t,x). The calculations of synthetic
seismograms and sensitivity kernels rely on forward modeling. To make it
computationally feasible for tomographic problems involving a large number of
seismic records, the forward problem is solved in the two-dimensional (2-D)
vertical plane passing through the source and the receiver by a high-order
central difference method. The final model is parameterized on 3-D regular
grid (inversion) nodes with variable spacings, while model values on each 2-D
forward modeling node are linearly interpolated by the values at its eight
surrounding 3-D inversion grid nodes. Finally, the tomographic inverse
problem is formulated as a regularized optimization problem, which can be
iteratively solved by either the LSQR solver or a~nonlinear
conjugate-gradient method. To provide some insights into future 3-D
tomographic inversions, Fréchet kernels for different seismic phases are
also demonstrated in this study. |
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