A demonstration of the joint use of P wave polarization and travel-time data in tomographic inversion: Crustal velocity structure near the South Iceland Lowland Network

1993 ◽  
Vol 20 (13) ◽  
pp. 1407-1410 ◽  
Author(s):  
Ge Hu ◽  
William Menke ◽  
Sigurdur Rognvaldsson
Keyword(s):  
Travel Time ◽  
Velocity Structure ◽  
P Wave ◽  
Wave Polarization ◽  
The South ◽  
Time Data ◽  
Tomographic Inversion ◽  
Crustal Velocity ◽  
Crustal Velocity Structure ◽  
Travel Time Data

scholarly journals Probabilistic neural network-based 2D travel-time tomography

2020 ◽  
Vol 32 (22) ◽  
pp. 17077-17095 ◽  
Author(s):  
Stephanie Earp ◽  
Andrew Curtis
Keyword(s):  
Travel Time ◽  
Prior Information ◽  
Velocity Structure ◽  
Probability Density Functions ◽  
High Dimensional ◽  
Density Functions ◽  
Time Data ◽  
Informative Prior ◽  
Travel Time Data ◽  
Highly Nonlinear

Abstract Travel-time tomography for the velocity structure of a medium is a highly nonlinear and nonunique inverse problem. Monte Carlo methods are becoming increasingly common choices to provide probabilistic solutions to tomographic problems but those methods are computationally expensive. Neural networks can often be used to solve highly nonlinear problems at a much lower computational cost when multiple inversions are needed from similar data types. We present the first method to perform fully nonlinear, rapid and probabilistic Bayesian inversion of travel-time data for 2D velocity maps using a mixture density network. We compare multiple methods to estimate probability density functions that represent the tomographic solution, using different sets of prior information and different training methodologies. We demonstrate the importance of prior information in such high-dimensional inverse problems due to the curse of dimensionality: unrealistically informative prior probability distributions may result in better estimates of the mean velocity structure; however, the uncertainties represented in the posterior probability density functions then contain less information than is obtained when using a less informative prior. This is illustrated by the emergence of uncertainty loops in posterior standard deviation maps when inverting travel-time data using a less informative prior, which are not observed when using networks trained on prior information that includes (unrealistic) a priori smoothness constraints in the velocity models. We show that after an expensive program of network training, repeated high-dimensional, probabilistic tomography is possible on timescales of the order of a second on a standard desktop computer.

scholarly journals Insights from the P Wave Travel Time Tomography in the Upper Mantle Beneath the Central Philippines

2021 ◽  
Vol 13 (13) ◽  
pp. 2449
Author(s):  
Huiyan Shi ◽  
Tonglin Li ◽  
Rui Sun ◽  
Gongbo Zhang ◽  
Rongzhe Zhang ◽  
...  
Keyword(s):  
Travel Time ◽  
Upper Mantle ◽  
High Velocity ◽  
Velocity Structure ◽  
The Philippines ◽  
P Wave ◽  
The South ◽  
Teleseismic Tomography ◽  
The North ◽  
Velocity Anomalies

In this paper, we present a high resolution 3-D tomographic model of the upper mantle obtained from a large number of teleseismic travel time data from the ISC in the central Philippines. There are 2921 teleseismic events and 32,224 useful relative travel time residuals picked to compute the velocity structure in the upper mantle, which was recorded by 87 receivers and satisfied the requirements of teleseismic tomography. Crustal correction was conducted to these data before inversion. The fast-marching method (FMM) and a subspace method were adopted in the forward step and inversion step, respectively. The present tomographic model clearly images steeply subducting high velocity anomalies along the Manila trench in the South China Sea (SCS), which reveals a gradual changing of the subduction angle and a gradual shallowing of the subduction depth from the north to the south. It is speculated that the change in its subduction depth and angle indicates the cessation of the SCS spreading from the north to the south, which also implies that the northern part of the SCS opened earlier than the southern part. Subduction of the Philippine Sea (PS) plate is exhibited between 14° N and 9° N, with its subduction direction changing from westward to eastward near 13° N. In the range of 11° N–9° N, the subduction of the Sulu Sea (SS) lies on the west side of PS plate. It is notable that obvious high velocity anomalies are imaged in the mantle transition zone (MTZ) between 14° N and 9° N, which are identified as the proto-SCS (PSCS) slabs and paleo-Pacific (PP) plate. It extends the location of the paleo-suture of PSCS-PP eastward from Borneo to the Philippines, which should be considered in studying the mechanism of the SCS and the tectonic evolution in SE Asia.

Crustal velocity structure of the Northwest Sub-basin of the South China Sea based on seismic data reprocessing

2020 ◽  
Vol 63 (11) ◽  
pp. 1791-1806
Author(s):  
Qiang Wang ◽  
Minghui Zhao ◽  
Haoyu Zhang ◽  
Jiazheng Zhang ◽  
Enyuan He ◽  
...  
Keyword(s):  
South China Sea ◽  
South China ◽  
Seismic Data ◽  
Velocity Structure ◽  
The South China Sea ◽  
The South ◽  
China Sea ◽  
Crustal Velocity ◽  
Crustal Velocity Structure

scholarly journals Three dimensional velocity structure and relocated aftershocks for the 1985 Constantine, Algeria (MS = 5.9) earthquake

1998 ◽  
Vol 41 (1) ◽  
Author(s):  
M. ou A. Bounif ◽  
C. Dorbath
Keyword(s):  
Velocity Structure ◽  
Three Dimensional ◽  
Velocity Model ◽  
P Wave ◽  
Time Data ◽  
Data Set ◽  
S Waves ◽  
Travel Time Data ◽  
Velocity Image ◽  
Local Earthquake

Local earthquake travel-time data were inverted to obtain a three dimensional tomographic image of the region centered on the 1985 Constantine earthquake. The resulting velocity model was then used to relocate the events. The tomographic data set consisted of P and S waves travel-times from 653 carefully selected aftershocks of this moderate size earthquake, recorded at 10 temporary stations. A three-dimensional P-wave velocity image to a depth of 12 km was obtained by Thurber's method. At shallower depth, the velocity contrasts reflected the differences in tectonic units. Velocities lower than 4 km/s corresponded to recent deposits, velocities higher than 5 km/s to the Constantine Neritic and the Tellian nappes. The relocation of the aftershocks indicates that most of the seismicity occured where the velocity exceeded 5.5 km/s. The aftershock distribution accurately defined the three segments involved in the main shock and led to a better understanding of the rupture process.

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