journal article·2023-01-19Open access

Calculation of Theoretical Travel Time and Automatic Picking of Actual Travel Time in Seismic Data

Wenqi Gao, Youxue Wang, Yang Yang, Sanxi Peng, Songping Yu, Lu Liu, Lei Yan

Applied Sciences· Volume 13· Issue 3

Abstract

We used the ray tracing technique based on the IASP91 Earth model to calculate the travel times in order to identify the phases. This technique can calculate the travel times for the seismic phases in the conventional travel time tables. The waveform data received from the stations in the Guangxi area are selected for analysis and discussion. The outcomes of the numerical modeling and its use demonstrate that there is good agreement in terms of the absolute differences between the calculated and theoretical travel times from the ISAP91 tables. The relative residuals are determined directly from the actual arrival times picking during the correlation analysis, and the validity of the travel time method for picking seismic phases by correlation analysis can be demonstrated.
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Research context

OpenAlex topics: Seismology and Earthquake Studies · Seismic Imaging and Inversion Techniques · earthquake and tectonic studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of Earth Sciences, Guilin University of Technology, Guilin 541004, China

Funding

National Natural Science Foundation of China · Innovation Program for College Graduates of Guangxi · Natural Science Foundation of Guangxi

References (31)

Show source-provided references
1. Development of Automatic Earthquake Quick Report in China
2. Jeffreys, H., and Bullen, K.E. (1940). Seismology Tables, British Association of Seismological Investigations.
3. Preliminary reference Earth model10.1016/0031-9201(81)90046-7 ↗
4. Travel times for global earthquake location and phase association10.1111/j.1365-246X.1991.tb06724.x ↗
5. Global teleseismic earthquake relocation with improved travel times and procedures for depth determination10.1785/BSSA0880030722 ↗
6. Crust and upper mantle P wave velocity structure beneath Valles caldera, New Mexico: Results from the Jemez teleseismic tomography experiment10.1029/98JB00750 ↗
7. Fast kinematic ray tracing of first-and later-arriving global seismic phases10.1046/j.1365-246x.1999.00950.x ↗
8. 3D shear-wave velocity structure of the Eifel plume, Germany10.1016/S0012-821X(02)00861-0 ↗
9. Seismic ray path variations in a 3D global velocity model10.1016/j.pepi.2003.11.010 ↗
10. Wang, J.Y. (2002). Inverse Theory in Geophysics, Higher Education Press. [2nd ed.].
11. 2-D/3-D irregular shortest-path ray tracing for multiple arrivals and its applications10.1111/j.1365-246X.2010.04817.x ↗
12. Fast and accurate global multiphase arrival tracking: The irregular shortest-path method in a 3-D spherical earth model10.1093/gji/ggt204 ↗
13. Seismic tomography of the Seismic tomography of the crust and upper mantle structure underneath the Chinese Tianshan10.1002/cjg2.982 ↗
14. Tomographic imaging of P and S wave velocity structure beneath northeastern Japan10.1029/92JB00603 ↗
15. Deep structure of Japan subduction zone as derived from local, regional, and teleseismic events10.1029/94JB01149 ↗
16. High-resolution mantle tomography of China and surrounding regions10.1029/2005JB004066 ↗
17. Robust automatic P-phase picking: An on-line implementation in the analysis of broadband seismogram recordings10.1016/S0031-9201(99)00007-2 ↗
18. Automatic onset phase picking for portable seismic array observation
19. Multi-channel estimation of time residuals from broadband seismic data using multi-wavelets10.1785/BSSA0890030681 ↗
20. Optimal measurement of relative and absolute delay times by simulated annealing10.1046/j.1365-246X.2002.01755.x ↗
21. Automatic earthquake recognition and timing from single traces10.1785/BSSA0680051521 ↗
22. Microseismic event detection in noisy environments with instantaneous spectral Shannon entropy10.1103/PhysRevE.106.014133 ↗
23. Wu, H., Xiao, W., and Ren, H. (2022). Automatic Time Picking for Weak Seismic Phase in the Strong Noise and Interference Environment: An Hybrid Method Based on Array Similarity. Sensors, 22.10.3390/s22249924 ↗
24. Deep learning, machine learning and internet of things in geophysical engineering applications: An overview10.1016/j.micpro.2020.103613 ↗
25. Deep learning for picking seismic arrival times10.1029/2019JB017536 ↗
26. Machine learning and geophysical inversion—A numerical study10.1190/tle38070512.1 ↗
27. First-break timing: Arrival onset times by direct correlation10.1190/1.1444653 ↗
28. Determination of teleseismic relative phase arrival times using multi-channel cross-correlation and least squares
29. Rapid estimation of relative and absolute delay times across a network by adaptive stacking10.1111/j.1365-246X.2004.02188.x ↗
30. Numerical modeling of global seismic phases and its application in seismic phase identification10.29382/eqs-2019-0072-04 ↗
31. A new approach in non-linear mechanics: The large time increment method10.1002/nme.1620290312 ↗