Neural network modeling of Herglotz—Wiechert inversion of multiparametric travel-time curves of seismic waves

Authors

  • M. Lazarenko S.I. Subbotin Institute of Geophysics, National Academy of Sciences of Ukraine, Ukraine
  • O. Herasymenko S.I. Subbotin Institute of Geophysics, National Academy of Sciences of Ukraine, Ukraine

DOI:

https://doi.org/10.24028/gzh.0203-3100.v39i4.2017.107503

Keywords:

neural network, seismic waves propagation, training, the Herglots—Wiechert inversion, discrepancies, travel-time curves, velocity gradient

Abstract

Using artificial neural networks to solve a problem of plotting travel-time curves of seismic waves can create nonlinear travel-time model of P and S phases of seismic waves arrangement as a function of several arguments: source depth, magnitude, back azimuth and epicenter distance. Construction of three-dimensional travel-time relationships and their use for modeling of hadographs and their inversion are considered on examples of seismic records Ukrainian seismic stations. Examples of inversion locus within the model Herglotz—Wiechert and features of application of the model in a real environment for single seismic stations, and generalization for arbitrary coordinate of the source and the point of signal registration in the Black Sea region are given.

References

Gobarenko V. S., Yanovskaya T. B., 2011. Velocity structure of the upper levels of the Black Sea mantle. Geofizicheskiy zhurnal 33(3), 62—74 (in Russian).

Lazarenko M. A., Gerasimenko O. A., 2010. Neural network modeling of the travel time curves of seismic waves. Geofizicheskiy zhurnal 32(5), 62—74 (in Russian).

Lithosphere of Central and Eastern Europe: Young platforms and the Alpine folded belt, 1994. Ed. A. V. Chekunov. Kiev: Naukova Dumka, 331 p. (in Russian).

Poklad G. G., 1988. Geodesy: Proc. For high schools .Moscow: Nedra, 304 p. (in Russian).

Khaykin S., 2008. Neural networks: a full course. Moscow: Williams, 1103 p. (in Russian).

Chauvin Y., Rumelhart D. E., 1995. Back Propagation: Theory, Architectures, and Applications. Lawrence Erlbaum Associates, 564 р.

Lay T., Wallace T. C., 1995. Modern Global Seismology. San Diego: Academic. Press, 521 p.

Sjцberg L., Shirazian M., 2012. Solving the Direct and lnverse Geodetic Problems on the Ellipsoit by Numerical Integration. J. Surv. Eng. 138(1), 9––16. https://doi.org/10.1061/(ASCE)SU.1943-5428.0000061#sthash.qIIieVw6.dpuf.

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Published

2017-07-25

How to Cite

Lazarenko, M., & Herasymenko, O. (2017). Neural network modeling of Herglotz—Wiechert inversion of multiparametric travel-time curves of seismic waves. Geofizicheskiy Zhurnal, 39(4), 3–14. https://doi.org/10.24028/gzh.0203-3100.v39i4.2017.107503

Issue

Vol. 39 No. 4 (2017)

Section

Articles

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