Selection of deep, energetically weak waves in seismic DSS records


  • D.M. Gryn’ Subbotin Institute of Geophysics, National Academy of Sciences of Ukraine, Ukraine



deep seismic sounding, wave fields, hodograph, target reflections, waves, noise, difference operators


To solve direct problems of seismic, namely, to construct velocity DSS models we need to have a maximal number of hodographs of reflected waves from geological borders. The strongest reflections occur at a short distance from the explosion point. The more is the distance, the smaller the amplitude of vibrations of seismic reflected waves and more difficult their selection from the wave field. The object of the paper is a proposal of the ways for increasing information value of DSS data by selection of small amplitude reflected waves and their hodographs from the borders which occur at deep depths. The basis of the method is a difference method of spatial selection of hodographs of the target waves by the calculated or arbitrarily chosen direction. As a result the initial wave field is subdivided into the field with noise-waves of different origin and the wave field of efficient signals.

Working capacity of the method is demonstrated on the model temporal seismic sections obtained with the help of the program of integral-wave modeling Tesseral 2D. As a field material the data of deep seismic sounding (DSS) were used, obtained during a fulfillment of the marine part of DOBRE-2 project. For the Black Sea the hodographs of the waves reflected from the basement were selected overlapped by various noise-waves from the upper part of the seismic section. For the Sea of Azov an area was processed situated at the distance of 130-150 km from the source of seismic vibrations. Attenuated wave reflected from the Moho border up to the depth of 45 km was hidden by the noise-waves, and so for selection of the target reflected wave calculated direction of the hodograph was used. 

Application of the proposed method allows an increase of the amount of hodographs applied for construction of velocity models that in its turn increases the significance of solving direct and inverse problems.


Dyadyura, V.A., & Sokolovskiy, O.I. (1984). Separation of interfering regular waves. Moscow, 68 p. (in Russian).

Horn, R., & Johnson, C. (1989). Matrix Analysis. Moscow: Mir, 656 p. (in Russian).

Albert, D.G., & Decato, S.N. (2017) Acoustic and seismic ambient noise measurements in urban and rural areas. Applied Acoustics, 119, 135—143.

Amundsen, L., Ikelle, L. & Martin, J. (2000). Multiple attenuation and P/S splitting of multicomponent OBC data at a heterogeneous sea floor. Wave Motion, 32(1), 67—78.

Bormann, P., & Wielandt, E. (2013). Seismic signals and noise. In: P. Bormann (Ed.), New Manual of Seismological Observatory Practice 2 (NMSOP2) (pp. 1—62). Potsdam.

Green, D.N., Bastow, I.D., Dashwood, B, Nippress, S.E.J. (2017). Characterizing Broadband Seismic Noise in Central London. Seismological Research Letters, 88(1), 113—124. doi: 10.1785/0220160128.

Harlan, W.S., Claerbout, J.F., & Rocca, F. (1984). Signal/noise separation and velocity estimation. Geophysics, 49(11), 1869—1880.

Hendrick, N. (2006). Multi-component seismic wave field separation via spectral matrix filtering. ASEG Extended Abstracts, 1, 1—4. doi: 10.1071/ASEG2006ab065.

Poppeliers, C., & Mallinson, D. (2015). High-frequency seismic noise generated from breaking shallow water ocean waves and the link to time-variable sea states. Geophysical Research Letters, 42(20), 8563—8569.

Schwarz, B. (2019). An introduction to seismic diffraction. Advances in Geophysics, 60, 1—64. doi: 10.1016/bs.agph.2019.05.001.

Schwarz, B., & Gajewski, D. (2017). Accessing the diffracted wavefield by coherent subtraction. Geophysical Journal International, 211(1), 45—49.

Sollberger, D., Greenhalgh, S.A., Schmelzbach, C., Van Renterghem, C., Robertsson, J.O.A. (2018). 6-C polarization analysis using point measurements of translational and rotational ground-motion: theory and applications. Geophysical Journal International, 213(1), 77—97.

Starostenko, V., Janik, T., Stephenson, R., Gryn, D., Rusakov, O., Czuba, W., Środa, P., Lysynchuk, D., Grad, M., Guterch, A., Fluh, E., Thybo, H., Artemieva, I., Tolkunov, A., Sydorenko, G., Omelchenko, V., Kolomiyets, K., Legostaeva, O., Dannowski, A., & Shulgin, A. (2016). DOBRE-2 WARR profile: the Earth’s crust across Crimea between the pre-Azov Massif and the northeastern Black Sea Basin. In M. Sosson, R.A. Stephenson & S.A. Adamia (Eds.), Tectonic Evolution of the Eastern Black Sea and Caucasus (pp. 199—220). Geol. Soc., London, Spec. Publ., 428.

Van Renterghem, C., Schmelzbach, C., Sollberger, D., & Robertsson, J.O.A. (2018). Spatial wavefield gradient-based seismic wavefield separation. Geophysical Journal International, 212(3), 1588—1599.

Wang, Y., Singh, S.C., & Barton, P.J. (2002). Separation of P- and SV-wavefields from multi-component seismic data in the τ-p domain. Geophysical Journal International, 151(2), 663—672.

Wang, C., Wang, Y., Sun, P., & Li, Y. (2019). Discussions on the Processing of the Multi-Component Seismic Vector Field. Applied Sciences, 9(9), 1770. doi: 10.3390/app9091770.

Wapenaar, C. & Haim.e, G. (1990). Elastic extrapolation of primary seismic P- and S-waves. Geophysical Prospecting, 38(1) 23—60.

Zhou, B., Hatherly, P., & Sun, W. (2017). Enhancing the detection of small coal structures by seismic diffraction imaging. International Journal of Coal Geology, 178, 1—12.



How to Cite

Gryn’, D. (2020). Selection of deep, energetically weak waves in seismic DSS records. Geofizicheskiy Zhurnal, 42(1), 96–109.