Articles | Volume 14, issue 2
https://doi.org/10.5194/se-14-181-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-14-181-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Ocean bottom seismometer (OBS) noise reduction from horizontal and vertical components using harmonic–percussive separation algorithms
Institute of Geosciences, University of Potsdam, Karl-Liebknecht-Str.
24–25, 14476 Potsdam, Germany
GFZ German Research Centre for Geosciences, Potsdam, Germany
Theresa Rein
Institute of Geosciences, University of Potsdam, Karl-Liebknecht-Str.
24–25, 14476 Potsdam, Germany
Frank Krüger
Institute of Geosciences, University of Potsdam, Karl-Liebknecht-Str.
24–25, 14476 Potsdam, Germany
Matthias Ohrnberger
Institute of Geosciences, University of Potsdam, Karl-Liebknecht-Str.
24–25, 14476 Potsdam, Germany
Frank Scherbaum
Institute of Geosciences, University of Potsdam, Karl-Liebknecht-Str.
24–25, 14476 Potsdam, Germany
Related authors
No articles found.
Nele Inken Käte Vesely, Eva Patrica Silke Eibl, Gilda Currenti, Mariangela Sciotto, Giuseppe Di Grazia, Matthias Ohrnberger, and Philippe Jousset
EGUsphere, https://doi.org/10.5194/egusphere-2025-4412, https://doi.org/10.5194/egusphere-2025-4412, 2025
This preprint is open for discussion and under review for Solid Earth (SE).
Short summary
Short summary
We compare seismometers with the 6C method, which combines rotational and seismometer data, determining signal directions and wave velocities for short and continuous low-frequency volcanic signals at Mt. Etna. Either the cluster or the rotational sensor reliably detect continuous signal directions, aligning with the observatory data. For short signals, 6C directions deviate more, likely due to a complex underground. Combining both methods' velocity results improves understanding volcanic waves.
Maria R. P. Sudibyo, Eva P. S. Eibl, Sebastian Hainzl, and Matthias Ohrnberger
Nat. Hazards Earth Syst. Sci., 24, 4075–4089, https://doi.org/10.5194/nhess-24-4075-2024, https://doi.org/10.5194/nhess-24-4075-2024, 2024
Short summary
Short summary
We assessed the performance of permutation entropy (PE), phase permutation entropy (PPE), and instantaneous frequency (IF), which are estimated from a single seismic station, to detect changes before, during, and after the 2014–2015 Holuhraun eruption in Iceland. We show that these three parameters are sensitive to the pre-eruptive and eruptive processes. Finally, we discuss their potential and limitations in eruption monitoring.
Tomáš Fischer, Pavla Hrubcová, Torsten Dahm, Heiko Woith, Tomáš Vylita, Matthias Ohrnberger, Josef Vlček, Josef Horálek, Petr Dědeček, Martin Zimmer, Martin P. Lipus, Simona Pierdominici, Jens Kallmeyer, Frank Krüger, Katrin Hannemann, Michael Korn, Horst Kämpf, Thomas Reinsch, Jakub Klicpera, Daniel Vollmer, and Kyriaki Daskalopoulou
Sci. Dril., 31, 31–49, https://doi.org/10.5194/sd-31-31-2022, https://doi.org/10.5194/sd-31-31-2022, 2022
Short summary
Short summary
The newly established geodynamic laboratory aims to develop modern, comprehensive, multiparameter observations at depth for studying earthquake swarms, crustal fluid flow, mantle-derived fluid degassing and processes of the deep biosphere. It is located in the West Bohemia–Vogtland (western Eger Rift) geodynamic region and comprises a set of five shallow boreholes with high-frequency 3-D seismic arrays as well as continuous real-time fluid monitoring at depth and the study of the deep biosphere.
Cited articles
Ammon, C. J., Randall, G. E., and Zandt, G.: On the nonuniqueness of
receiver function inversions, J. Geophys. Res.-Sol. Ea., 95,
15303–15318, https://doi.org/10.1029/JB095iB10p15303, 1990.
An, C., Cai, C., Zhou, L., and Yang, T.: Characteristics of Low-Frequency
Horizontal Noise of Ocean-Bottom Seismic Data, Seismol. Res. Lett., 93, 257–267.
https://doi.org/10.1785/0220200349, 2021.
Bell, S. W., Forsyth, D. W., and Ruan, Y.: Removing noise from the vertical
component records of ocean-bottom seismometers: Results from year one of the
Cascadia Initiative, B. Seismol. Soc. Am., 105, 300–313,
https://doi.org/10.1785/0120140054, 2015.
Beyreuther, M., Barsch, R., Krischer, L., Megies, T., Behr, Y., and Wassermann,
J.: ObsPy: A Python Toolbox for Seismology. Seismol. Res. Lett., 81,
530–533, 2010.
Brink, K. H.: Tidal and lower frequency currents above Fieberling Guyot, J.
Geophys. Res.-Oceans, 100, 10817–10832,
https://doi.org/10.1029/95JC00998, 1995.
Corela, C.: Ocean bottom seismic noise: applications for the crust
knowledge, interaction ocean-atmosphere and instrumental behaviour, PhD
thesis, University of Lisbon, 339 pp., http://hdl.handle.net/10451/15805, 2014.
Crawford, W. C.: Determination of oceanic crustal shear velocity structure
from seafloor compliance measurements, Doctoral dissertation, University of
California, San Diego, https://www.ipgp.fr/~crawford/Homepage/Publis/Crawford1994_Thesis.pdf (last access: July 2002), 1994.
Crawford, W. C. and Webb, S. C.: Identifying and removing tilt noise from
low-frequency (< 0.1 Hz) seafloor vertical seismic data, B. Seismol.
Soc. Am., 90, 952–963, https://doi.org/10.1785/0119990121, 2000.
Crawford, W. C., Webb, S. C., and Hildebrand, J. A.: Estimating shear
velocities in the oceanic crust from compliance measurements by
two-dimensional finite difference modeling, J. Geophys. Res.-Sol. Ea.,
103, 9895–9916, https://doi.org/10.1029/97JB03532, 1998.
Deuss, A.: Global observations of mantle discontinuities using SS and PP
precursors, Surv. Geophys., 30, 301–326,
https://doi.org/10.1007/s10712-009-9078-y, 2009.
Driedger, J., Müller, M., and Disch, S.: Extending
Harmonic-Percussive Separation of Audio Signals, in: ISMIR, 611–616, https://doi.org/10.5281/zenodo.1415226,
2014.
Duennebier, F. K. and Sutton, G. H.: Fidelity of ocean bottom seismic
observations, Oceanographic Literature Review, 10, 996,
https://doi.org/10.1007/BF01204343, 1995.
Dziewonski, A., Bloch, S., and Landisman, M.: A technique for the analysis of
transient seismic signals, B. Seismol. Soc. Am., 59, 427–444,
https://doi.org/10.1785/BSSA0590010427, 1969.
Essing, D., Schlindwein, V., Schmidt-Aursch, M. C., Hadziioannou, C., and
Stähler, S. C.: Characteristics of Current-Induced Harmonic Tremor
Signals in Ocean-Bottom Seismometer Records, Seismol. Res. Lett., 92,
3100–3112, https://doi.org/10.1785/0220200397, 2021.
Eulenfeld, T.: rf: Receiver function calculation in seismology, J.
Open Source Softw., 5, 1808, https://doi.org/10.21105/joss.01808,
2020.
Fitzgerald, D.: Harmonic/percussive separation using median filtering,
in: Proceedings of the International Conference on Digital Audio Effects
(DAFx), Vol. 13, https://doi.org/10.1049/ic.2012.0225, 2010.
FitzGerald, D.: Vocal separation using nearest neighbours and median
filtering, 23rd IET Irish Signals and Systems Conference, Maynooth, 28–29 June 2012, https://doi.org/10.1049/ic.2012.0225, 2012.
Friedrich, A., Krüger, F., and Klinge, K.: Ocean-generated microseismic
noise located with the Gräfenberg array, J. Seismol., 2, 47–64,
https://doi.org/10.1023/A:1009788904007, 1998.
Hannemann, K., Krüger, F., Dahm, T., and Lange, D.: Oceanic lithospheric S wave velocities from the analysis of P wave polarization at the ocean floor, Geophys. J. Int., 207, 1796–1817, https://doi.org/10.1093/gji/ggw342, 2016.
Hannemann, K., Krüger, F., Dahm, T., and Lange, D.: Structure of the
oceanic lithosphere and upper mantle north of the Gloria fault in the
eastern mid-Atlantic by receiver function analysis, J. Geophys. Res.-Sol. Ea.,
122, 7927–7950, https://doi.org/10.1002/2016JB013582, 2017.
Hasselmann, K.: A statistical analysis of the generation of
microseisms, Rev. Geophys., 1, 177–210,
https://doi.org/10.1029/RG001i002p00177, 1963.
Heimann, S., Kriegerowski, M., Isken, M., Cesca, S., Daout, S., Grigoli, F.,
Juretzek, C., Megies, T., Nooshiri, N., Steinberg, A., Sudhaus, H.,
Vasyura-Bathke, H., Willey, T., and Dahm, T.: Pyrocko – An open-source
seismology toolbox and library, V. 0.3, GFZ Data Services [data set],
https://doi.org/10.5880/GFZ.2.1.2017.001, 2017.
Herrmann, R. B.: Computer programs in seismology: An evolving tool for
instruction and research, Seismol. Res. Lett., 84, 1081–1088,
https://doi.org/10.1785/0220110096, 2013.
Janiszewski, H. A., Gaherty, J. B., Abers, G. A., Gao, H., and Eilon, Z.
C.: Amphibious surface-wave phase-velocity measurements of the Cascadia
subduction zone, Geophys. J. Int., 217, 1929–1948,
https://doi.org/10.1093/gji/ggz051, 2019.
Johnson, J. B., and Watson, L. M.: Monitoring volcanic craters with
infrasound “music”, Eos, 100, https://doi.org/10.1029/2019EO123979, 2019.
Kennett, B. L., Engdahl, E. R., and Buland, R.: Constraints on seismic
velocities in the Earth from traveltimes, Geophys. J. Int., 122, 108–124,
https://doi.org/10.1111/j.1365-246X.1995.tb03540.x, 1995.
Kind, R., Kosarev, G. L., and Petersen, N. V.: Receiver functions at the
stations of the German Regional Seismic Network (GRSN), Geophys. J. Int.,
121, 191–202, https://doi.org/10.1111/j.1365-246X.1995.tb03520.x, 1995.
Langston, C. A.: Structure under Mount Rainier, Washington, inferred from
teleseismic body waves, J. Geophys. Res., 84,
4749–4762, https://doi.org/10.1029/JB084iB09p04749, 1979.
Ligorría, J. P. and Ammon, C. J.: Iterative deconvolution and
receiver-function estimation, B. Seismol. Soc. Am., 89, 1395–1400,
https://doi.org/10.1785/BSSA0890051395, 1999.
McFee, B., McVicar, M., Faronbi, D., et al.: librosa/librosa: 0.10.0 (0.10.0), Zenodo [code], https://doi.org/10.5281/zenodo.7657336, 2023.
Mousavi, S. M. and Langston, C.A.: Automatic noise-removal/signal-removal
based on general cross-validation thresholding in synchrosqueezed domain and
its application on earthquake data, Geophysics, 82.4, V211–V227,
https://doi.org/10.1190/geo2016-0433.1, 2017.
Müller, M.: Fundamentals of music processing: Audio, analysis,
algorithms, applications, Cham, Switzerland: Springer International
Publishing, https://doi.org/10.1007/978-3-319-21945-5, 2015.
Negi, S. S., Kumar, A., Ningthoujam, L. S., and Pandey, D. K.: An Efficient
Approach of Data Adaptive Polarization Filter to Extract Teleseismic Phases
from the Ocean-Bottom Seismograms, Seismol. Soc. Am., 92,
528–542, https://doi.org/10.1785/0220200034, 2021.
Rafii, Z. and Pardo, B.: Music/Voice Separation Using the Similarity
Matrix, Proc. ISMIR, 583–588, 2012.
Rafii, Z., Liutkus, A., and Pardo, B.: REPET for background/foreground
separation in audio, in: Blind Source Separation, Springer,
Berlin, Heidelberg, 395-411, https://doi.org/10.1007/978-3-642-55016-4_14, 2014.
Rafii, Z., Liutkus, A., Stöter, F. R., Mimilakis, S. I., FitzGerald, D.,
and Pardo, B.: An overview of lead and accompaniment separation in
music, IEEE T. Audio Speech, 26, 1307–1335, https://doi.org/10.1109/TASLP.2018.2825440,
2018.
Ramakrushana Reddy, T., Dewangan, P., Arya, L., Singha, P., and Kamesh
Raju, K. A.: Tidal triggering of the harmonic noise in ocean-bottom
seismometers, Seismol. Res. Lett., 91, 803–813,
https://doi.org/10.1785/0220190080, 2020.
Rondenay, S.: Upper mantle imaging with array recordings of converted and
scattered teleseismic waves, Surv. Geophys., 30, 377–405,
https://doi.org/10.1007/s10712-009-9071-5, 2009.
Romanowicz, B., Stakes, D., Montagner, J. P., Tarits, P., Uhrhammer, R.,
Begnaud, M., Stutzmann, E., Pasyanos, M., Karczewski, J. F., Etchemendy, S.,
and Neuhauser, D.: MOISE: A pilot experiment towards long term sea-floor
geophysical observatories, Earth Planets Space, 50, 927–937,
https://doi.org/10.1186/BF03352188, 1998.
Schlindwein, V., Wassermann, J., and Scherbaum, F.: Spectral analysis of
harmonic tremor signals at Mt. Semeru volcano, Indonesia, Geophys. Res.
Lett., 22, 1685–1688, https://doi.org/10.1029/95GL01433, 1995.
Schlindwein, V., Krüger, F., and Schmidt-Aursch, M.: Project KNIPAS: DEPAS
ocean-bottom seismometer operations in the Greenland Sea in
2016-2017, Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Bremerhaven, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.896635,
2018.
Schmidt-Aursch, M. and Haberland, C.: DEPAS (Deutscher Geräte-Pool für amphibische Seismologie): German instrument pool for amphibian seismology, J. Largescale Res. Facil., 3, A122, https://doi.org/10.17815/jlsrf-3-165, 2017.
Silver, P. G. and Chan, W. W.: Shear wave splitting and subcontinental mantle
deformation, J. Geophys. Res., 96, 16429–16454,
https://doi.org/10.1029/91JB00899, 1991.
Stähler, S. C., Schmidt-Aursch, M. C., Hein, G., and Mars, R.: A
self-noise model for the German DEPAS OBS pool, Seismol. Res. Lett., 89,
1838–1845, https://doi.org/10.1785/0220180056, 2018.
Tanimoto, T. and Rivera, L.: The ZH ratio method for long-period seismic data:
sensitivity kernels and observational techniques, Geophys. J. Int., 172,
187–198, https://doi.org/10.1111/j.1365-246X.2007.03609.x, 2008.
Vaseghi, S. V.: Advanced signal processing and digital noise reduction,
Vieweg + Teubner Verlag, https://doi.org/10.1002/9780470740156, 1996.
Wang, R.: A simple orthonormalization method for stable and efficient
computation of Green's functions, B. Seismol. Soc. Am., 89, 733–741,
https://doi.org/10.1785/BSSA0890030733, 1999.
Webb, S. C.: Broadband seismology and noise under the ocean, Rev.
Geophys., 36, 105–142, https://doi.org/10.1029/97RG02287, 1998.
Webb, S. C., Zhang, X., and Crawford, W.: Infragravity waves in the deep
ocean, J. Geophys. Res.-Oceans, 96, 2723–2736,
https://doi.org/10.1029/90JC02212, 1991.
Zali, Z.: ZahraZali/NoiseCut: NoiseCut (v1.0.0), Zenodo [code],
https://doi.org/10.5281/zenodo.7339552, 2022.
Zali, Z., Ohrnberger, M., Scherbaum, F., Cotton, F., and Eibl, E. P.:
Volcanic Tremor Extraction and Earthquake Detection Using Music Information
Retrieval Algorithms, Seismol. Res. Lett., 92, 3668–3681,
https://doi.org/10.1785/0220210016, 2021.
Zhu, W., Mousavi, S. M., and Beroza, G. C.: Seismic signal denoising and
decomposition using deep neural networks, IEEE T. Geosci. Remote., 57,
9476–9488, https://doi.org/10.1109/TGRS.2019.2926772, 2019.
Short summary
Investigation of the global Earth's structure benefits from the analysis of ocean bottom seismometer (OBS) data that allow an improved seismic illumination of dark spots of crustal and mantle structures in the oceanic regions of the Earth. However, recordings from the ocean bottom are often highly contaminated by noise. We developed an OBS noise reduction algorithm, which removes much of the oceanic noise while preserving the earthquake signal and does not introduce waveform distortion.
Investigation of the global Earth's structure benefits from the analysis of ocean bottom...