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Discussion papers
https://doi.org/10.5194/se-2019-29
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-2019-29
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 11 Feb 2019

Research article | 11 Feb 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Solid Earth (SE).

Improving quality of empirical Greens functions, obtained by cross-correlation of high-frequency ambient seismic noise

Nikita Afonin1,4, Elena Kozlovskaya1,2, Jouni Nevalainen1,3, and Janne Narkilahti3 Nikita Afonin et al.
  • 1Oulu Mining School, POB-3000, FIN-90014, University of Oulu, Finland
  • 2Geological Survey of Finland, P.O. Box 96, FI-02151, Espoo, Finland
  • 3Sodankylä Geophysical Observatory POB 3000, FIN-90014, University of Oulu, Finland
  • 4N. Laverov Federal Centre for the Integrated Arctic Research RAS, Arkhangelsk, Russia

Abstract. Studying the uppermost structure of the subsurface is a necessary part for solving many practical problems (exploration of minerals, groundwater studies, geoengineering, etc.). Practical application of active seismic methods is not always possible because of different reasons, such as logistical difficulties, high cost of work, high level of seismic and acoustic noise, etc. That is why developing and improving of passive seismic methods for these purposes is one of the important problems in applied geophysics. In our study, we describe the way of improving quality of Empirical Green’s Functions (EGFs), evaluated from high-frequency ambient seismic noise, by using of advanced technique of cross-correlation functions stacking in the time domain (in this paper we use term “high-frequency” for the frequencies higher than 1 Hz). In compare to existing techniques, based on weight-stacking, our proposed technique makes it possible to more significantly increase the signal-to-noise ratio and, therefore quality of the EGF. The technique is based on both iterative and global optimization algorithms, where the optimized parameter is a signal-to-noise ratio of an EGF, retrieved for each iteration. The technique has been tested with the field data acquired in an area with high level of industrial noise (Pyhäsalmi Mine, Finland) and in an area with low level of anthropogenic noise (Kuusamo Greenstone Belt, Finland). The results show that the our proposed technique can be used for extraction of EGFs from high-frequency seismic noise in practical problems of mapping of the shallow subsurface in areas with high and low level of high-frequency seismic noise.

Nikita Afonin et al.
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