Afonin, N., Kozlovskaya, E., Heinonen, S., and Buske, S.: Near-surface structure of the Sodankylä area in Finland, obtained by passive seismic interferometry, Solid Earth, 12, 1563–1579, https://doi.org/10.5194/se-12-1563-2021, 2021
Near-surface structure of the Sodankylä area in Finland, obtained by passive seismic interferometry
|Author:||Afonin, Nikita1,2; Kozlovskaya, Elena1,3,4; Heinonen, Suvi3;|
1Oulu Mining School, POB-3000, University of Oulu, 90014, Oulu, Finland
2N. Laverov Federal Center for Integrated Arctic Research of the Ural Branch of the Russian Academy of Sciences, Arkhangelsk, Russia
3Geological Survey of Finland, P.O. Box 96, 02151, Espoo, Finland
4Sodankylä Geophysical Observatory, University of Oulu, 90014, Oulu, Finland
5TU Bergakademie Freiberg, Institute of Geophysics and Geoinformatics, Freiberg, Germany
|Online Access:||PDF Full Text (PDF, 12.7 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2021090645220
|Publish Date:|| 2021-09-06
Controlled-source seismic exploration surveys are not always possible in nature-protected areas. As an alternative, the application of passive seismic techniques in such areas can be proposed. In our study, we show results of passive seismic interferometry application for mapping the uppermost crust in the area of active mineral exploration in northern Finland. We utilize continuous seismic data acquired by the Sercel Unite wireless multichannel recording system along several profiles during XSoDEx (eXperiment of SOdankylä Deep Exploration) multidisciplinary geophysical project. The objective of XSoDEx was to obtain a structural image of the upper crust in the Sodankylä area of northern Finland in order to achieve a better understanding of the mineral system at depth. The key experiment of the project was a high-resolution seismic reflection experiment. In addition, continuous passive seismic data were acquired in parallel with reflection seismic data acquisition. Due to this, the length of passive data suitable for noise cross-correlation was limited from several hours to a couple of days. Analysis of the passive data demonstrated that dominating sources of ambient noise are non-stationary and have different origins across the XSoDEx study area. As the long data registration period and isotropic azimuthal distribution of noise sources are two major conditions for empirical Green function (EGF) extraction under the diffuse field approximation assumption, it was not possible to apply the conventional techniques of passive seismic interferometry. To find the way to obtain EGFs, we used numerical modelling in order to investigate properties of seismic noise originating from sources with different characteristics and propagating inside synthetic heterogeneous Earth models representing real geological conditions in the XSoDEx study area. The modelling demonstrated that scattering of ballistic waves on irregular shape heterogeneities, such as massive sulfides or mafic intrusions, could produce a diffused wavefield composed mainly of scattered surface waves. In our study, we show that this scattered wavefield can be used to retrieve reliable EGFs from short-term and non-stationary data using special techniques. One of the possible solutions is application of “signal-to-noise ratio stacking” (SNRS). The EGFs calculated for the XSoDEx profiles were inverted, in order to obtain S-wave velocity models down to the depth of 300 m. The obtained velocity models agree well with geological data and complement the results of reflection seismic data interpretation.
|Pages:||1563 - 1579|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
The XSoDEx project was realized as a joint effort of the Geological Survey of Finland (coordinator); TU Bergakademie Freiberg; Institute of Geophysics and Geoinformatics, Freiberg, Germany; and University of Oulu, Finland. The field work of the University of Oulu personnel in summer 2017 was supported by the Renlund Foundation and by the University of Oulu. Financial support for processing and interpretation of the XSoDEx data used in this study was provided by the Geological Survey of Finland in 2018.
The numerical simulation and development of algorithms for passive seismic data processing used in the present paper was part of the ARCEMIS focus area spearhead projects funded by the KVANTUM Institute of the University of Oulu in 2017–2020, and it was partly supported by the project AAAA-A18 118012490072-7 funded by the Russian Federation Ministry of Science and Higher Education.
© Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License.