Improved target illumination at Ludvika mines of Sweden through seismic-interferometric surface-wave suppression

Journal Article (2020)
Author(s)

F.I. Balestrini (TU Delft - Applied Geophysics and Petrophysics)

DS Draganov (TU Delft - Applied Geophysics and Petrophysics)

Alireza Malehmir (Uppsala University)

Paul Marsden (NIO (Nordic Iron Ore AB))

Ranajit Ghose (TU Delft - Applied Geophysics and Petrophysics)

Research Group
Applied Geophysics and Petrophysics
Copyright
© 2020 F.I. Balestrini, D.S. Draganov, Alireza Malehmir, Paul Marsden, R. Ghose
DOI related publication
https://doi.org/10.1111/1365-2478.12890
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 F.I. Balestrini, D.S. Draganov, Alireza Malehmir, Paul Marsden, R. Ghose
Research Group
Applied Geophysics and Petrophysics
Issue number
1
Volume number
68
Pages (from-to)
200-213
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Abstract

In mineral exploration, new methods to improve the delineation of ore deposits at depth are in demand. For this purpose, increasing the signal-to-noise ratio through suitable data processing is an important requirement. Seismic reflection methods have proven to be useful to image mineral deposits. However, in most hard rock environments, surface waves constitute the most undesirable source-generated or ambient noise in the data that, especially given their typical broadband nature, often mask the events of interest like body-wave reflections and diffractions. In this study, we show the efficacy of a two-step procedure to suppress surface waves in an active-source reflection seismic dataset acquired in the Ludvika mining area of Sweden. First, we use seismic interferometry to estimate the surface-wave energy between receivers, given that they are the most energetic arrivals in the dataset. Second, we adaptively subtract the retrieved surface waves from the original shot gathers, checking the quality of the unveiled reflections. We see that several reflections, judged to be from the mineralization zone, are enhanced and better visualized after this two-step procedure. Our comparison with results from frequency-wavenumber filtering verifies the effectiveness of our scheme, since the presence of linear artefacts is reduced. The results are encouraging, as they open up new possibilities for denoising hard rock seismic data and, in particular, for imaging of deep mineral deposits using seismic reflections. This approach is purely data driven and does not require significant judgment on the dip and frequency content of present surface waves, which often vary from place to place.