Deep reflection seismic imaging of iron‐oxide deposits in the Ludvika mining area of central Sweden

Creator/Principal investigator(s)

Alireza Malehmir - Uppsala University, Department of Earth Sciences orcid

Description

Reflection seismic data were acquired within two field campaigns in the Blötberget, Ludvika mining area of central Sweden, for deep imaging of iron‐oxide mineralization that were known to extend down to 800–850 m depth. The two surveys conducted in years 2015 and 2016, one employing a seismic landstreamer and geophones connected to wireless recorders, and another one using cabled geophones and wireless recorders, aimed to delineate the geometry and depth extent of the iron‐oxide mineralization for when mining commences in the area. Even with minimal and conventional processing approaches, the merged datasets provide encouraging information about the depth continuation of the mineralized horizons and the geological setting of the study area. Multiple sets of strong reflections represent a possible continuation of the known deposits that extend approximately 300 m further down‐dip than the known 850 m depth obtained from historical drilling. They show excellent correlation in shape and strength with those of the Blötberget deposits. Furthermore, several reflections in the footwall of the known m

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Creator/Principal investigator(s)

Alireza Malehmir - Uppsala University, Department of Earth Sciences orcid

Identifiers

SND-ID: 2020-190

Description

Reflection seismic data were acquired within two field campaigns in the Blötberget, Ludvika mining area of central Sweden, for deep imaging of iron‐oxide mineralization that were known to extend down to 800–850 m depth. The two surveys conducted in years 2015 and 2016, one employing a seismic landstreamer and geophones connected to wireless recorders, and another one using cabled geophones and wireless recorders, aimed to delineate the geometry and depth extent of the iron‐oxide mineralization for when mining commences in the area. Even with minimal and conventional processing approaches, the merged datasets provide encouraging information about the depth continuation of the mineralized horizons and the geological setting of the study area. Multiple sets of strong reflections represent a possible continuation of the known deposits that extend approximately 300 m further down‐dip than the known 850 m depth obtained from historical drilling. They show excellent correlation in shape and strength with those of the Blötberget deposits. Furthermore, several reflections in the footwall of the known m

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Language

English

Time period(s) investigated

2015-09-01 — 2016-10-01

Geographic spread

Geographic location: Dalarna County, Ludvika Municipality

Geographic description: The study area, Blötberget in the Ludvika mining area belongs to the Bergslagen mineral district of south‐central Sweden.

Funding

Funding agency: European Union's Horizon 2020

Funding agency’s reference number: 775971

Contact for questions about the data

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Publications

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Malehmir, A., Maries, G., Bäckström, E., Schon, M., & Marsden, P. (2017). Deep Targeting an Iron-Oxide Ore Body Using a Seismic Landstreamer and a 500-Kg Drop Hammer Source. 79th EAGE Conference and Exhibition 2017. https://doi.org/10.3997/2214-4609.201701416
DOI: https://doi.org/10.3997/2214-4609.201701416
URN: urn:nbn:se:uu:diva-326271

Braunig, L., Buske, S., Malehmir, A., Backstrom, E., Schon, M., & Marsden, P. (2020). Seismic depth imaging of iron-oxide deposits and their host rocks in the Ludvika mining area of central Sweden. Geophysical Prospecting, 68(1), 24–43. https://doi.org/10.1111/1365-2478.12836
DOI: https://doi.org/10.1111/1365-2478.12836
URN: urn:nbn:se:uu:diva-409455

Markovic, M., Maries, G., Malehmir, A., von Ketelhodt, J., Bäckström, E., Schön, M., & Marsden, P. (2020). Deep reflection seismic imaging of iron-oxide deposits in the Ludvika mining area of central Sweden. Geophysical Prospecting, 68(1), 7–23. https://doi.org/10.1111/1365-2478.12855
DOI: https://doi.org/10.1111/1365-2478.12855
URN: urn:nbn:se:uu:diva-408710

Balestrini, F., Draganov, D., Malehmir, A., Marsden, P., & Ghose, R. (2020). Improved target illumination at Ludvika mines of Sweden through seismic-interferometric surface-wave suppression. Geophysical Prospecting, 68(1), 200–213. https://doi.org/10.1111/1365-2478.12890
URN: urn:nbn:se:uu:diva-408468
DOI: https://doi.org/10.1111/1365-2478.12890

Malehmir, A., Maries, G., Bäckstrom, E., Schön, M., & Marsden, P. (2017). Developing cost-effective seismic mineral exploration methods using a landstreamer and a drophammer. Scientific Reports, 7, Article 10325. https://doi.org/10.1038/s41598-017-10451-6
DOI: https://doi.org/10.1038/s41598-017-10451-6
URN: urn:nbn:se:uu:diva-335402

Papadopoulou, M., Col, F., Mi, B., Backstrom, E., Marsden, P., Brodic, B., Malehmir, A., & Socco, L. V. (2020). Surface-wave analysis for static corrections in mineral exploration : A case study from central Sweden. Geophysical Prospecting, 68(1), 214–231. https://doi.org/10.1111/1365-2478.12895
URN: urn:nbn:se:uu:diva-406181
DOI: https://doi.org/10.1111/1365-2478.12895

Maries, G., Malehmir, A., & Marsden, P. (n.d.). Cross-profile seismic data acquisition, imaging and modeling of iron-oxide deposits: A case study from Blötberget, south central Sweden. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-408711
URN: urn:nbn:se:uu:diva-408711

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Deep reflection seismic imaging of iron‐oxide deposits in the Ludvika mining area of central Sweden

Suggested citation

Alireza Malehmir. Uppsala University, Department of Earth Sciences (2021). <em>Deep reflection seismic imaging of iron‐oxide deposits in the Ludvika mining area of central Sweden</em>. Swedish National Data Service. Version 1. <a href="https://doi.org/10.5878/8gbt-cf87">https://doi.org/10.5878/8gbt-cf87</a>

Creator/Principal investigator(s)

Alireza Malehmir - Uppsala University, Department of Earth Sciences orcid

Description

The datasets consist of processed unmigrated stacked sections. One mixed file for 2015 and 2016 (see Markovic et al., 2020 and Malehmir et al., 2017) and one file for 2016 (see Markovic et al., 2020).

Data are available in SEG-Y format and can be read in 3D visualization software such as GOCAD. Examples of free non-proprietary programs that can be used are ssView (https://sourceforge.net/projects/simple-seismic/) and SeisSee (https://seisee.software.informer.com/).

Additional data can be mad

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Data format / data structure

3D

Published: 2021-01-15