Seismic depth imaging of iron‐oxide deposits and their host rocks in the Ludvika mining area of central Sweden

• Published in: Geophysical Prospecting 2020-01, Vol.68 (1), p.24-43
• Main Authors: Bräunig, Lena, Buske, Stefan, Malehmir, Alireza, Bäckström, Emma, Schön, Monica, Marsden, Paul
• Format: Article
• Language: English
• Subjects: Algorithms; Analytical methods; Banded structure; Boreholes; Data; Data acquisition; Data processing; Datasets; Depth; Fault lines; Frequencies; Geophysical exploration; Geophysical methods; Geophysics; Heterogeneity; High resolution; Imaging; Imaging techniques; Iron; Mineral deposits; Mineral exploration; Mineral resources; Mineralization; Mining; Overburden; Reflectors; Resolution; Seismic exploration; Seismics; Structures; Tomography; Velocity; Wavelength; Workflow
• ISSN: 0016-8025; 1365-2478; 1365-2478
• DOI: 10.1111/1365-2478.12836

ABSTRACT The development of cost‐effective and environmentally acceptable geophysical methods for the exploration of mineral resources is a challenging task. Seismic methods have the potential to delineate the mineral deposits at greater depths with sufficiently high resolution. In hardrock environments, which typically host the majority of metallic mineral deposits, seismic depth‐imaging workflows are challenged by steeply dipping structures, strong heterogeneity and the related wavefield scattering in the overburden as well as the often limited signal‐to‐noise ratio of the acquired data. In this study, we have developed a workflow for imaging a major iron‐oxide deposit at its accurate position in depth domain while simultaneously characterizing the near‐surface glacial overburden including surrounding structures like crossing faults at high resolution. Our workflow has successfully been showcased on a 2D surface seismic legacy data set from the Ludvika mining area in central Sweden acquired in 2016. We applied focusing prestack depth‐imaging techniques to obtain a clear and well‐resolved image of the mineralization down to over 1000 m depth. In order to account for the shallow low‐velocity layer within the depth‐imaging algorithm, we carefully derived a migration velocity model through an integrative approach. This comprised the incorporation of the tomographic near‐surface model, the extension of the velocities down to the main reflectors based on borehole information and conventional semblance analysis. In the final step, the evaluation and update of the velocities by investigation of common image gathers for the main target reflectors were used. Although for our data set the reflections from the mineralization show a strong coherency and continuity in the seismic section, reflective structures in a hardrock environment are typically less continuous. In order to image the internal structure of the mineralization and decipher the surrounding structures, we applied the concept of reflection image spectroscopy to the data, which allows the imaging of wavelength‐specific characteristics within the reflective body. As a result, conjugate crossing faults around the mineralization can directly be imaged in a low‐frequency band while the internal structure was obtained within the high‐frequency bands.