Abstract
Abstract. To discover or delineate mineral deposits and other geological features such as faults and lithological boundaries in their host rocks, seismic methods are preferred for imaging the targets at great depth. One major goal for seismic methods is to produce a reliable image of the reflectors underground given the typical discontinuous geology in crystalline environments with low signal-to-noise ratios. In this study, we investigate the usefulness of the reverse time migration (RTM) imaging algorithm in hardrock environments by applying it to a 2D dataset, which was acquired in the Ludvika mining area of central Sweden. We provide a how-to solution for applications of RTM in future and similar datasets. When using the RTM imaging technique properly, it is possible to obtain high-fidelity seismic images of the subsurface. Due to good amplitude preservation in the RTM image, the imaged reflectors provide indications to infer their geological origin. In order to obtain a reliable RTM image, we performed a detailed data pre-processing flow to deal with random noise, near-surface effects, and irregular receiver and source spacing, which can downgrade the final image if ignored. Exemplified with the Ludvika data, the resultant RTM image not only delineates the iron oxide deposits down to 1200 m depth as shown from previous studies, but also provides a better inferred ending of sheet-like mineralization. Additionally, the RTM image provides much-improved reflection of the dike and crosscutting features relative to the mineralized sheets when compared to the images produced by Kirchhoff migration in the previous studies. Two of the imaged crosscutting features are considered to be crucial when interpreting large-scale geological structures at the site and the likely disappearance of mineralization at depth. Using a field dataset acquired in hardrock environment, we demonstrate the usefulness of RTM imaging workflows for deep targeting mineral deposits.
Highlights
Seismic methods are favourable for deep targeting in mineral exploration because of their ability to image targets at great depth (> 500 m) (e.g. Malehmir et al, 2012b)
We found that the reverse time migration (RTM) section (Fig. 11d) obtained using the data pre-processed with median filter did not present the obvious crosscutting feature F1 that was shown in the RTM section (Fig. 11a) with the curvelet filter in the pre-processing
Based on the flatness of those events in common image gathers (CIGs) images, we argue that the current velocity model works well for imaging the mineral deposits at the site, though the migration velocity needs to be updated to better image other subsurface structures
Summary
Seismic methods are favourable for deep targeting in mineral exploration because of their ability to image targets at great depth (> 500 m) (e.g. Malehmir et al, 2012b). Seismic methods may provide an image of the targets with high resolution at depth when the survey is designed to record the signal reflected from the targets directly below the survey area and/or line In such a seismic survey, a seismic source (e.g. a sudden impact produced by a weight drop) should be employed to generate seismic wave fields with sufficient energy and frequency bandwidth Though Kirchhoff prestack depth imaging algorithms have been attempted with a few good illustrating results (Bellefleur et al, 2018; Bräunig et al, 2020), direct targeting deep mineral deposits using the RTM methods has rarely been applied to mineral exploration data examples. Our main goal is to demonstrate the usefulness of the seismic methods in deep targeting of iron oxide deposits by applying the RTM imaging algorithm (Baysal et al, 1983; Zhou et al, 2018) to a field dataset. We study and interpret the resultant RTM image by integrating it with other geological and geophysical datasets
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