Seismic methods are widely used for the exploration of the Earth’s subsurface. While they allow higher resolution compared to other geophysical methods, their performance depends on site and geological characteristics, and the volume and type of recorded information. Additionally, data processing plays a critical role in the efficacy of the application of seismic methods. A common challenge when utilising seismic methods arises as a result of field restrictions and cost constraints. As a consequence, seismic data often suffer from irregular or sparse spatial sampling, which can affect the application of advanced processing and imaging algorithms, for instance, surface-related multiple elimination and wave equation migration. These algorithms require dense and regular sampling to provide reliable results. Thus, seismic-data regularisation and interpolation are commonly utilised processing steps. Nevertheless, the interpolation of data for relatively large gaps is not trivial, in particular for land data acquired in complex geological settings where the seismic events exhibit pronounced curvature and lack of continuity....@en

Seismic interferometry (SI) is a method that retrieves new seismic traces from the cross-correlation of existing traces, where one of the receivers acts as a virtual seismic source whose response is retrieved at other receivers. When using sources only at the surface, and the so-called one-sided illumination of the receivers occurs, we will retrieve not only the desired physical reflections but also non-physical (ghost) reflections. These non-physical reflections appear due to waves that propagate inside a subsurface layer. Thus, they contain information about the seismic properties of the specific layer. We illustrate the technique’s potential using numerically modelled data for a subsurface model with a low-velocity layer, which is also pinching out, and near-surface field data. We apply SI by cross-correlation and auto-correlation. Both resulting non-physical reflections are sensitive to the physical rock properties of the layer that causes them to appear in the SI results. Moreover, non-physical reflections in zero-offset gathers that result from SI by auto-correlation show very good conformity with the geometry of the subsurface layers.@en

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.@en

In exploration seismology, surface waves generated by active sources usually mask events of interest like reflections and diffractions. This is exacerbated in high-noise, near-mine environments where the targets have often low-impedance contrasts. We present a purely data-driven approach for surface-waves attenuation in active-source reflection seismic data acquired at the Ludvika mining area of central Sweden in 2016. We apply seismic interferometry to the data in order to retrieve dominant surface waves between receivers. We then subtract them from the original data in an adaptive way for their attenuation. Our results show that the surface waves are well suppressed and the target mineralization signature is boosted allowing new features to be revealed. After a simple pre-stack processing, we obtain cleaner seismic sections with more continuous reflections.@en