Data Reconstruction Using Seismic Interferometry Applied to Active-Source Data from the Ludvika Mines of Sweden

Summary Dense and regular trace sampling is of great importance when utilizing seismic methods for exploration. An increment in the fold coverage can improve the illumination of the subsurface, resulting in better images of potential deposits and also the structures hosting them. Additionally, different advanced seismic processing and imaging algorithms require dense and regular datasets in order to achieve optimum results. Thus, we propose using data retrieved by seismic interferometry as a data-driven method to provide missing traces for relatively large source or receiver gaps. Together with a data-reconstruction algorithm, we merge these two datasets in an optimal way for further processing as just one dataset. We apply the proposed methodology to an active-source dataset acquired at the Ludvika Mines of Sweden for imaging of its iron-oxide deposit.