Kristian Jensen

Title: Modelling and processing of flexural ice waves

Abstract: One of the most common problems with seismic data obtained in Arctic environments is the presence of so-called flexural ice wave noise on the seismic raw data. Flexural wave noise occurs on seismic data acquired on ice sheets in the transition zone between the shoreline and a water depth of approximately 5.5 meters. As the flexural waves are highly dispersive they are manifested as a broad fan of noise on the seismic data, often having an order of magnitude 40-60 dB higher than reflected signals. In addition, the frequency spectrum of flexural ice waves frequently overlaps with reflected signals, and due to the low velocities of flexural waves, spatial aliasing commonly occurs. Thus, flexural waves are difficult to remove using conventional seismic processing.

This study aims to outline how flexural waves may be modelled synthetically, as well as how effective various processing techniques are in removing the flexural waves while keeping reflected signals intact. Through investigating how parameters such as ice temperature and ice thickness affect the modelled flexural waves insight into the dispersion relation of the flexural waves may be obtained. Further, by comparing various processing approaches, knowledge about which parameters should be taken into account when setting up a processing work flow may be acquired. Results of the analysis indicates that conventional f-k filtering works well when dense receiver spacing is used to lessen spatial aliasing. Further, when the flexural wave velocities are separated from wave velocities in the subsurface layers, Tau-p filtering provides a good approach for effectively muting flexural wave noise. When these criteria are not met, however, more unconventional approaches, or a combination of various approaches, are required.