Extending the useable bandwidth of seismic data with tensor-guided, frequency-dependent filtering

Abstract

Improving the bandwidth of seismic data has been an ongoing endeavour in increasing the usability of seismic data in many plays throughout the world. While various broadband acquisition techniques have been recently developed for marine acquisition, the most significant issue for land seismic has been the low signal-to-noise ratio, particularly at the low and high ends of the frequency spectrum. In this paper, we describe a frequency-dependent filtering technique that can significantly increase the available bandwidth of the seismic data. We show a field data example and demonstrate that the enhanced bandwidth seismic data ties with well logs in the area. A variety of methods have been proposed to increase the bandwidth of seismic data that fall broadly into three categories: 1. Inversion-type approaches where some pre-determined information or assumption is used to overcome the inherent non-uniqueness of the inversion solution (Zhang and Castangna, 2011). 2. Methods that use the available bandwidth with high signal-to-noise to extrapolate or ‘predict’ the low and high-frequency components (Smith et al., 2008). 3. Methods that apply some sort of frequency-dependent filtering to the seismic data to improve the signal-to-noise of the high and/or low-frequency components (Whitcome and Hodgson, 2007).