Data reconstruction using a six-dimensional model space

While 5D data reconstruction has become widespread in recent years, we show that the use of 5D model spaces in some settings may result in sub-optimal handling of structures exhibiting HTI traveltime behaviour. To overcome these problems we propose the use of a 6D model space based on an extension of the parametric definition of Hugonnet et al. (2008). The model is solved using a sparse solver based on the anti-leakage Fourier transform of Xu et al. (2005). Synthetic and real datasets exhibiting HTI anisotropy are used to illustrate the signal preserving benefits of the approach.