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 equations previously used for 3D Radon demultiple. The model is obtained using a sparse solver based on the anti-leakage Fourier transform. Synthetic and real datasets exhibiting HTI anisotropy are used to illustrate the signal preserving benefits of the approach.