Multi-dimensional data reconstruction and noise attenuation for optimal wide azimuth stack

Over recent years the value of wide-azimuth acquisition has been well documented. As well as significant improvements in the imaging of complex structures due to improved illumination, these data have also demonstrated benefits in the suppression of coherent and random noise and multiple energy. Two of the key factors controlling the quality of wide-azimuth datasets are high density regular sampling and good signal to noise. Using simple synthetics, we demonstrate the importance of regular sampling in the stack response. We continue by showing how data can be regularised and interpolated with 5D Fourier reconstruction to stack out more noise and improve the stack response of primary energy. In addition we highlight how the use of multi-dimensional denoising techniques can be used to enhance weak energy where the signal-to-noise ratio is a problem.