  In this abstract, we propose a multiscale fusion technique to enhance seismic
geometric attributes, such as dip and curvature, which are very sensitive to
noise present in seismic data. For a give seismic section, first, we construct
a Gaussian pyramid that allows us to generate the seismic attribute at
different resolutions (scales). Then, all attributes at the different scales
are fused together to form the proposed multiscale enhanced attribute.
Applications to the 3D seismic dataset over the Great South Basin in New
Zealand demonstrate that the proposed method is capable of improving both the
resolution and noise robustness of the first-order dip and the second-order
curvature attributes, compared to existing methods and algorithm. Such
improvement indicates the great potential of our multiscale fusion technique
for enhancing the quality of more multitrace seismic attributes, such as
coherence, flexure, and GLCM.
