1D wavelet transform based filtering is increasingly being used in seismic data noise attenuation. However, it doesn t take into account the spatial continuity of reflections, and is less effective when the dip is the main distinguishable feature between signal and noise. We have explored the characteristics of multi-scale and multi-orientation higher dimensional wavelet transforms. We discuss a wide range of desirable criteria, from practical applicability to general signal analysis. We have selected the complex wavelet transform, mainly from a practicality perspective and developed an adaptive noise attenuation approach to define a multi-dimensional threshold filter function in the time-space-scale-orientation space. The effectiveness of this complex wavelet transform based multi-dimensional filter is discussed together with a field data example.
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