Abstract

Although generally very powerful, ground roll and multiple attenuation techniques can often leave remnants in seismic data. For example, ground roll can be hard to model and fully remove using standard methods. Similarly, multiple remnants are often present after multiple attenuation when multiples are generated by relatively complex geology, such as rugose water bottoms or salt, and as such do not conform to the assumptions of most multiple attenuation algorithms. These remnants can cause problems in later processing, for example through the generation of migration noise and contamination of AVO analysis etc. and therefore often need to be further attenuated in the processing sequence. As these remnants are often localized and may have high amplitudes compared to the underlying data, they can be relatively easy to identify and can be targeted in a different number of domains. The application of a wavelet transform (wavelet decomposition) on pre-stack data can be used to separate signal from coherent noise in both frequency and time. The noise can then be removed from the data by a variety of noise attenuation methods in the wavelet domain.