1887

Abstract

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

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609-pdb.38.F067
2003-09-01
2020-09-21
Loading full text...

Full text loading...

http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609-pdb.38.F067
Loading
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error