The radial trace transform: An effective domain for coherent noise attenuation and wavefield separation

1999 ◽  
Author(s):  
D. C. Henley
Keyword(s):  
Noise Attenuation ◽  
Coherent Noise ◽  
Wavefield Separation ◽  
Trace Transform ◽  
Effective Domain ◽  
Radial Trace Transform

Bayesian wavefield separation by transform-domain sparsity promotion

Geophysics ◽  
2008 ◽  
Vol 73 (5) ◽  
pp. A33-A38 ◽  
Author(s):  
Deli Wang ◽  
Rayan Saab ◽  
Özgür Yilmaz ◽  
Felix J. Herrmann
Keyword(s):  
Bayesian Approach ◽  
Real Data ◽  
Transform Domain ◽  
Coherent Noise ◽  
Noise Sources ◽  
Wavefield Separation ◽  
Ground Roll ◽  
Successful Removal ◽  
Multiple Elimination ◽  
Made In

Successful removal of coherent-noise sources greatly determines seismic imaging quality. Major advances have been made in this direction, e.g., surface-related multiple elimination (SRME) and interferometric ground-roll removal. Still, moderate phase, timing, amplitude errors, and clutter in predicted signal components can be detrimental. Adopting a Bayesian approach, along with assuming approximate curvelet-domain independence of the to-be-separated signal components, we construct an iterative algorithm that takes predictions produced by, for example, SRME as input and separates these components in a robust manner. In addition, the proposed algorithm controls the energy mismatch between separated and predicted components. Such a control, lacking in earlier curvelet-domain formulations, improves results for primary-multiple separation on synthetic and real data.

A procedure for optimally removing localized coherent noise

Geophysics ◽  
1995 ◽  
Vol 60 (1) ◽  
pp. 191-203 ◽  
Author(s):  
A. Frank Linville ◽  
Robert A. Meek
Keyword(s):  
Seismic Data ◽  
Seismic Profile ◽  
Noise Attenuation ◽  
Signal Distortion ◽  
Coherent Noise ◽  
Vertical Seismic Profile ◽  
Seismic Records ◽  
Signal Distortions ◽  
Notch Filtering ◽  
Phase Differences

Primary reflections in seismic records are often obscured by coherent noise making processing and interpretation difficult. Trapped water modes, surface waves, scattered waves, air waves, and tube waves to name a few, must be removed early in the processing sequence to optimize subsequent processing and imaging. We have developed a noise canceling algorithm that effectively removes many of the commonly encountered noise trains in seismic data. All currently available techniques for coherent noise attenuation suffer from limitations that introduce unacceptable signal distortions and artifacts. Also, most of those techniques impose the dual stringent requirements of equal and fine spatial sampling in the field acquisition of seismic data. Our technique takes advantage of characteristics usually found in coherent noise such as being localized in time, highly aliased, nondispersive (or only mildly so), and exhibit a variety of moveout patterns across the seismic records. When coherent noise is localized in time, a window much like a surgical mute is drawn around the noise. The algorithm derives an estimate of the noise in the window, automatically correcting for amplitude and phase differences, and adaptively subtracts this noise from the window of data. This signal estimate is then placed back in the record. In a model and a land data example, the algorithm removes noise more effectively with less signal distortion than does f-k filtering or velocity notch filtering. Downgoing energy in a vertical seismic profile (VSP) with irregular receiver spacing is also removed.

Coherent noise attenuation using the Wavelet Transform on Radial Basis

2015 ◽  
Author(s):  
Lucas J. A. Almeida* ◽  
Rafael R. Manenti ◽  
Milton J. Porsani
Keyword(s):  
Wavelet Transform ◽  
Noise Attenuation ◽  
Coherent Noise ◽  
Radial Basis

Model‐based coherent noise attenuation for complex dispersive waves

2011 ◽  
Author(s):  
Claudio Strobbia ◽  
Alexander Zarkhidze ◽  
Roger May ◽  
John Quigley ◽  
Phil Bilsby
Keyword(s):  
Noise Attenuation ◽  
Coherent Noise ◽  
Dispersive Waves ◽  
Model Based
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