Intelligent Adaptive Subtraction for Multiple Attenuation

Perrier, S.; Dyer, Richard; Liu, Y.; Nguyen, Truong Thao; Lecocq, P.

doi:10.3997/2214-4609.201701237

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2017

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“…We found that at lower frequencies, the improved method for LSF subtraction produces better results. Both multiple subtraction techniques have been integrated into an intelligent adaptive subtraction program (Perrier et al, 2017) that combines different multiple subtraction techniques to produce the optimum demultiple.…”

Section: Examplesmentioning

confidence: 99%

Seismic Noise Attenuation Using Curvelet Transform and Dip Map Data Structure

Nguyen

Liu

2017

Proceedings

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The curvelet transform is a known tool used in the attenuation of coherent and incoherent noise in seismic data. It utilises the fact that signal and noise are usually better separated in the curvelet domain than in the timespace (TX) domain. Coefficients of the transform are not independent and neighbouring coefficients are strongly correlated, which existing curvelet-based noise attenuation algorithms do not fully utilise. In this work we propose to use a data structure called a 'dip map' to describe dip information in seismic data. This information links local curvelet coefficients together in adaptive thresholding or subtraction of curvelet coefficients in seismic denoising algorithms. We used the dip map to improve curvelet multiple subtraction algorithm and the results show significant improvement over traditional methods with real data.

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Section: Examplesmentioning

confidence: 99%