The impact of field‐survey characteristics on surface‐relatedmultiple attenuation

Dragoset, Bill; Moore, Ian D.; Kostov, C.

doi:10.1111/j.1365-2478.2006.00581.x

Cited by 14 publications

(1 citation statement)

References 12 publications

(19 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If the prediction step was perfect, i.e., the predicted multiples matched the actual multiples in the data, then simple subtraction of predicted multiples from the input data would give us the multiple-free seismic recordings, called primaries. Unfortunately, multiple predictions are never perfect due to mismatches between amplitudes, phases, travel time, acquisition wavelets, and others (Verschuur and Berkhout, 1997;Dragoset et al, 2006). A common practice is to perform the multiple subtraction in an adaptive manner to account for the aforementioned data mismatches.…”

Section: Introductionmentioning

confidence: 99%

Adaptive multiple separation based on information maximization

Liu¹,

Dragoset²

2012

SEG Technical Program Expanded Abstracts 2012

View full text Add to dashboard Cite

We are interested in the problem of separating primary and multiple seismic signals based on their statistical properties. We present a novel adaptive subtraction method based on an information maximization principle. Compared with previous methods, our proposed method has the theoretical advantages of utilizing higher-order statistics of the data and incorporating the filtering nature of the adaptive subtraction problem into our algorithm formulation. Furthermore, our proposed method provides a flexible framework for simultaneously subtracting more than one set of multiple predictions from the input data. We use simulations to show that our proposed adaptive subtraction method outperforms the popular least-square adaptive subtraction and the independent component analysis methods both quantitatively, as measured by the mean-squared error, and qualitatively, as evaluated by the visual quality of the image reconstruction.

show abstract

Section: Introductionmentioning

confidence: 99%

Adaptive multiple separation based on information maximization

Liu¹,

Dragoset²

2012

SEG Technical Program Expanded Abstracts 2012

View full text Add to dashboard Cite

show abstract

Imaging of first-order surface-related multiples by reverse-time migration

Liu

Liu²,

et al. 2016

Geophys. J. Int.

View full text Add to dashboard Cite

The influence of errors in the source wavelet on inversion‐based surface‐related multiple attenuation

Yuan

Wang

Yuan³

et al. 2017

Geophysical Prospecting

View full text Add to dashboard Cite

We investigate the influence of source wavelet errors on inversion‐based, surface‐related multiple attenuation, in order to address how the inverted primary impulse response, estimated primaries, and predicted multiples are affected by the estimated wavelet. In theory, errors in estimated wavelet can lead to errors in the upgoing waves. Because of smoothness and the band‐limitedness characteristics of the estimated wavelet, errors in the upgoing waves are usually not white and random. Theoretical analysis and two synthetic examples demonstrate that (i) when the overall amplitude scalar of the estimated wavelet is underestimated, the inversion of the primary impulse response suffers from instability, which will distort the estimation of primaries, and (ii) when the wavelet is overestimated, the estimated primaries will simply mimic the recorded upgoing waves. Nevertheless, the quality of the estimated primaries in the region above the first‐order, water‐bottom multiples is independent of the estimated wavelet. Synthetic results illustrate that inversion‐based, surface‐related multiple attenuation with a known wavelet is stable, since slight inaccuracy in amplitude spectrum and/or phase spectrum of the given wavelet or the corresponding upgoing waves will not lead to considerable deviation in the waveforms of the inverted results from those of the references. Furthermore, shot‐to‐shot wavelet variations, with maximum amplitude difference of 5% and maximum phase difference of 10°, create just slight artefacts in both the inverted primary impulse response and the estimated primaries. Moreover, the sensitivity test of estimation of primaries by sparse inversion method involving wavelet estimation shows that this method can stably and alternately update the wavelet and the primary impulse response; however, different choices of the initial wavelet can lead to different final inverted results.

show abstract

The impact of field‐survey characteristics on surface‐relatedmultiple attenuation

Cited by 14 publications

References 12 publications

Adaptive multiple separation based on information maximization

Adaptive multiple separation based on information maximization

Imaging of first-order surface-related multiples by reverse-time migration

The influence of errors in the source wavelet on inversion‐based surface‐related multiple attenuation

Contact Info

Product

Resources

About