Data reconstruction combining MWNI and CRS-based interpolation methods

Bezerra, Yuri Shalom de Freitas; Garabito, German; Sacchi, Mauricio D.; Caldeira, João

doi:10.1016/j.jappgeo.2022.104912

Cited by 1 publication

(2 citation statements)

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“…The results showed a significant improvement of the Tacutu basin data in relation to the combined algorithms applied separately, better solving steep curvature events. This methodology has formalized and expanded by Bezerra et al (2022), along with the presentation of another similar workflow, where CRSbased interpolation is applied to the original data, with the preconditioned CRS attributes obtained from the reconstructed data by the MWNI algorithm. The results shown a significant improvement of the Parnaíba basin data where the gaps are filled in more correctly.…”

Section: R a F Tmentioning

confidence: 99%

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Combination of Fourier and CRS-Based Reconstruction Algorithms in Land Seismic Data

Bezerra,

Garabito,

Sacchi

2024

Braz J Geophys

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ABSTRACT. The reconstruction based on the partial CRS stacking operator presents higher signal-to-noise ratio and better continuity of events. However, irregularly sampled land data often introduce errors in the CRS attributes, creating artifacts that contaminate the seismic data. Recently, the combination of Fourier and CRS-based reconstruction algorithms has significantly solved these problems. The approach consists of applying a Fourier-based interpolation method as a regularization operator to the original data and then the CRS attributes are searched in the reconstructed data. The CRS attributes determined in this way are more accurate and they can be applied in two different forms, either in the interpolation and regularization of the original data or in the denoising of the Fourier-based reconstructed data. We propose to compare the combination of the Fourier-based interpolation methods MWNI and MPFI with the CRSbased interpolation method in order to evaluate which is the best preconditioner of the prestack data to search the CRS attributes. We applied the proposed flowcharts combining the interpolation methods mentioned above to the land seismic data from the Tacutu basin, which is vintage data with very low fold and noisy. The reconstructed data obtained by the combinations show significant improvements compared to the data reconstructed using the algorithms separately, in other words, the weaknesses and limitations of each method are overcome when they are applied in combination. The MWNI+CRS combination flow produces the best results, with the stacked section of reconstructed data showing better noise removal, enhancement of coherent events, better definition and continuity of steeply dipping events.

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Section: R a F Tmentioning

confidence: 99%

“…The traditional CRS-based interpolation strategy uses only the original prestack data, both to determine the three CRS attributes and to apply the interpolation process. This workflow proposes to apply the attribute search in the reconstructed data Fourier-based Bezerra et al (2022).…”

Section: Fourier+crs Interpolation Workflowmentioning

confidence: 99%