Iterative deblending with robust Fourier thresholding

Bahia, Breno; Lin, Rongzhi; Sacchi, Mauricio D.

doi:10.1190/segam2020-3425671.1

Cited by 5 publications

(1 citation statement)

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“…Imposing a sparsity constraint, an inversion-based deblending algorithm utilizes sparse representations of signal components in auxiliary domains to retrieve desired signals, which is referred to as sparse inversion. A number of studies have shown high-quality deblending in various domains such as the Radon domain (Akerberg et al 2008;Moore 2010;Ibrahim and Sacchi 2013;Lin and Sacchi 2020), the Fourier domain (Abma et al 2015;Song et al 2019;Kumar et al 2020;Bahia et al 2020), the Curvelet domain (Zu et al, 2016) and the Seislet domain (Chen et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Deblending and merging of 3D multi‐sweep seismic blended data

Jeong

Tsingas

Almubarak

2021

Geophysical Prospecting

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Seismic blended source acquisition, also referred to as simultaneous source acquisition, is a cost-effective technology that achieves a significant reduction in acquisition cycle time and increases seismic crew field productivity. The dispersed source array is a blended acquisition field technique that simultaneously employs sources emitting different types of sweeps (i.e. multi-sweep), in terms of frequency bandwidth and length, which ultimately will result in a full broadband seismic data. In this paper, deblending of 3D multi-sweep seismic blended data and the subsequent merging of the data volumes having different frequency bandwidths will be discussed. In specific data domains where the signal component is coherent, interference shots (i.e. blending noise) are randomly distributed in the data space according to its own shot firing time. Therefore, the deblending process, which separates interference shots from a signal component, becomes a noise attenuation problem. A sparse inversion methodology is applied in the frequency-wavenumber-wavenumber (f-k x -k y ) domain to attenuate blending noise. By applying this deblending methodology to both dispersed source array's low-and mid-high-frequency bandwidths, we obtained high-quality deblending results. For both frequency bandwidths of the deblended dispersed source array data, additional effort was made to combine the two datasets to a single broadband data volume. Consequently, deblending and merging of the dispersed source array blended data generated a broadband, deblended and well-balanced seismic volume suitable for further processing and reservoir characterization applications.

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