Shallow water demultiple with seafloor reflection modeling using multichannel prediction operator

Yang, Kunlun; Hung, Barry

doi:10.1190/segam2012-0994.1

Cited by 7 publications

(2 citation statements)

References 7 publications

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“…A new demultiple workflow, SWD (Yang, et al, 2012) preceding a SRME with ACDS, delivered higher fidelity results compared to the existing workflow employing least squares subtraction. It is highlighted here that ACDS (Wu et al, 2013) played a critical role in the new workflow.…”

Section: Introductionmentioning

confidence: 99%

FWI and RTM 3D Seismic Reprocessing of Vintage data from Carbonate Basement

et al. 2014

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TX 75083-3836, U.S.A., fax ϩ1-972-952-9435 SUMMARYReprocessing of vintage seismic data was conducted to address reservoir uncertainties in a fractured and karstified carbonate basement. The objectives were achieved by employing advanced processing technologies that included Full Waveform Inversion (FWI), TTI Reverse Time Migration (TTI TRM), Adaptive Curvelet Domain Multiple Separation (ACDS) and azimuthal anisotropic NMO.FWI is a data-fitting method designed to deliver high-quality, high-resolution velocity models critical for PSDM imaging. Currently, FWI concentrates on low frequency (3 -10Hz) transmitted energy (head waves and diving waves) as well as some reflection energy. The resulting FWI velocity model displayed very high resolution and good geological correlation. Forward modeling through the FWI technique generated synthetic shots that corresponded to the real seismic shots accurately.TTI RTM was applied to complement the high resolution FWI model and to achieve the best imaging around the target area where velocities were complex. Prior to the imaging Shallow Water Demultiple (SWD) and Surface Related Multiple Elimination (SRME), multiple separation was as critical to multiple prediction. A conventional Least Squares separation was applied in the 2D X-T domain. However, it was unsuccessful in separating crossing primaries and multiples with similar dips. Therefore, ACDS was appliedin the 4D curvelet domain and achieved successful representation of linear and curved events with sparse coefficients. Finally, azimuthal anisotropy was observed in the CDP gathers and in the crossline sections. Azimuthal anisotropic NMO based on a scanning method corrected this effect and aligned the data thoroughly.These technologies covered pre-migration processing, velocity modelling and migration. The combined application of these advanced technologies delivered significant improvement of the overall seismic quality, with reduced multiple contamination, sharper fault definitions, a crisper top basement and superiorfracture imaging within the basement.

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Section: Introductionmentioning

confidence: 99%

FWI and RTM 3D Seismic Reprocessing of Vintage data from Carbonate Basement

et al. 2014

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“…Surface-Related Multiple Elimination (SRME) is used routinely in the industry to eliminate longperiod multiples. Short-period multiples generated from the shallow seafloor and internal multiples generated by subsurface interfaces of high impedance contrast have also received attention in the areas of multiple modelling (Hargreaves, 2006;Hung et al, 2010;Wang et al, 2011;Wang et al, 2012;Yang and Hung, 2012).…”

Section: Introductionmentioning

confidence: 99%

High-fidelity Adaptive Curvelet Domain Primary-Multiple Separation

Wu¹,

Hung²

2013

London 2013, 75th Eage Conference en Exhibition Incorporating SPE Europec

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Closed-loop surface-related multiple estimation with full-wavefield migration-reconstructed near offsets for shallow water

Zhang

Verschuur

2021

GEOPHYSICS

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Reliably separating primary and multiple reflections in a shallow water environment (i.e., 50 m to 200 m water depth) still remains a challenge. The success of previously published closed-loop surface-related multiple estimation (CL-SRME) depends heavily on the data coverage, i.e., the near-offset reconstruction. Therefore, we propose the integrated framework of CL-SRME and full-wavefield migration (FWM). Multiples recorded in the data are capable of helping infill the acquisition imprint of the FWM image. With this image as a strong constraint, we are able to reconstruct the data at near-offsets, which is essential for better primary and multiple estimation during CL-SRME. FWM applied in a non-linear way can avoid the negative influences from the missing data, and at the same time bring in more physics between primaries and multiples. The FWM image of the top part of the subsurface is also used to back-project the information from multiples to primaries with the physical constraint of all this information belongs to the same earth model, provided that a good description of the source wavefield and a reasonable velocity model are available. The proposed integrated framework first reconstructs near-offsets via the closed-loop imaging process of FWM and then feeds the complete reconstructed data to CL-SRME for better primary and multiple estimation. A good performance is demonstrated on both 2D synthetic and field data examples in a challenging shallow water environment.

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Shallow water demultiple with seafloor reflection modeling using multichannel prediction operator

Cited by 7 publications

References 7 publications

FWI and RTM 3D Seismic Reprocessing of Vintage data from Carbonate Basement

FWI and RTM 3D Seismic Reprocessing of Vintage data from Carbonate Basement

High-fidelity Adaptive Curvelet Domain Primary-Multiple Separation

Closed-loop surface-related multiple estimation with full-wavefield migration-reconstructed near offsets for shallow water

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