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Attenuation of Diffracted Multiples. Gabriel Alvarez Biondo Biondi Antoine Guitton. Stanford University. Goal. Introduce a method to attenuate diffracted multiples on 2D data, based on an apex-shifted Radon transform.
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Attenuation of Diffracted Multiples Gabriel Alvarez Biondo Biondi Antoine Guitton Stanford University
Goal Introduce a method to attenuate diffracted multiples on 2D data, based on an apex-shifted Radon transform. The method is applied in image space, in particular to Angle Domain Common Image Gathers (ADCIG). Alvarez-Biondi-Guitton
Motivation Aperture angle Aperture angle Aperture angle -60 0 60 -60 0 60 -60 60 0 1000 Depth (m) 4000 ADCIG Multiples Primaries Alvarez-Biondi-Guitton
Motivation Aperture angle Aperture angle Aperture angle -60 0 60 -60 0 60 -60 0 60 1000 Depth (m) 4000 ADCIG Primaries Multiples Alvarez-Biondi-Guitton
Apex-shifted Multiple Horizontal Coordinate (m) Aperture angle (degrees) -1000 3000 0 20 40 1.35 500 Time (s) Depth (m) 3000 1.6 Receiver-side peg-leg multiples Arrival times 0 Alvarez-Biondi-Guitton
A Note on Terminology Diffracted multiples: Multiples with apex-shifted residual moveout on ADCIGs migrated with primary velocity. Specularly-reflected multiples: Multiples whose residual moveout have their apex at zero aperture angle on ADCIGs migrated with primary velocity. Alvarez-Biondi-Guitton
What about SRME? Can Surface-Related Multiple Elimination (SRME) attenuate the apex-shifted multiples? Yes, but SRME requires dense, regular, large-aperture acquisition which is not generally available with today’s 3D streamer geometries. An alternative: apex-shifted Radon transform of ADCIGs. Alvarez-Biondi-Guitton
Aperture angle 0 Curvature (q) (γ) Primaries Depth Depth Multiple ADCIG Standard Radon Transform Alvarez-Biondi-Guitton
Apex-shifted Radon Transform 0 q γ γa 0 Primaries S-R multiples multiples ADCIG z z’ Alvarez-Biondi-Guitton
Separating Primaries and Multiples hγ 0 q 0 τ,z’ Zero out the primary region in the (z’,q,h) cube. Map the multiples back to the (z,γ) plane (ADCIG). Subtract the multiples from the original ADCIG to get the primaries. Alvarez-Biondi-Guitton
Image space vs. data space In complex geology the primaries are more likely to be horizontal in ADCIGs than in NMO-corrected CMPs. However In data space the multiple moveout is more intuitive (predictable)and easy to visualize. Delaying the multiple removal after imaging may compromise the choice of the migration velocities for the primaries. Alvarez-Biondi-Guitton
From model space to data space (ADCIGs): γ: aperture angle q: moveout curvature γa: apex-shift distance z, z’: depth Apex-shifted Radon Transform The transform is implemented as a least-squares inverse with a sparsity constraint. Alvarez-Biondi-Guitton
2D GOM seismic line CMP position 4000 24000 1000 Depth (m) 5000 Stack of migrated angle gathers Alvarez-Biondi-Guitton
ADCIGs Aperture-angle (degrees) Aperture-angle (degrees) -60 0 60 -60 0 60 1000 1000 Depth (m) Depth (m) 5000 5000 Sediments Below salt Alvarez-Biondi-Guitton
2D GOM seismic line CMP position 4000 24000 1000 Depth (m) 5000 Stack of migrated angle gathers Alvarez-Biondi-Guitton
Salt-edge ADCIGs Aperture-angle (degrees) Aperture-angle (degrees) -60 0 60 -60 0 60 1000 1000 Depth (m) Depth (m) 5000 5000 ADCIG1: Left edge ADCIG2: Right edge Alvarez-Biondi-Guitton
Comparison of Radon Transforms Curvature (m) Curvature (m) -400 0 2000 -400 0 2000 1000 1000 Primaries Depth (m) Depth (m) 5000 5000 2D transform γa=0 plane from 3D transform Alvarez-Biondi-Guitton
A look at the 3-D Radon cube Apex-shift (degrees) Apex-shift (degrees) Curvature (m) -30 0 30 -30 0 30 -400 0 2000 1000 Depth (m) 4000 plane q=0 plane q=1200 plane γa=10 Alvarez-Biondi-Guitton
Results of Multiple Attenuation Aperture-angle (degrees) Aperture-angle (degrees) -60 0 60 -60 0 60 1000 1000 Depth (m) Depth (m) 5000 5000 ADCIG1: Left edge ADCIG2: Right edge Alvarez-Biondi-Guitton
Primaries ADCIG 1 Aperture-angle (degrees) Aperture-angle (degrees) -40 0 40 -40 0 40 3200 3200 Depth (m) Depth (m) 5200 5200 standard transform apex-shifted transform Alvarez-Biondi-Guitton
Multiples ADCIG 1 Aperture-angle (degrees) Aperture-angle (degrees) -40 0 40 -40 0 40 3200 3200 Depth (m) Depth (m) 5200 5200 standard transform apex-shifted transform Alvarez-Biondi-Guitton
Discrimination of Multiples ADCIG 1 Aperture-angle (degrees) Aperture-angle (degrees) -40 0 40 -40 0 40 3200 3200 Depth (m) Depth (m) 5200 5200 Diffracted multiples S-R multiples Alvarez-Biondi-Guitton
Primaries ADCIG 2 Aperture-angle (degrees) Aperture-angle (degrees) -40 0 40 -40 0 40 3200 3200 Depth (m) Depth (m) 5200 5200 Standard transform Apex-shifted transform Alvarez-Biondi-Guitton
Multiples ADCIG 2 Aperture-angle (degrees) Aperture-angle (degrees) -40 0 40 -40 0 40 3200 3200 Depth (m) Depth (m) 5200 5200 Standard transform Apex-shifted transform Alvarez-Biondi-Guitton
2D GOM seismic line CMP position 4000 24000 1000 Depth (m) 5000 Stack of migrated angle gathers Alvarez-Biondi-Guitton
Primaries on Angle Stacks CMP position (m) 4000 10000 3000 Depth (m) 5000 3000 3D-RT Depth (m) 5000 3000 Diff Depth (m) 5000 2D-RT Alvarez-Biondi-Guitton
Multiples on Angle Stacks CMP position (m) 10000 4000 3000 2D-RT Depth (m) 5000 3000 3D-RT Depth (m) 5000 3000 Diff Depth (m) 5000 Alvarez-Biondi-Guitton
Conclusions The apex-shifted Radon transform is an effective way to attenuate diffracted multiples in the image space. The usual trade-off between multiple attenuation and primary preservation remains. Alvarez-Biondi-Guitton
Opportunities and challenges In 3D data, the apex-shift is a function of azimuth as well as aperture angle. We will takeadvantage of the development of 3D ADCIGs. The challenge is to handle the increased dimensionality of the problem. Alvarez-Biondi-Guitton
Thank you for your attention. I will be happy to entertain your questions. Alvarez-Biondi-Guitton
From model space to data space (ADCIGs): From data space to model space: γ: aperture angle γ: aperture angle q: moveout curvature q: moveout curvature h: apex-shift distance h: apex-shift distance z, z’: depth z, z’: depth Apex-shifted Radon Transform Alvarez-Biondi-Guitton
Constrained LS inversion Apex-shifted Radon transform: Objective Function: Cauchy regularization ε: controls level of sparsity in model space b: controls minimum value below which to zero out model space Alvarez-Biondi-Guitton