Introduction to Multiple Attenuation Methods
GP 210 Basic Earth Imaging
Dec 5th, 2012
Prepared by Mandy Wong
Introduction Types of multiples
Multiple removal methods 1. Predictive Deconvolution 2. Fk filtering 3. Hyperbolic Radon filtering 4. Surface-related multiple elimination (SRME)
Summary
Overview
Introduction • Multiples are seismic arrival that have more than one reflections or scattering • There are many types of multiples with special names
(3) Mirror signal • A type of receiver ghost that involves ocean bottom receiver • It can easily be used as signal
(5) Water-column reverberations
• a class of surface-related multiples • Reflections only between the sea-surface and the seabed.
(7) Peg-leg multiples • A multiple reflection involving successive reflection at different interfaces so that its travel path is not symmetric
1. Predictive Deconvolution 2. F-k filtering 3. Parabolic Radon Transform 4. Surface-related multiple elimination
(SRME)
Multiple removal methods
Predictive Deconvolution • Remove short-period multiples (most notably from relatively flat, shallow water-bottom) • The periodicity of the multiples is exploited to design a filter that removes the predictable part of the wavelet (multiples), leaving only its non-predictable part (signal)
After prediction decon Zero-offset gather
Predictive Deconvolution
After prediction decon Zero-offset gather
To suppress multiples choose a lag corresponding to the two-way travel-time of the multiples
Predictive Deconvolution
Pros Cons
• Computationally affordable • Good for shallow water reverberation
• 1D model • For dipping reflector, multiples are not periodic
Fk-filtering
CMP gather from Lab 5
Primaries and multiples exhibit different hyperbolic moveout in CMPs
Fk-filtering
CMP gather from Lab 5
Primaries and multiples exhibit different hyperbolic moveout in CMPs
Which one is primary? And multiple?
NMO with the Vrms of the primaries
Fk-filtering NMO with the Vrms between the
primaries and the multiples
Fk-filtering
Pros Cons
• Computationally affordable • Good for simple subsurface
• Fail at near offset • Insufficient for complex subsurface • Require velocity model
Radon Transform
Pros Cons
• Computationally affordable • Good for simple subsurface
• Insufficient for complex subsurface • Require velocity model
Surface Related Multiple Elimination (SRME)
X1
X2
X1*X2 (convolution): predict multiples of path S1-R1-R2
Surface Related Multiple Elimination (SRME)
A C
Verschuur (2009)
To estimate the multiples coming from point A to C, convolve the following • common shot gather (shot at A) • common receiver gather (receiver at B) And then sum all the contributions
Surface Related Multiple Elimination (SRME)
Verschuur (2009)
To estimate the multiples coming from point A to C, convolve the following • common shot gather (shot at A) • common receiver gather (receiver at B) And then sum all the contributions
Surface Related Multiple Elimination (SRME) To estimate the multiples coming from point A to C, convolve the following • common shot gather (shot at A) • common receiver gather (receiver at B) And then sum all the contributions
Verschuur (2009)
Figure 5:Surface bounce lie outside of acquisition geometry.
Surface Related Multiple Elimination (SRME)
Pros Cons
• Require no subsurface info • Can eliminate complex surface-related multiples
• Require dense and regular acquisition geometry
Surface Related Multiple Elimination (SRME)
Summary Methods Pros Cons Predictive Deconvolution
Computationally affordable Good for shallow water reverberation
1D model For dipping reflector, not periodic
F‐k Filtering ‐Computationally affordable ‐ Good for simple subsurface
Fail at near offset Insufficient for complex subsurface Require velocity model
Radon Transform ‐Computationally affordable ‐ Good for simple subsurface
Insufficient for complex subsurface Require velocity model
Surface Related Multiple Elimination (SRME)
Require no subsurface info Effectively converging
Require dense and regular acquisition geometry.
References
Alvarez G F, Attenuation of Multiples in Image Space, PhD Thesis, Stanford University, 2007 (Figure 5)
Cao Z.H., Analysis and Application of Radon Transform, MSc Thesis, Univ of Calgary, 2006 (Figure 1, 4)
Peacock K L and Treitel S, Predictive Deconvolution: Theory and Practice, Geophysics, 34 (1969) (Figure 3)
Verschuur, D. J., Berkhout, A. J. and Wapenaar, C. P. A., Adaptive surface-related multiple elimination, Geophysics, 57, 1166-1177, 1992
Weglein A B, Multiple attenuation: an overview of recent advances and the road ahead, The Leading Edge, 18 (1999), 40-44