Attenuation of free-surface multiples by up/down deconvolution for marine towed-streamer data

Majdański, Mariusz; Kostov, C.; Kragh, Ed; Moore, Ian D.; Thompson, Mark; Mispel, J.

doi:10.1190/geo2010-0337.1

Cited by 18 publications

(7 citation statements)

References 27 publications

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“…To fulfil all these requirements, we could use the output of inversion-based methods that are sometimes applied for freesurface multiple removal. We mention the Up/Down Deconvolution method of Amundsen et al (2001), its implementation for towedstreamer data (Majdanski et al 2011) and estimation of primaries by sparse inversion (Van Groenestijn & Verschuur 2009;Lin & Herrmann 2013). Unlike in the conventional surface-related multiple elimination methodology (Verschuur et al 1992), the source signature is deconvolved by these methods and the appropriate scaling of the output reflection response (as required by our scheme) is guaranteed.…”

Section: Discussionmentioning

confidence: 99%

On Green's function retrieval by iterative substitution of the coupled Marchenko equations

Neut¹,

Vasconcelos

Wapenaar³

2015

Geophys. J. Int.

117

114

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S U M M A R YIterative substitution of the coupled Marchenko equations is a novel methodology to retrieve the Green's functions from a source or receiver array at an acquisition surface to an arbitrary location in an acoustic medium. The methodology requires as input the single-sided reflection response at the acquisition surface and an initial focusing function, being the time-reversed direct wavefield from the acquisition surface to a specified location in the subsurface. We express the iterative scheme that is applied by this methodology explicitly as the successive actions of various linear operators, acting on an initial focusing function. These operators involve multidimensional crosscorrelations with the reflection data and truncations in time. We offer physical interpretations of the multidimensional crosscorrelations by subtracting traveltimes along common ray paths at the stationary points of the underlying integrals. This provides a clear understanding of how individual events are retrieved by the scheme. Our interpretation also exposes some of the scheme's limitations in terms of what can be retrieved in case of a finite recording aperture. Green's function retrieval is only successful if the relevant stationary points are sampled. As a consequence, internal multiples can only be retrieved at a subsurface location with a particular ray parameter if this location is illuminated by the direct wavefield with this specific ray parameter. Several assumptions are required to solve the Marchenko equations. We show that these assumptions are not always satisfied in arbitrary heterogeneous media, which can result in incomplete Green's function retrieval and the emergence of artefacts. Despite these limitations, accurate Green's functions can often be retrieved by the iterative scheme, which is highly relevant for seismic imaging and inversion of internal multiple reflections.

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Section: Discussionmentioning

confidence: 99%

On Green's function retrieval by iterative substitution of the coupled Marchenko equations

Neut¹,

Vasconcelos

Wapenaar³

2015

Geophys. J. Int.

117

114

View full text Add to dashboard Cite

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“…Free-surface related multiples generate particularly strong spurious structures in images though their removal is generally straightforward, and various methods are available for marine pressure streamer data (Verschuur, 1991(Verschuur, , 1992, ocean-bottom cable (OBC) and multicomponent marine steamer data (Ziolkowski et al, 1999;Amundsen, 2001;Majdański et al, 2011). The same is not true for internal multiples, which often require detailed subsurface information for their effective removal.…”

Section: Introductionmentioning

confidence: 99%

Elastic P- and S-wave autofocus imaging with primaries and internal multiples

2015

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Conventional seismic imaging methods rely on the single-scattering Born approximation, requiring the removal of multiply scattered events from reflection data prior to imaging. Additionally, many methods use an acoustic approximation, representing the solid Earth as an acoustic (fluid) medium. We propose imaging methods for (solid) elastic media that use primaries and internal multiples, including their P S and SP conversions, thus obviating the need for internal multiple removal and improving handling of internal conversions. The methods rely on the elastic autofocusing method which creates multi-component elastodynamic Green's functions from virtual sources interior to the medium to receivers placed on the surface. They require only surface seismic reflection data and estimates of the direct waves from virtual sources interior to the medium, both of which are commonly available at the imaging step of seismic processing. We demonstrate our methods on a synthetic model with constant P and S velocities and vertical and horizontal density variations, by producing for the first time P P and SS images from elastic autofocusing which are compared to 1 reference seismic images based on conventional methods. Effects of multiples are greatly attenuated in the images, with fewer spurious reflectors than are observed when using Born imaging.2

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“…Separation of recorded fields into downgoing and upgoing constituents is a technique that is used in many geophysical methods. Decomposed fields form the basis for various surface-related multiple elimination and deghosting procedures (e.g., Frijlink, Van Borselen, and Söellner 2011;Majdanski et al 2011) and for depth imaging using primary and multiple reflections (e.g., Muijs, Robertsson, and Holliger 2007). Novel methodologies that make use of horizontal downhole sensors, such as the virtual source method (e.g., Bakulin and Calvert 2006;Mehta et al 2007; and multi-dimensional deconvolution Wapenaar et al 2011, rely on decomposing the seismic field at depth.…”

Section: Introductionmentioning

confidence: 99%

Unified multi‐depth‐level field decomposition

Grobbe

Neut

Slob

et al. 2015

Geophysical Prospecting

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A B S T R A C TWavefield decomposition forms an important ingredient of various geophysical methods. An example of wavefield decomposition is the decomposition into upgoing and downgoing wavefields and simultaneous decomposition into different wave/field types. The multi-component field decomposition scheme makes use of the recordings of different field quantities (such as particle velocity and pressure). In practice, different recordings can be obscured by different sensor characteristics, requiring calibration with an unknown calibration factor. Not all field quantities required for multi-component field decomposition might be available, or they can suffer from different noise levels. The multi-depth-level decomposition approach makes use of field quantities recorded at multiple depth levels, e.g., two horizontal boreholes closely separated from each other, a combination of a single receiver array combined with free-surface boundary conditions, or acquisition geometries with a high-density of vertical boreholes. We theoretically describe the multi-depth-level decomposition approach in a unified form, showing that it can be applied to different kinds of fields in dissipative, inhomogeneous, anisotropic media, e.g., acoustic, electromagnetic, elastodynamic, poroelastic, and seismoelectric fields. We express the one-way fields at one depth level in terms of the observed fields at multiple depth levels, using extrapolation operators that are dependent on the medium parameters between the two depth levels. Lateral invariance at the depth level of decomposition allows us to carry out the multi-depth-level decomposition in the horizontal wavenumber-frequency domain. We illustrate the multi-depth-level decomposition scheme using two synthetic elastodynamic examples. The first example uses particle velocity recordings at two depth levels, whereas the second example combines recordings at one depth level with the Dirichlet free-surface boundary condition of zero traction. Comparison with multicomponent decomposed fields shows a perfect match in both amplitude and phase for both cases. The multi-depth-level decomposition scheme is fully customizable to the desired acquisition geometry. The decomposition problem is in principle an inverse problem. Notches may occur at certain frequencies, causing the multi-depth-level composition matrix to become uninvertible, requiring additional notch filters. We can add multi-depth-level free-surface boundary conditions as extra equations to the multi-component composition matrix, thereby overdetermining this inverse problem. The combined multi-component-multi-depth-level decomposition on a land data set clearly shows improvements in the decomposition results, compared with the performance of the multi-component decomposition scheme. *

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Attenuation of free-surface multiples by up/down deconvolution for marine towed-streamer data

Cited by 18 publications

References 27 publications

On Green's function retrieval by iterative substitution of the coupled Marchenko equations

On Green's function retrieval by iterative substitution of the coupled Marchenko equations

Elastic P- and S-wave autofocus imaging with primaries and internal multiples

Unified multi‐depth‐level field decomposition

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