Crossline wavefield reconstruction from multicomponent streamer data: Part 1 — Multichannel interpolation by matching pursuit (MIMAP) using pressure and its crossline gradient

Vassallo, Massimiliano; Özbek, Ali; Özdemir, Kemal; Eggenberger, Kurt

doi:10.1190/1.3496958

Cited by 103 publications

(47 citation statements)

References 19 publications

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“…Equation [13] is a 'sinc interpolation formula' for a multicomponent streamer (recording a minimum of pressure and crossline components of particle velocity, the latter being simply obtained by integrating the acceleration). Vassallo et al (2010) presented an interpolation algorithm for multicomponent data (pressure and particle acceleration recordings) based on a basis function expansion (a so-called matching pursuit algorithm) that in combination with a linearity assumption, similar to what was proposed by Spitz (1991), provides a powerful engine for dealiasing multicomponent streamer data. In particular, note the factor ½ that occurs with every factor s in eqn [13] compared to eqn [11].…”

Section: Receiver-side Techniquesmentioning

confidence: 99%

Tools and Techniques: Marine Seismic Methods

Robertsson

Laws²,

Kragh³

2015

Treatise on Geophysics

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Section: Receiver-side Techniquesmentioning

confidence: 99%

Tools and Techniques: Marine Seismic Methods

Robertsson

Laws²,

Kragh³

2015

Treatise on Geophysics

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“…We focus on relatively simple approaches to processing dual-sensor towed streamer data to illustrate the underlying signal processing issues that must be overcome for realistic acquisition geometries. The same physical principles have been used to develop inversion-based approaches to deghosting and data reconstruction that additionally take advantage of recorded crossline particle motion data Özdemir et al, 2010;Vassallo et al, 2010), but these methods will not be discussed in this paper. We show how the data may be used to separate the recorded wavefield into its up-and downgoing parts, thereby allowing the receiver-side ghost to be distinguished from the upgoing scattered energy.…”

Section: Introductionmentioning

confidence: 97%

Wavefield-separation methods for dual-sensor towed-streamer data

et al. 2013

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A dual-sensor towed streamer records the pressure and vertical component of particle motion associated with the incident wavefield that may be used to separate the wavefield into its upand downgoing parts. This procedure requires information about the water properties (wave-propagation velocity and density) and is robust in the presence of errors in the estimation of these quantities of the magnitude likely to be encountered. In practice, the particle motion data recorded by current towed marine streamers encounter very strong mechanical noise such that, for the lowest frequencies, the wavefield separation must be approximated by deconvolving the ghost function from the pressure data. This procedure requires information about the streamer depth and is robust to small depth errors over the frequency range for which it is required for dual-sensor streamer processing, but it is much more sensitive if applied over the bandwidth necessary to deghost pressure data acquired at a conventional streamer depth. The signal-to-noise ratio can be further enhanced by recombining the up-and downgoing pressure fields at the sea surface, which has the effect of applying a ghostlike filter to noise that is recorded by only one of the two sensors. In practical marine acquisition scenarios, spatial sampling is often insufficient to yield an accurate result, especially in the crossline direction. If each streamer is processed independently assuming that the wavefield propagation is purely inline, significant errors can be introduced. For arrivals with high emergent angles, errors may also be introduced even if the wavefield propagation actually is purely inline due to incorrect treatment of spatially aliased energy. However, these effects are almost entirely confined to very shallow events. They can be mitigated by using independently derived information about the crossline propagation angle and, for data comprising predominantly forward scattered energy, appropriate application of linear moveout.

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“…In recent years, acquisition technology has seen rapid improvements with the introduction of dual-field acoustic systems. Initially deployed as a combination of pressure sensors with single component (vertical) velocity/acceleration measurements (Cambois et al, 2009) or vertical derivatives of pressure from "over-under" acquisition, seismic streamer technology is now able to combine pressure and multicomponent gradient/acceleration observations (Robertsson et al, 2008;Vassallo et al, 2010). In parallel to sensor technology, dual-source technology now combines pressure with gradient/ dipole marine sources (Robertsson et al, 2012).…”

Section: Introductionmentioning

confidence: 98%

Source-receiver, reverse-time imaging of dual-source, vector-acoustic seismic data

Vasconcelos

2013

GEOPHYSICS

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Novel technologies in seismic data acquisition allow for recording full vector-acoustic (VA) data: pointwise recordings of pressure and its multicomponent gradient, excited by pressure only as well as dipole/gradient sources. Building on recent connections between imaging and seismic interferometry, we present a wave-equation-based, nonlinear, reverse-time imaging approach that takes full advantage of dual-source multicomponent data. The method's formulation relies on source-receiver scattering reciprocity, thus making proper use of VA fields in the wavefield extrapolation and imaging condition steps in a self-consistent manner. The VA imaging method is capable of simultaneously focusing energy from all in-and outgoing waves: The receiver-side up-and downgoing (receiver ghosts) fields are handled by the VA receiver extrapolation, whereas source-side in-and outgoing (source ghosts) arrivals are accounted for when combining dual-source data at the imaging condition. Additionally, VA imaging handles image amplitudes better than conventional reverse-time migration because it properly handles finite-aperture directivity directly from dual-source, 4C data. For nonlinear imaging, we provide a complete source-receiver framework that relies only on surface integrals, thus being computationally applicable to practical problems. The nonlinear image can be implicitly interpreted as a superposition of several nonlinear interactions between scattering components of data with those corresponding to the extrapolators (i.e., to the model). We demonstrate various features of the method using synthetic examples with complex subsurface features. The numerical results show, e.g., that the dual-source, VA image retrieves subsurface features with "super-resolution", i.e., with resolution higher than the limits of Born imaging, but at the cost of introducing image artifacts not present in the linear image. Although the method does not require any deghosting as a preprocessing step, it can use separated up-and downgoing fields to generate independent subsurface images.

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Crossline wavefield reconstruction from multicomponent streamer data: Part 1 — Multichannel interpolation by matching pursuit (MIMAP) using pressure and its crossline gradient

Cited by 103 publications

References 19 publications

Tools and Techniques: Marine Seismic Methods

Tools and Techniques: Marine Seismic Methods

Wavefield-separation methods for dual-sensor towed-streamer data

Source-receiver, reverse-time imaging of dual-source, vector-acoustic seismic data

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