Source-receiver wave field interferometry

Curtis, Andrew; Halliday, David

doi:10.1103/physreve.81.046601

Cited by 101 publications

(76 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Because Marchenko imaging involves redatuming of sources as well as receivers, it has an interesting relation with source-receiver interferometry, as proposed by Curtis and Halliday (2010) and Halliday and Curtis (2010). We analyze this relation for the Marchenko scheme for imaging from below.…”

Section: Comparison With Source-receiver Interferometrymentioning

confidence: 99%

“…Instead of selecting only the zero-offset, zero-time component R ∪ ðx i ; x i ; 0Þ, the full reflection response R ∪ ðx i ; x 0 i ; tÞ can be used to derive the angle-dependent reflectivity at each image point (de Bruin et al, 1990;Sava and Fomel, 2003). This information can be used as input for amplitude-versus-angle inversion to determine the detailed medium parameters in the target zone.…”

Section: Imaging From Abovementioning

confidence: 99%

See 1 more Smart Citation

Marchenko imaging

et al. 2014

View full text Add to dashboard Cite

Traditionally, the Marchenko equation forms a basis for 1D inverse scattering problems. A 3D extension of the Marchenko equation enables the retrieval of the Green’s response to a virtual source in the subsurface from reflection measurements at the earth’s surface. This constitutes an important step beyond seismic interferometry. Whereas seismic interferometry requires a receiver at the position of the virtual source, for the Marchenko scheme it suffices to have sources and receivers at the surface only. The underlying assumptions are that the medium is lossless and that an estimate of the direct arrivals of the Green’s function is available. The Green’s function retrieved with the 3D Marchenko scheme contains accurate internal multiples of the inhomogeneous subsurface. Using source-receiver reciprocity, the retrieved Green’s function can be interpreted as the response to sources at the surface, observed by a virtual receiver in the subsurface. By decomposing the 3D Marchenko equation, the response at the virtual receiver can be decomposed into a downgoing field and an upgoing field. By deconvolving the retrieved upgoing field with the downgoing field, a reflection response is obtained, with virtual sources and virtual receivers in the subsurface. This redatumed reflection response is free of spurious events related to internal multiples in the overburden. The redatumed reflection response forms the basis for obtaining an image of a target zone. An important feature is that spurious reflections in the target zone are suppressed, without the need to resolve first the reflection properties of the overburden.

show abstract

Section: Comparison With Source-receiver Interferometrymentioning

confidence: 99%

Section: Imaging From Abovementioning

confidence: 99%

Marchenko imaging

et al. 2014

View full text Add to dashboard Cite

show abstract

“…The source and receiver in the surface survery data are denoted as s and r. Using a similar approach as Poliannikov (2010) under the framework of SRI (Curtis and Halliday, 2010), an equation for retrieving the reflections from above the sources can be written as…”

Section: Theorymentioning

confidence: 99%

“…Liu et al (2013) show a numerical example of this type of interferometry, implemented as interferometry by multidimensional deconvolution (MDD). Curtis and Halliday (2010) propose SRI to construct the wavefield between a source and a receiver using recordings to or from the two surrounding boundaries. It allows one to incorporate the more conventional seismic data for use in interferometry.…”

Section: Introductionmentioning

confidence: 99%

Combining inter-source seismic interferometry and source-receiver interferometry for deep local imaging

Liu¹,

Arntsen²,

Wapenaar³

et al. 2014

SEG Technical Program Expanded Abstracts 2014

View full text Add to dashboard Cite

SummaryThe virtual source method has been applied successfully to retrieve the impulse response between pairs of receivers in the subsurface. This method is further improved by an updown separation prior to the crosscorrelation to suppress the reflections from the overburden and the free surface. In a reversed situation where the sources are in the subsurface and receivers are on the surface, in principle, one can apply the same logic to retrieve the virtual response between pairs of sources by source-receiver reciprocity, turning the physical borehole sources into virtual receivers. However, since the up-down separation is not applicable on the source side, the simple crosscorrelation of the total fields results in spurious events due to the incomplete receiver coverage around the sources. We show with a numerical example that for this configuration of borehole sources and surface receivers, one can replace such an updown separation at the source side by that of the direct and reflected waves as a first order approximation. This procedure produces the virtual receiver data that is adequate for local imaging below the source depth and is completely independent of the accuracy of the overburden velocity model. We implement this inter-source type of interferometry by multidimensional deconvolution (MDD). Further, if the conventional surface survey data is available, we test the methodology from source-receiver interferometry (SRI) for this reverse configuration with borehole sources to retrieve the virtual receiver data with reflections coming from above, using also only the separation of the direct and reflected waves. By migrating the two sets of virtual receiver data, one can create a local image around the borehole sources in a deep area with better focusing and localization without a sophisticated velocity model.

show abstract

“…But the SI process can also be applied to retrieve the Green's function between two sources or between a source and receiver, where the receiver has not recorded the signal from that source (so-called source-receiver interferometry, Curtis and Halliday, 2010).…”

Section: Introductionmentioning

confidence: 99%

Retrieval of reflections from ambient noise recorded in the Mizil area, Romania

et al. 2014

View full text Add to dashboard Cite

We applied seismic interferometry (SI) by crosscorrelation to ambient-noise panels recorded in the Mizil area, Romania, aiming to retrieve body-wave reflections. To achieve this goal, surface waves in the noise panels input to SI should be suppressed. We did this by selecting for input to SI-only noise panels that are not dominated by surface waves; the selection was either after visual inspection in the time domain or after automatic slowness evaluation on crosscorrelated panels. The latter used the slowness of arrivals passing through the virtual-source position at time 0 s. We discovered that the automatic slowness-evaluation method allows better retrieval of reflections. From the retrieved reflection gathers, we obtained stacked images of the subsurface. Comparing the SI images to a stacked image from active-source data, we concluded that some retrieved events correspond to reflectors in the active seismic section, including known geologic markers. In a previous application of SI to ambient noise, the retrieved reflections exhibited frequency content lower than that of active data. In our results, the frequency content of the SI retrieved data was comparable to the one of the active data.

show abstract

Source-receiver wave field interferometry

Cited by 101 publications

References 30 publications

Marchenko imaging

Marchenko imaging

Combining inter-source seismic interferometry and source-receiver interferometry for deep local imaging

Retrieval of reflections from ambient noise recorded in the Mizil area, Romania

Contact Info

Product

Resources

About