A Comparison of Strategies for Seismic Interferometry

Snieder, Roel; Miyazawa, Masatoshi; Slob, Evert; Vasconcelos, Ivan; Wapenaar, Kees

doi:10.1007/s10712-009-9069-z

Cited by 108 publications

(48 citation statements)

References 99 publications

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“…This modified deconvolution method has been used to illuminate the San Andreas fault from the side using drill-bit noise ͑Figure 10͒ and for subsalt imaging from below using internal multiples ͑Vasconcelos et al, 2008͒. A comparison of crosscorrelation, deconvolution, and multidimensional deconvolution ͑presented in the next section͒ is given by Snieder et al ͑2009a͒.…”

Section: ͑32͒mentioning

confidence: 99%

Tutorial on seismic interferometry: Part 2 — Underlying theory and new advances

et al. 2010

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In the 1990s, the method of time-reversed acoustics was developed. This method exploits the fact that the acoustic wave equation for a lossless medium is invariant for time reversal. When ultrasonic responses recorded by piezoelectric transducers are reversed in time and fed simultaneously as source signals to the transducers, they focus at the position of the original source, even when the medium is very complex. In seismic interferometry the time-reversed responses are not physically sent into the earth, but they are convolved with other measured responses. The effect is essentially the same: The time-reversed signals focus and create a virtual source which radiates waves into the medium that are subsequently recorded by receivers. A mathematical derivation, based on reciprocity theory, formalizes this principle: The crosscorrelation of responses at two receivers, integrated over different sources, gives the Green's function emitted by a virtual source at the position of one of the receivers and observed by the other receiver. This Green's function representation for seismic interferometry is based on the assumption that the medium is lossless and nonmoving. Recent developments, circumventing these assumptions, include interferometric representations for attenuating and/or moving media, as well as unified representations for waves and diffusion phenomena, bending waves, quantum mechanical scattering, potential fields, elastodynamic, electromagnetic, poroelastic, and electroseismic waves. Significant improvements in the quality of the retrieved Green's functions have been obtained with interferometry by deconvolution. A trace-by-trace deconvolution process compensates for complex source functions and the attenuation of the medium. Interferometry by multidimensional deconvolution also compensates for the effects of one-sided and/or irregular illumination.

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Section: ͑32͒mentioning

confidence: 99%

Tutorial on seismic interferometry: Part 2 — Underlying theory and new advances

et al. 2010

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“…This principle has been successfully applied in the fields of ultrasonics [7], regional seismology [8,9,10,11], exploration seismic [12], underwater acoustics [13,14], and medical imaging [15]. For a review of the theory and the many applications see [16], [17], [18], and [19].…”

Section: Introductionmentioning

confidence: 99%

On the Retrieval of the Directional Scattering Matrix from Directional Noise

Wapenaar¹,

Thorbecke²

2013

SIAM J. Imaging Sci.

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Abstract. The crosscorrelation of ambient acoustic noise observed at two receivers yields the impulse response between these receivers, assuming that the noise field is diffuse. In practical situations the noise field exhibits directionality, which imprints the angle-dependent correlation function. For the situation of a directional scatterer in a directional noise field, the correlation function contains the product of the directional scattering matrix and the directional noise. This seemingly underdetermined problem can be resolved by exploiting a relation between the causal and acausal parts of the correlation function. For a given pair of receivers, the causal and acausal parts of the correlation function contain the same element of the scattering matrix (by reciprocity) but different elements of the directional noise field. This property can be used to estimate the directionality of the noise (apart from an undetermined scaling factor) and, subsequently, of the scattering matrix.

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“…These spurious events could also be investigated with the FD code, for example by not using a free surface. When intrinsic attenuation is present in the medium, one could use single-channel deconvolution to account for the losses (Snieder et al, 2009). When illumination issues are present, one could try to balance the amplitudes as proposed by Curtis and Halliday (2010).…”

Section: Discussionmentioning

confidence: 99%

Finite-difference modeling experiments for seismic interferometry

2011

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In passive seismic interferometry, new reflection data can be retrieved by crosscorrelating recorded noise data. The quality of the retrieved reflection data is, among others, dependent on the duration and number of passive sources present during the recording time, the source distribution, and the source strength. To investigate these relations we set up several numerical modeling studies. To carry out the modeling in a feasible time, we design a finite-difference algorithm for the simulation of long-duration passive seismic measurements of band-limited noise signatures in the subsurface. Novel features of the algorithm include the modeling of thousands of randomly placed sources during one modeling run. The modeling experiments explore the dependency relation between the retrieved reflections and source-signature length, source positions, number of sources, and source amplitude variations. From these experiments we observed that the positions of the passive sources and the length of the source signals are of direct influence on the quality of the retrieved reflections. Random amplitude variations among source signals do not seem to have a big impact on the retrieved reflections.

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A Comparison of Strategies for Seismic Interferometry

Cited by 108 publications

References 99 publications

Tutorial on seismic interferometry: Part 2 — Underlying theory and new advances

Tutorial on seismic interferometry: Part 2 — Underlying theory and new advances

On the Retrieval of the Directional Scattering Matrix from Directional Noise

Finite-difference modeling experiments for seismic interferometry

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