Crosscorrelations of seismic signals from both active and passive sources at the surface or in the subsurface can be used to reconstruct a valid model of the subsurface. Seismic interferometry can produce a result similar to traditional methods without limitations on the diffusivity of the wavefield or ambient sources. In a drilling application, it is possible to utilize a virtual source to image the subsurface adjacent to a downhole location. This application is increasingly utilized particularly for exploration in subsalt settings.
Seismic interferometry provides for the possibility of reconstructing the subsurface reflection response using the crosscorrelations of two seismic traces. Recent work has mathematically demonstrated applications of crosscorrelation for reconstructing Green's function using wave field reciprocity theorem in a lossless, 3D heterogeneous medium. Traces are most often extended records of passive background noise, but it is also possible to utilize active sources depending on the objective. Seismic interferometry essentially exploits the phase difference between adjacent receiver locations to image the subsurface.
The conditions for the method to be valid, meaning to retrieve the Green's function from correlated signals, are given as follows:
The last two conditions are hard to meet directly in nature. However, thanks to the wave scattering, the waves are converted, which satisfies the equipartition condition. The equal distribution of sources is met thanks to the fact, that the waves are scattered in every direction.
Seismic interferometry consists of simple crosscorrelation and stacking of actual receiver responses to approximate the impulse response as if a virtual source was placed at the location of the applicable receiver. Crosscorrelation of continuous functions in the time domain is presented as Equation 1.
(
f
1
∗
f
2
)
(
t
)
=
∫
f
1
(
λ
)
f
2
(
λ
−
t
)
d
λ
{\displaystyle (f_{1}*f_{2})(t)=\int f_{1}(\lambda )f_{2}(\lambda -t)d\lambda }
Where the functions are integrated as a function of time at different lag values. In fact, crosscorrelation can be understood conceptually as the traveltime lag associated with waveforms in two discrete receiver locations. Crosscorrelation is similar to convolution where the second function is folded relative to the first.
Where:
Intensity is related to the magnitude of the reflection coefficient (R) and the phase component ω(λAr+λrB). An estimate of the reflectivity distributions can be obtained through the crosscorrelation of the direct wave at a location A with the reflection recorded at a location B where A represents the reference trace. The multiplication of the conjugate of the trace spectrum at A and the trace spectrum at B gives:
ФAB =Re^iω(λAr+λrB) + o.t.
Where:
ФAB = product spectrum
o.t. = additional terms, e.g. correlations of direct-direct, etc. As in the previous case, the product spectrum is a function of phase.
Key: Changes in reflector geometry lead to changes in the correlation result and the reflector geometry can be recovered through the application of a migration kernel. Interpretation of raw interferograms is not normally attempted; crosscorrelated results are generally processed using some form of migration.
Ф(A, B) = −(Wiω)^2 Re^iω(λArλrB)+o.t.
The crosscorrelation of the direct wave at a location A with a ghost reflection at a location B removes the unknown source term where:
This form is equivalent to a virtual source configuration at a location A imaging hypothetical reflections at a location B. Migration of these correlation positions removes the phase term and yields a final migration image at position x where:
Where:
ø(A,B,t) = temporal correlation between locations A and B with lag time t
This model has been applied to simulate subsurface geometry in West Texas using simulated models including a traditional buried source and a synthetic (virtual) rotating drill bit source to produce similar results. A similar model demonstrated the reconstruction of a simulated subsurface geometry. In this case, the reconstructed subsurface response correctly modeled the relative positions of primaries and multiples. Additional equations can be derived to reconstruct signal geometries in a wide variety of cases.
Seismic interferometry is currently utilized primarily in research and academic settings. In one example, passive listening and the crosscorrelation of long noise traces was used to approximate the impulse response for shallow subsurface velocity analysis in Southern California. Seismic interferometry provided a result comparable to that indicated using elaborate inversion techniques. Seismic interferometry is most often used for the examination of the near surface and is
often utilized to reconstruct surface and direct waves only. As such, seismic interferometry is commonly used to estimate ground roll to aid in its removal. Seismic interferometry simplifies estimates of shear wave velocity and attenuation in a standing building. Seismic interferometry has been applied to image the seismic scattering and velocity structure of volcanoes.
Seismic interferometry applications are currently limited by a number of factors. Real world media and noise represent limitations for current theoretical development. For example, for interferometry to work noise sources must be uncorrelated and completely surround the region of interest. In addition, attenuation and geometrical spreading are largely neglected and need to be incorporated into more robust models. Other challenges are inherent to seismic interferometry. For example, the source term only drops out in the case of the crosscorrelation of a direct wave at a location A with a ghost reflection at a location B. The correlation of other waveforms can introduce multiples to the resulting interferogram. Velocity analysis and filtering can reduce but not eliminate the occurrence of multiples in a given dataset.
Although there have been many advancements in seismic interferometry challenges still remain. One of the biggest remaining challenges is extending the theory to account for real world media and noise distributions in the subsurface. Natural sources typically do not comply with mathematical generalizations and may in fact display some degree of correlation. Additional problems must be addressed before applications of seismic interferometry can become more widespread.
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Curtis et al. 2006 - Curtis, A.; Gerstoft, P.; Sato, H.; Snieder, R.; Wapenaar, K. (2006). "Seismic interferometry turning noise into signal". The Leading Edge. 25 (9): 1082–1092. Bibcode:2006LeaEd..25.1082C. doi:10.1190/1.2349814. http://resolver.tudelft.nl/uuid:bc099609-47bd-4ad8-91ad-2a4a9a949c0f
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Wapenaar 2004 harvnb error: no target: CITEREFWapenaar2004 (help)
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Wapenaar & Fokkema 2006 harvnb error: no target: CITEREFWapenaarFokkema2006 (help)
Curtis et al. 2006 - Curtis, A.; Gerstoft, P.; Sato, H.; Snieder, R.; Wapenaar, K. (2006). "Seismic interferometry turning noise into signal". The Leading Edge. 25 (9): 1082–1092. Bibcode:2006LeaEd..25.1082C. doi:10.1190/1.2349814. http://resolver.tudelft.nl/uuid:bc099609-47bd-4ad8-91ad-2a4a9a949c0f
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Larose, Eric; Carrière, Simon; Voisin, Christophe; Bottelin, Pierre; Baillet, Laurent; Guéguen, Philippe; Walter, Fabian; Jongmans, Denis; Guillier, Bertrand; Garambois, Stéphane; Gimbert, Florent (2015-05-01). "Environmental seismology: What can we learn on earth surface processes with ambient noise?". Journal of Applied Geophysics. 116: 62–74. Bibcode:2015JAG...116...62L. doi:10.1016/j.jappgeo.2015.02.001. ISSN 0926-9851. https://www.sciencedirect.com/science/article/pii/S0926985115000403
Curtis et al. 2006 - Curtis, A.; Gerstoft, P.; Sato, H.; Snieder, R.; Wapenaar, K. (2006). "Seismic interferometry turning noise into signal". The Leading Edge. 25 (9): 1082–1092. Bibcode:2006LeaEd..25.1082C. doi:10.1190/1.2349814. http://resolver.tudelft.nl/uuid:bc099609-47bd-4ad8-91ad-2a4a9a949c0f
Animation http://mathworld.wolfram.com/Convolution.html
Draganov, Wapenaar & Thorbecke 2006 - Draganov, D.; Wapenaar, K.; Thorbecke, J. (2006). "Seismic interferometry: Reconstructing the earth's reflection response". Geophysics. 71 (4): SI61 – SI70. Bibcode:2006Geop...71SI.61D. CiteSeerX 10.1.1.75.113. doi:10.1190/1.2209947. https://ui.adsabs.harvard.edu/abs/2006Geop...71SI.61D
Wapenaar & Fokkema 2006 harvnb error: no target: CITEREFWapenaarFokkema2006 (help)
Schuster et al. 2004 - Schuster, G.; Yu, J.; Sheng, J.; Rickett, J. (2004). "Interferometric/daylight seismic imaging". Geophysical Journal International. 157 (2): 838–852. Bibcode:2004GeoJI.157..838S. doi:10.1111/j.1365-246x.2004.02251.x. https://doi.org/10.1111%2Fj.1365-246x.2004.02251.x
Curtis et al. 2006 - Curtis, A.; Gerstoft, P.; Sato, H.; Snieder, R.; Wapenaar, K. (2006). "Seismic interferometry turning noise into signal". The Leading Edge. 25 (9): 1082–1092. Bibcode:2006LeaEd..25.1082C. doi:10.1190/1.2349814. http://resolver.tudelft.nl/uuid:bc099609-47bd-4ad8-91ad-2a4a9a949c0f
Schuster et al. 2004 - Schuster, G.; Yu, J.; Sheng, J.; Rickett, J. (2004). "Interferometric/daylight seismic imaging". Geophysical Journal International. 157 (2): 838–852. Bibcode:2004GeoJI.157..838S. doi:10.1111/j.1365-246x.2004.02251.x. https://doi.org/10.1111%2Fj.1365-246x.2004.02251.x
Schuster et al. 2004 - Schuster, G.; Yu, J.; Sheng, J.; Rickett, J. (2004). "Interferometric/daylight seismic imaging". Geophysical Journal International. 157 (2): 838–852. Bibcode:2004GeoJI.157..838S. doi:10.1111/j.1365-246x.2004.02251.x. https://doi.org/10.1111%2Fj.1365-246x.2004.02251.x
Schuster et al. 2004 - Schuster, G.; Yu, J.; Sheng, J.; Rickett, J. (2004). "Interferometric/daylight seismic imaging". Geophysical Journal International. 157 (2): 838–852. Bibcode:2004GeoJI.157..838S. doi:10.1111/j.1365-246x.2004.02251.x. https://doi.org/10.1111%2Fj.1365-246x.2004.02251.x
Schuster et al. 2004 - Schuster, G.; Yu, J.; Sheng, J.; Rickett, J. (2004). "Interferometric/daylight seismic imaging". Geophysical Journal International. 157 (2): 838–852. Bibcode:2004GeoJI.157..838S. doi:10.1111/j.1365-246x.2004.02251.x. https://doi.org/10.1111%2Fj.1365-246x.2004.02251.x
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Snieder & Safak 2006 harvnb error: no target: CITEREFSniederSafak2006 (help)
Chaput et al., 2012
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Curtis et al. 2006 - Curtis, A.; Gerstoft, P.; Sato, H.; Snieder, R.; Wapenaar, K. (2006). "Seismic interferometry turning noise into signal". The Leading Edge. 25 (9): 1082–1092. Bibcode:2006LeaEd..25.1082C. doi:10.1190/1.2349814. http://resolver.tudelft.nl/uuid:bc099609-47bd-4ad8-91ad-2a4a9a949c0f
Curtis et al. 2006 - Curtis, A.; Gerstoft, P.; Sato, H.; Snieder, R.; Wapenaar, K. (2006). "Seismic interferometry turning noise into signal". The Leading Edge. 25 (9): 1082–1092. Bibcode:2006LeaEd..25.1082C. doi:10.1190/1.2349814. http://resolver.tudelft.nl/uuid:bc099609-47bd-4ad8-91ad-2a4a9a949c0f
Schuster et al. 2004 - Schuster, G.; Yu, J.; Sheng, J.; Rickett, J. (2004). "Interferometric/daylight seismic imaging". Geophysical Journal International. 157 (2): 838–852. Bibcode:2004GeoJI.157..838S. doi:10.1111/j.1365-246x.2004.02251.x. https://doi.org/10.1111%2Fj.1365-246x.2004.02251.x
Curtis et al. 2006 - Curtis, A.; Gerstoft, P.; Sato, H.; Snieder, R.; Wapenaar, K. (2006). "Seismic interferometry turning noise into signal". The Leading Edge. 25 (9): 1082–1092. Bibcode:2006LeaEd..25.1082C. doi:10.1190/1.2349814. http://resolver.tudelft.nl/uuid:bc099609-47bd-4ad8-91ad-2a4a9a949c0f