Interferometric/daylight seismic imaging

Abstract

S U M M A R YClaerbout's daylight imaging concept is generalized to a theory of interferometric seismic imaging (II). Interferometric seismic imaging is defined to be any algorithm that inverts correlated seismic data for the reflectivity or source distribution. As examples, we show that II can image reflectivity distributions by migrating ghost reflections in passive seismic data and generalizes the receiver-function imaging method used by seismologists. Interferometric seismic imaging can also migrate free-surface multiples in common depth point (CDP) data and image source distributions from passive seismic data. Both synthetic and field data examples are used to illustrate the different possibilities of II. The key advantage of II is that it can image source locations or reflectivity distributions from passive seismic data where the source position or wavelet is unknown. In some cases it can mitigate defocusing errors as a result of statics or an incorrect migration velocity. The main drawback with II is that severe migration artefacts can be created by partial focusing of virtual multiples.

Retrieving the Green's Function From Cross Correlation in a Bianisotropic Medium

“…The points x A and x B are chosen in D and both states have the same medium parameterŝ M A =M B =M. With these choices the correlation type Green's matrix representation is given bŷ (8) where the contrast functionM is Hermitian and given by…”

“…Draganov et al [7] retrieved seismic subsurface reflections from noise records. Schuster et al [8] and Snieder [9] showed with stationary phase theory how not all sources on the boundary play an equally important role, but only those that are stationary for the resulting event. Wapenaar [10] showed that the elastodynamic response of an arbitrary heterogeneous elastic half space can be retrieved from contributions of sources in the subsurface below a pressure free surface.…”

Green's function retrieval by cross‐correlation in case of one‐sided illumination

“…Various theories have been developed to explain this phenomenon, ranging from diffusion theory for enclosures [Weaver and Lobkis, 2001], multiple scattering theory and stationary-phase theory for random media [Malcolm et al, 2004;Snieder, 2004] and reciprocity theory for deterministic and random media [Wapenaar, 2004;Weaver and Lobkis, 2004;van Manen et al, 2005]. The principle of recovering an acoustic response by cross-correlation is often called Green's function retrieval; in the geophysical literature it is also known as seismic interferometry [Schuster et al, 2004;Wapenaar and Fokkema, 2006;Snieder et al, 2006].…”

“…This type of configuration occurs for example in exploration seismology, where the sources are located at the earth's surface only. For this configuration cross-correlation methods have been developed by Schuster et al [2004] as a method for seismic imaging, by Bakulin and Calvert [2004] for Green's function retrieval and by Verschuur and Berkhout [2005] for transforming surface related multiples into primaries. Impressive results have been obtained by these authors for ballistic waves, but the coda due to internal multiple scattering was not considered.…”

Estimation of primaries by sparse inversion from passive seismic data

“…Instead, passive sources are used such as mini earthquakes within the subsurface of the earth ͑for example, from reservoir rocks cracking due to fluid-pressure changes during production͒ or heavy traffic on the surface. We will compare the passive data model with the primary-multiple model and demonstrate that crosscorrelating data, as is usually done in seismic interferometry ͑see, e.g., Claerbout, 1968;Schuster, 2001;Shapiro and Campillo, 2004;Wapenaar, 2004;Wapenaar et al, 2004;Snieder et al, 2006;Dellinger and Yu, 2009;Draganov et al, 2009͒, is only the first step in a modified version of the recently introduced estimation of primaries by sparse inversion ͑EPSI͒ method ͑van Groenestijn and Verschuur, 2009a͒. A framework to describe active and passive seismic data ͑Berkhout and Verschuur, 2009͒ proposes to find the primary impulse responses via an inversion method.…”