Abstract
Seismic interferometry comprises a suite of methods to redatum recorded wavefields to those that would have been recorded if different sources (so-called virtual sources) had been activated. Seismic interferometry by cross-correlation has been formulated using either two-way (for full wavefields) or one-way (for directionally decomposed wavefields) representation theorems. To obtain improved Green's function estimates, the cross-correlation result can be deconvolved by a quantity that identifies the smearing of the virtual source in space and time, the so-called point-spread function. This type of interferometry, known as interferometry by multidimensional deconvolution (MDD), has so far been applied only to one-way directionally decomposed fields, requiring accurate wavefield decomposition from dual (e.g. pressure and velocity) recordings. Here we propose a form of interferometry by multidimensional deconvolution that uses full wavefields with two-way representations, and simultaneously invert for pressure and (normal) velocity Green's functions, rather than only velocity responses as for its one-way counterpart. Tests on synthetic data show that two-way MDD improves on results of interferometry by cross-correlation, and generally produces estimates of similar quality to those obtained by one-way MDD, suggesting that the preliminary decomposition into up-and downgoing components of the pressure field is not required if pressure and velocity data are jointly used in the deconvolution. We also show that constraints on the directionality of the Green's functions sought can be added directly into the MDD inversion process to further improve two-way multidimensional deconvolution. Finally, as a by-product of having pressure and particle velocity measurements, we adapt one-and two-way representation theorems to convert any particle velocity receiver into its corresponding virtual dipole/gradient source by means of MDD. Thus data recorded from standard monopolar (e.g. marine) pressure sources can be converted into data from dipolar (derivative) sources at no extra acquisition cost.