Interferometric imaging condition for wave-equation migration |
Paul Sava (Colorado School of Mines)
and
Oleg Poliannikov (Massachusetts Institute of Technology)
There are two possible ways to address this problem: improve wavefield reconstruction by estimating more accurate velocity models and image using conventional techniques (e.g. wavefield cross-correlation), or reconstruct wavefields with conventional methods using the known background velocity model, but improve the imaging condition to alleviate the artifacts caused by the imprecise reconstruction, which is what we suggest in this paper.
We describe the unknown component of the velocity model as a random function with local spatial correlations. Imaging data perturbed by such random variations is characterized by statistical instability, i.e. various wavefield components image at wrong locations that depend on the actual realization of the random model. Statistical stability can be achieved by pre-processing the reconstructed wavefields prior to the imaging condition. We employ Wigner distribution functions to attenuate the random noise present in the reconstructed wavefields, parametrized as a function of image coordinates. Wavefield filtering using Wigner distribution functions and conventional imaging can be lumped-together into a new form of imaging condition which we call an ``interferometric imaging condition'' due to its similarity to concepts from recent work on interferometry. The interferometric imaging condition can be formulated both for zero-offset and for multi-offset data, leading to robust and efficient imaging procedures that are effective in attenuating imaging artifacts due to unknown velocity models.
Interferometric imaging condition for wave-equation migration |