Broadband Extended Images by Joint Deconvolution of Multiple Blended Wavefields

We propose a method for inversion of subsurface reflectivity image gathers that jointly relies on the broadband nature of combining multiple wavefields with diverse temporal and spatial spectra. Our inversion retrieves depth-domain extended images (EIs), which represent the full reflectivity operators within the subsurface. Based on interferometry by multidimensional deconvolution (MDD), we present MDD-based imaging conditions for an extended-image inversion. Our method consists of deconvolving correlation-based EIs with the so-called joint point-spread function (JPSF). This method can account for imaging primaries as well as internal and free-surface multiples. Because it is based on MDD, our JPSF approach can account for blended/simultaneous-source data in imaging with no need to separate the simultaneous-source data prior to imaging. With the example dual-source vector-acoustic seismic data the extended-image JPSF system is constructed by separating source and receiver wavefields from upgoing and ghost data, from both pressure and gradient sources. We demonstrate how the method inverts for EIs representing subsurface reflectivity, while benefiting from the increase in temporal and spatial bandwidth brought on by dual-source multimeasurement data. In addition, our joint wavefield approach provides a framework for jointly imaging data from multiple experiments of any kind (e.g., surface and borehole, active and passive).