The next generation seismic migration and inversion technology considers multiple scattering as vital information, allowing the industry to derive significantly better reservoir models — with more detail and less uncertainty—while requiring a minimum of user intervention. Three new insights have been uncovered with respect to this fundamental transition. Unblended or blended multiple scattering can be included in the seismic migration process, and it has been proposed to formulate the imaging principle as a minimization problem. The resulting process yields angle-dependent reflectivity and is referred to as recursive full wavefield migration (WFM). The full waveform inversion process for velocity estimation can be extended to a recursive, optionally blended, anisotropic multiple-scattering algorithm. The resulting process yields angle-dependent velocity and is referred to as recursive full waveform inversion (WFI). The mathematical equations of WFM and WFI have an identical structure, but the physical meaning behind the expressions is fundamentally different. In WFM the reflection process is central, and the aim is to estimate reflection operators of the subsurface, using the up- and downgoing incident wavefields (including the codas) in each gridpoint. In WFI, however, the propagation process is central and the aim is to estimate velocity operators of the subsurface, using the total incident wavefield (sum of up- and downgoing) in each gridpoint. Angle-dependent reflectivity in WFM corresponds with angle-dependent velocity (anisotropy) in WFI. The algorithms of WFM and WFI could be joined into one automated joint migration-inversion process. In the resulting hybrid algorithm, being referred to as recursive joint migration inversion (JMI), the elaborate volume integral solution was replaced by an efficient alternative: WFM and WFI are alternately applied at each depth level, where WFM extrapolates the incident wavefields and WFI updates the velocities without any user interaction. The output of the JMI process offers an integrated picture of the subsurface in terms of angle-dependent reflectivity as well as anisotropic velocity. This two-fold output, reflectivity image and velocity model, offers new opportunities to extract accurate rock and pore properties at a fine reservoir scale.