Vertical seismic profiling data can provide a high-resolution reservoir image because the receivers are located close to the reservoir and, hence, the wavefield encounters less distortion in the overburden compared to surface seismic data. However, conventional migration of vertical seismic profiling data using only upgoing primary wavefields often suffers from poor illumination, imaging artefacts and low image reliability, especially at image locations away from the well. We propose full-wavefield migration to image vertical seismic profiling data using the primaries and all orders of surface multiples and internal multiples. The downgoing internal or surface multiples are treated as an additional source of illumination. In full-wavefield migration, weaim to estimate a high-resolution reflectivity image of the subsurface with this extended illumination. The algorithm is recursive in depth like conventional wavefield extrapolation-based migration, however, it incorporates the non-linear transmission and scattering effects at each depth level. Further, full-wavefield migration is posed as a constrained least-squares inversion problem that could be solved using a conjugate gradient method. We propose an iterative full-wavefield forward modellingengine as the backbone of this inversion scheme. The parameter used in the modelling is subsurface reflectivity. Full-wavefield modelling iteratively incorporates thenon-linearity of the wavefield due to multiple scattering, where every iteration utilizes one higher order of scattered wavefields to estimate the subsurface reflectivity. In addition, the constrained inversion helps in reducing the extrapolation artefacts and provides a high-resolution image of the reservoir. In this paper, we discuss the concept of full-wavefield migration and demonstrate its potential as an imaging tool for vertical seismic profiling data using synthetic examples.