Silva, R.U., De Basabe, J.D., Sen, M.K., Gonzalez-Escobar, M., Gomez-Trevifio, E. and Solorza-Calderén, S., 2020. Cooperative full waveform and gravimetric inversion. Journal of Seismic Exploration, 29: 549-573. There has been an increasing interest in recent years in the inversion of multiple geophysical data sets to obtain a consistent subsurface model for exploration and exploitation purposes. We employ cooperative inversion of gravity and seismic data for estimating a velocity and density model which fits observed data on the surface. This particular combination is motivated by the fact that the horizontal resolution of a model can be resolved by gravity inversion while the vertical resolution can be better estimated from the seismic data. We develop an iterative scheme based on full waveform inversion (FWD and petrophysical relations that minimizes the misfit between the observed and synthetic data measured at the surface for gravimetric stations and seismograms. Our algorithm exploits the benefits of each of the geophysical methods. It uses the adjoint- state method for the computation of the gradient needed for FWI and uses a constrained Conjugate Gradient Least Squares method for gravimetric inversion subject to the discrepancies between the density and the velocity models using petrophysical relationships between these properties. We tested our algorithm on three synthetic models: The first model isa Texas-shaped structure with a high-velocity region beneath 0963-065 1/20/$5.00 © 2020 Geophysical Press Ltd. 550 some horizontal layers with low velocities, the second example consists of a more complex version of the Texas-shaped model adding more heterogeneities and faults with the addition of random noise on the observed data, and the final model is a 3D example of cooperative gravimetric and full waveform inversion. In all the examples, we were able to fit the data and achieve iterative convergence, recovering the interface between layers and the top and shape of the higher-velocity body. The numerical examples demonstrate that the proposed method can be used to successfully combine gravimetric and seismic data sets to obtain a consistent subsurface model without incurring the computational cost of traditional joint-inversion methods.