In this thesis the added value of gravity observations for hydrocarbon reservoir monitoring and characterization is investigated. Reservoir processes and reservoir types most suitable for gravimetric monitoring are identified. Major noise sources affecting time-lapse gravimetry are analyzed. The added value of gravity data for reservoir monitoring and characterization is analyzed within closed-loop reservoir management concept. Synthetic 2D and 3D numerical experiments are performed where various reservoir parameters, like permeability, porosity, reservoir structure, and aquifer characteristics, are updated using gravity and reservoir production data assimilation. The results show that history matching a gas field with pressure data only may provide highly non-unique solutions because several parameter combinations can explain the reservoir pressure behavior observed in the wells. Therefore, additional information is needed which can be provided by time-lapse gravimetry. It is demonstrated that a joint assimilation of pressure and gravity data can provide more constrained inverse solutions and result not only in improved gas and water production forecast, but also can give more accurate reservoir reserves evaluation and reservoir state description.