Optimizing and enhancing oil recovery is a key focus for the oil and gas industry. For economic success, good reservoir formation knowledge is important to optimize oil & gas extraction over the course of production time. Reservoir history matching plays a crucial role in the incorporation of production and logging data for efficiently forecasting the development of reservoirs and its depletion. While production and logging data have been readily incorporated, sparse spatial sampling of these data may yield insufficient information about the formation structure to accurately history match for large reservoirs such as Ghawar. InSAR (Interferometric Synthetic Aperture Radar) has revolutionized the way to measure the Earth's surface deformation and has been successfully and economically utilized for studying large surface deformation caused by hydrocarbon extraction (such as commercialized by Halliburton). Surface displacement is primarily caused by changes in the pressure level within the subsurface reservoirs that lead to an up-or downlift of the subsurface. With fluids travelling from high into low pressure environments, InSAR measurements can be used to forecast fluid displacements. We have developed an InSAR based history matching framework for oil & gas reservoirs that efficiently incorporates InSAR data for improved reservoir management and forecasts. Our numerical results suggest that InSAR data provide important information about the reservoir state which can be exploited to enhance the forecasting for large scale reservoirs.