Large-scale subsurface injection of has the potential to reduce emissions of atmospheric and improve oil recovery. Studying the effects of injected on the elastic properties of the saturated reservoir rock can help to improve long-term monitoring effectiveness and accuracy at locations undergoing injection. We used two vintages of existing 3D surface seismic data and well logs to probabilistically invert for the saturation and porosity at the Cranfield reservoir using a double-difference approach. The first step of this work was to calibrate the rock-physics model to the well-log data. Next, the baseline and time-lapse seismic data sets were inverted for acoustic impedance using a high-resolution basis pursuit inversion technique. The reservoir porosity was derived statistically from the rock-physics model based on the estimates inverted from the baseline survey. The porosity estimates were used in the double-difference routine as the fixed initial model from which saturation was then estimated from the time-lapse data. Porosity was assumed to remain constant between survey vintages; therefore, the changes between the baseline and time-lapse data may be inverted for saturation from the injection activities using the calibrated rock-physics model. Comparisons of inverted and measured porosity from well logs indicated quite accurate results. Estimates of saturation found less accuracy than the porosity estimates.