Studying how injected affects the seismic response of reservoir rocks is important because it can improve subsurface characterization where injection is taking place. This study uses multicomponent data from a 3D vertical seismic profile (VSP) and well logs to model and invert probabilistically for the porosity and saturation at the Cranfield reservoir. The well logs were used to calibrate a rock-physics model. Once the accuracy of the model was verified, P-impedance and / from inverted multicomponent VSP data were used to estimate the porosity and fluid saturation. This inversion generated probabilistic estimates of porosity and fluid saturation for the area of the reservoir sampled by PP- and PS-waves. Inversion results using the measured well log data for calibration indicated that the model was able to estimate porosity with a relatively high degree of accuracy, with the root-mean-square (rms) error being less than 3% for all calibration tests. Pore-fluid composition was estimated, however, with reduced accuracy, with rms errors ranging from 6% to 22% depending on the composition of the calibration fluid. Results from integrating the multicomponent VSP data with the rock-physics model indicated that estimated reservoir porosities are quite close to measured values at an observation well. Pore-fluid composition estimates indicated that this method can differentiate between areas containing and those that do not.