Simulation studies were performed to evaluate a novel technology, steam-propane injection, for heavy Hamaca crude oil from Venezuela's Orinoco Basin. The oil has a specific gravity of 1.005 (9.3degrees API) and a viscosity of 23 Pa(.)s (25,000 cp) at 50degrees C. Two types of studies were performed: a simulation study to history-match laboratory results and a reservoir simulation study of steam-propane injection in a 5-spot pattern. A 1D 48 grid-cell model was used to describe the sand mix in the injection cell. A ten pseudo-component oil model for Hamaca oil was developed based on composition up to C-10 that gave a satisfactory history match of experimental results. Components in the C-7 - C-10 range appear to play a significant role during steam-propane injection and therefore need to be described in greater detail. The pseudo-component oil model was subsequently used in the reservoir model. The reservoir model represented a symmetry volume that is one-eighth of a 10-acre 5-spot pattern. A 9 x 5 x 10 3D Cartesian model was used to describe the symmetry volume, with one axis (x-axis) oriented parallel to the injector-producer direction. Simulation results indicate the following. First, oil production acceleration of 15% was observed with a propane-steam mass ratio (PSR) of 0.05 compared to pure steam injection. A substantial gain in discounted revenue and savings in steam injection cost would be realized. Second, unlike the experimental results, the oil production rate peak with steam-propane injection. 175 m(3)/d (1,100 STB/D), is significantly higher than that with pure steam injection, 110 m(3)/d (690 STB/D). Third, oil production acceleration increases with increasing propane content. And finally, oil recovery (at the end of the five-year forecast period) increases from 2.3% OOIP for pure steam injection to 7.0% OOIP for steam-propane injection with a PSR of 0.05. Both experimental and simulation studies indicate that steam-propane injection is a very promising technology. Further research, followed by field tests, are recommended to better understand and verify the process under actual field conditions.