Minimum miscibility pressure (MMP) is a key parameter in the design of gas flooding. There are experimental and computational methods to determine MMP. Computational methods are fast and convenient alternatives to otherwise slow and expensive experimental procedures. This research focuses on the computational aspects of MMP estimation. It investigates the shortcomings of the current computational models and offers ways to improve the robustness of MMP estimation. First, we develop a new mixing cell method of estimating MMP that, unlike previous "mixing cell" methods, uses a variable number of cells and is independent of gas-oil ratio, volume of the cells, excess oil volumes, and the amount of gas injected. The new method relies entirely on robust P-T flash calculations using any cubic equation-of-state (EOS). We show that mixing cell MMPs are comparable with those of other analytical and experimental methods, and that our mixing cell method finds all the key tie lines predicted by MOC; however, the method proved to be more robust and reliable than current analytical methods. Second, we identify a number of problems with analytical methods of MMP estimation, and demonstrate them using real oil characterization examples. We show that the current MOC results, which assume that shocks exist from one key tie line to the next may not be reliable and may lead to large errors in MMP estimation. In such cases, the key tie lines determined using the MOC method do not control miscibility, likely as a result of the onset of L₁-L₂-V behavior. We explain the problem with a simplified pseudo-ternary model and offer a procedure for determining when an error exists and for improving the results. Finally, we present a simple mathematical model for predicting the MMP of contaminated gas. Injection-gas compositions often vary during the life of a gasflood because of reinjection and mixing of fluids in situ. Determining the MMP by slim-tube or other methods for each possible variation in the gas-mixture composition is impractical. Our method gives an easy and accurate way to determine impure CO₂ MMPs for variable field solvent compositions on the basis of just a few MMPs. Alternatively, the approach could be used to estimate the enrichment level required to lower the MMP to a desired pressure. / text