The objective of this research is to widen the applicability of gas flooding to shallow oil reservoirs by reducing the pressure required for miscibility using gas enrichment and increasing sweep efficiency with foam. Task 1 examines the potential for improved oil recovery with enriched gases. Subtask 1.1 examines the effect of dispersion processes on oil recovery and the extent of enrichment needed in the presence of dispersion. Subtask 1.2 develops a fast, efficient method to predict the extent of enrichment needed for crude oils at a given pressure. Task 2 develops improved foam processes to increase sweep efficiency in gas flooding. Subtask 2.1 comprises mechanistic experimental studies of foams with N{sup 2} gas. Subtask 2.2 conducts experiments with CO{sup 2} foam. Subtask 2.3 develops and applies a simulator for foam processes in field application. Regarding Task 1, several key results are described in this report relating to subtask 1.1. In particular, we show how for slimtube experiments, oil recoveries do not increase significantly with enrichments greater than the MME. For field projects, however, the optimum enrichment required to maximize recovery on a pattern scale may be different from the MME. The optimum enrichment is likely the result of greater mixing in reservoirs than in slimtubes. In addition, 2-D effects such as channeling, gravity tonguing, and crossflow can impact the enrichment selected. We also show the interplay between various mixing mechanisms, enrichment level, and numerical dispersion. The mixing mechanisms examined are mechanical dispersion, gravity crossflow, and viscous crossflow. UTCOMP is used to evaluate the effect of these mechanisms on recovery for different grid refinements, reservoir heterogeneities, injection boundary conditions, relative permeabilities, and numerical weighting methods including higher-order methods. For all simulations, the reservoir fluid used is a twelve-component oil displaced by gases enriched above the MME. The results for subtask 1.1 show that for 1-D enriched-gas floods, the recovery difference between displacements above the MME and those at or near the MME increases significantly with dispersion. The trend, however, is not monotonic and shows a maximum at a dispersivity (mixing level) of about 4 ft. The trend is independent of relative permeabilities and gas trapping for dispersivities less than about 4 ft. For 2-D enriched gas floods with slug injection, the difference in recovery generally increases as dispersion and crossflow increase. The magnitude of the recovery differences is less than observed for the 1-D displacements. Recovery differences for 2-D models are highly dependent on relative permeabilities and gas trapping. For water alternating gas (WAG) injection, the differences in recovery increase slightly as dispersion decreases. That is, the recovery difference is significantly greater with WAG at low levels of dispersion than with slug injection. For the cases examined, the magnitude of recovery difference varies from about 1 to 8 percent of the original oil-in-place (OOIP). Regarding Task 2, three results are described in this report: (1) New experiments with N{sup 2} foam examined the mobility of liquid injected following foam in alternating-slug (SAG) foam processes. These experiments were conducted in parallel with a simulation study of foam for acid diversion in well stimulation. The new experiments qualitatively confirm several of the trends predicted by simulation. (2) A literature study finds that the two steady-state foam-flow regimes seen with a wide variety of N{sup 2} foams also appears in many studies of CO{sup 2} foams, if the data are replotted in a format that makes these regimes clear. A new experimental study of dense CO{sup 2} foam here failed to reproduce these trends, however; the reason remains under investigation. (3) A number of published foam models were examined in terms of the two foam-flow regimes and using fractional-flow theory. At least two of the foam models predict the two foam-flow regimes. Fractional-flow theory predicts that large-scale simulation using one of the models would lead to numerical artifacts, however.
