Summary
Gas enrichment is an important variable used to optimize oil recovery in enriched-gas drives. For slimtube experiments, oil recoveries do not increase significantly with enrichments greater than the minimum miscibility enrichment (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, 2D effects, such as channeling, gravity tonguing, and crossflow, can impact the enrichment selected.
Numerical simulation is often used to model the effect of physical mixing on oil recovery in miscible gasfloods. Unfortunately, numerical dispersion can cloud the interpretation of the results by artificially increasing the level of mixing in the reservoir.
This paper investigates the interplay among various mixing mechanisms, enrichment levels, and numerical dispersion. The mixing mechanisms examined are mechanical dispersion, gravity crossflow, and viscous crossflow. The U. of Texas Compositional Simulator (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. The reservoir fluid used for all simulations is a 12-component oil displaced by gases enriched above the MME.
The results show that for 1D enriched gasfloods, 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 of approximately 4 ft. The trend is independent of relative permeabilities and gas trapping for dispersivities of less than approximately 4 ft. For 2D enriched gasfloods with slug injection, the difference in recovery generally increases as dispersion and crossflow increase. The magnitude of the recovery differences is less than that observed for the 1D displacements. Recovery differences for 2D 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 approximately 1 to 8% of the original oil in place (OOIP).
