Bubble-Population-Balance Modeling for Supercritical Carbon Dioxide Foam Enhanced-Oil-Recovery Processes: From Pore-Scale to Core-Scale and Field-Scale Events
- Mohammad Izadi (Louisiana State University) | Seung Ihl Kam (Louisiana State University)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- June 2019
- Document Type
- Journal Paper
- 2019.Society of Petroleum Engineers
- bubble population balance model, foam propagation, CO2 foam, foam EOR
- 18 in the last 30 days
- 47 since 2007
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A bubble-population-balance foam-modeling technique is developed to investigate how carbon dioxide (CO2) foam behaves rheologically and propagates in a field-scale radial system. The modeling technique is based on pore-scale events and honors three different foam states (weak, strong, and intermediate) and two steady-state strong-foam-flow regimes (high- and low-quality) measured in corescale experiments. The model parameters are first obtained from a fit to laboratory-coreflood experimental data, and then the mechanistic model is applied to different types of CO2 foams, ranging from gaseous to supercritical-CO2 foams, represented by various mobilization pressure gradients.
The results from the fit to existing coreflood data show that a reasonable match can be made satisfying multiple constraints, such as hysteresis exerted by three foam states, non-Newtonian flow behavior caused by gas trapping and shear-thinning rheology, and bubble stability in different capillary pressure environments. When applied to field-scale scenarios, supercritical-CO2 foams requiring low mobilization pressure gradients propagate much farther than gaseous-CO2 foams, far enough to make use of promising supercritical-CO2 foams in the field. This study, for the first time, theoretically demonstrates why supercritical-CO2 foams should be preferred in the field compared with gaseous N2 or CO2 foams.
The companion paper to extend this study to full-field-scale foam propagation in conjunction with gravity segregation is Izadi and Kam (2018).
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