Estimation of Foam-Flow Parameters for Local Equilibrium Methods by Use of Steady-State Flow Experiments and Optimization Algorithms
- Jose Sergio de Araujo Cavalcante Filho (University of Texas at Austin) | Mojdeh Delshad (University of Texas at Austin) | Kamy Sepehrnoori (University of Texas at Austin)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- February 2018
- Document Type
- Journal Paper
- 160 - 173
- 2018.Society of Petroleum Engineers
- Local Equilibrium, Population Balance, Fitting Foam Model Parameters, Foam
- 3 in the last 30 days
- 172 since 2007
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Foam has been successfully used in the oil industry for conformance and mobility control in gas-injection processes. The efficiency of a foam-injection project must be assessed by means of numerical models. Although there are several foam-flow models in the literature, the prediction of foam behavior is an important issue that needs further investigation. In this paper, we estimate foam parameters and investigate foam behavior for a given range of water saturation by use of two local equilibrium foam models: the population balance assuming local equilibrium (LE) model and the University of Texas (UT) model. Our method uses an optimization algorithm to estimate foam-model parameters by matching the measured pressure gradient from steady-state foam-coreflood experiments. We calculate the effective foam viscosity and the water fractional flow by use of experimental data, and we then compare laboratory data against results obtained with the matched foam models to verify the foam parameters. Other variables, such as the foam texture and foam relative permeability, are used to further investigate the behavior of the foam during each experiment. We propose an improvement to the UT model that provides a better match in the high-quality regime by assuming resistance factor and critical water saturation as a linear function of the pressure gradient. Results show that the parameter-estimation method coupled with an optimization algorithm successfully matches the experimental data by use of both foam models. In the LE model, we observe different values of the foam effective viscosity for each pressure gradient caused by variations of foam texture and the shear-thinning viscosity effect. The UT model presents a constant effective viscosity for each pressure gradient; we propose the use of resistance factor and critical water saturation as a linear function of the pressure gradient to improve the match in the high-quality regime, when applicable.
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