Experimentally-Based Empirical Foam Modeling
Practical application of foams for chemical and solvent EOR processes requires a representative and predictive model for foam flow and its mobility control characteristics. Many parameters such as surfactant concentration, shear rate, capillary number, oil saturation, and salinity affect foam flow behavior. Accordingly, different mechanistic and empirical foam models have been investigated in the literature and implemented in commercial simulators. Usually parameters in these models are tuned to match lab data for a particular foam-surfactant and oil system characteristics.
This paper presents process-based numerical simulations for modeling of foam-surfactant flow in a vertical sandpack column based on two sets of laboratory experimental data. The experimental setup, procedure, measurements and data analysis are discussed to provide apparent foam viscosity data for modeling. In the first lab tests, foam quality is constant and the total fluid velocity changes for shear thinning effect; while in the second tests, foam quality is varied at a fixed total velocity. The parametric matching of lab data is based on both fine-scale numerical simulations of the sandpack experiments as well as theoretical considerations of governing flow physics. The foam model is tuned to variable velocity foam flow of the first data set and then used to predict the second data set as consistency check. Based on this experimentally-tuned model, a validated foam model is constructed for use in field-scale commercial simulations of surfactant-foam flow in pilot testing of a naturally fractured reservoir. The model predictions for the second data set as well as the associated sensitivity analysis prove that our modeling approach is applicable for large scale predictions. The results of this paper illustrate a novel experimental procedure, a creative data analysis scheme and a comprehensive methodology for developing a process-based mechanistic foam model. The presented methodology for matching lab data is unique as it includes varying both foam quality and foam velocity for shear thinning and foam dry-out phenomena. As such, this model is shown to include basics physics of foam flow in porous media for large-scale field applications.
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© Copyright 2014. Society of Petroleum Engineers
Presented at the SPE Improved Oil Recovery Symposium, 12-16 April 2014, Tulsa, OK, USA