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Insights on Foam Transport from a Texture-Implicit Local-Equilibrium Model with an Improved Parameter Estimation Algorithm
Author(s) -
Yongchao Zeng,
Aarthi Muthuswamy,
Kun Ma,
Wang Le,
R. Farajzadeh,
Maura Puerto,
S. Vincent-Bonnieu,
Ali Akbar Eftekhari,
Ying Wang,
Chang Da,
Jeffrey C. Joyce,
Sibani Lisa Biswal,
George J. Hirasaki
Publication year - 2016
Publication title -
industrial and engineering chemistry research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.878
H-Index - 221
eISSN - 1520-5045
pISSN - 0888-5885
DOI - 10.1021/acs.iecr.6b01424
Subject(s) - algorithm , computer science , texture (cosmology) , estimation theory , artificial intelligence , image (mathematics)
We present an insightful discussion on the implications of foam transport inside porous media based on an improved algorithm for the estimation of model parameters. A widely used texture-implicit local-equilibrium foam model, STARS, is used to describe the reduction of gas mobility in the state of foam with respect to free gas. Both the dry-out effect and shear-dependent rheology are considered in foam simulations. We estimate the limiting capillary pressure Pc* from fmdryvalues in the STARS model to characterize foam film stability in a dynamic flowing system. We find that Pc* is a good indicator of foam strength in porous media and varies with different gas types. We also calculate Pc* for different foaming surfactants and find that foam stability is correlated with the Gibbs surface excess concentration. We compare our improved parameter estimation algorithm with others reported in literature. The robustness of the algorithm is validated for various foam systems

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