Designing of Partial Similarity Models and Evaluation Method in Polymer Flooding Experiment

• Published in: Transport in porous media Vol. 75; no. 3; pp. 401 - 412
• Main Authors: Bai, Yuhu, Zhou, Jifu, Li, Qingping
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.12.2008; Springer; Springer Nature B.V
• Subjects: Civil Engineering; Classical and Continuum Physics; Coefficients; Compressibility; Criteria; Dimensionless numbers; Dispersions; Dominance; Earth and Environmental Science; Earth Sciences; Earth, ocean, space; Engineering and environment geology. Geothermics; Exact sciences and technology; Geotechnical Engineering & Applied Earth Sciences; Hydrocarbons; Hydrogeology; Hydrology. Hydrogeology; Hydrology/Water Resources; Industrial Chemistry/Chemical Engineering; Mathematical models; Parameter sensitivity; Pollution, environment geology; Polymer flooding; Polymers; Sedimentary rocks; Sensitivity analysis; Similarity; Dimensionless parameter; Polymer flooding; Sensitivity analysis; Partial similarity model; experimental studies; models; diffusion; absorption; sensitivity analysis; reservoirs; accuracy; transport; compressibility; Polymer flooding . Partial similarity model . Dimensionless parameter; polymers; dispersion; porous media; methodology
• ISSN: 0169-3913; 1573-1634
• DOI: 10.1007/s11242-008-9227-7

Based on the scaling criteria of polymer flooding reservoir obtained in our previous work in which the gravity and capillary forces, compressibility, non-Newtonian behavior, absorption, dispersion, and diffusion are considered, eight partial similarity models are designed. A new numerical approach of sensitivity analysis is suggested to quantify the dominance degree of relaxed dimensionless parameters for partial similarity model. The sensitivity factor quantifying the dominance degree of relaxed dimensionless parameter is defined. By solving the dimensionless governing equations including all dimensionless parameters, the sensitivity factor of each relaxed dimensionless parameter is calculated for each partial similarity model; thus, the dominance degree of the relaxed one is quantitatively determined. Based on the sensitivity analysis, the effect coefficient of partial similarity model is defined as the summation of product of sensitivity factor of relaxed dimensionless parameter and its relative relaxation quantity. The effect coefficient is used as a criterion to evaluate each partial similarity model. Then the partial similarity model with the smallest effect coefficient can be singled out to approximate to the prototype. Results show that the precision of partial similarity model is not only determined by the number of satisfied dimensionless parameters but also the relative relaxation quantity of the relaxed ones.