Abstract
Understanding and predicting the performance of solvent drives and remediation of contaminated aquifers in heterogeneous reservoirs is of great importance to the petroleum and environmental industries. In this paper, a general method to scale flow through heterogeneous reservoirs is presented for a miscible displacement of oil by a solvent. Results show that scaling miscible displacements in a two-dimensional, heterogeneous, anisotropic vertical cross section requires the matching of 13 dimensionless scaling groups. These groups were derived using a general procedure of inspectional analysis. A detailed numerical sensitivity study was performed to reveal the relationship between the scaling groups and the fractional oil recovery of miscible displacements in heterogeneous reservoirs. This relationship was then mapped using an artificial neural network, which can be used as a quick prediction tool for the fractional oil recovery for any combinations of the scaling groups, thus eliminating the need for the expensive fine-mesh simulations. These results have potential applications in modeling miscible displacements and in the scaling of laboratory displacements to field conditions.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Bear, J.: 1972, Dynamics of Fluids in Porous Media, Elsevier, New York, pp. 665–727.
Birkhoff, G.: 1950, Hydrodynamics: A Study in Logic, Fact, and Similitude, Princeton University Press, Princeton, NJ.
Buckingham, E.: 1914, On physically similar systems; illustrations of the use of dimensional equations, Phys. Rev. 4, 345.
Collins, R. E.: 1976, Flow of Fluids Through Porous Materials, The Petroleum Publishing Company, Tulsa, OK, pp. 217–241.
Dykstra, H. and Parsons, R. L.: 1950, The Prediction of Oil Recovery by Water Flood. Secondary Recovery of Oil in the United States, Principles and Practice, 2nd edn., American Petroleum Institute.
Elsharkawy, A. and Gharbi, R.: 2000, Comparing classical and neural regression techniques in modeling crude oil viscosity, Adv. Engng Software (accepted).
Focken, C. M.: 1953, Dimensional Methods and Their Applications, Arnold & Co., London.
Gharbi, R., Karkoub, M. and Elkamel, A.: 1995, An artificial neural network for the prediction of immiscible flood performance, Energy Fuels 9, 894–900.
Gharbi, R., Peters, E.J. and Elkamel, A.: 1998, Scaling miscible fluid displacements in porous media, Energy Fuels 12, 801–811.
Greenkorn, R. A.: Flow models and scaling laws – flow through porous media, Ind. Eng. Chem. 56,27–32.
Langhaar, H. L.: 1951, Dimensional Analysis and Theory of Models, Wiley, New York.
Li, D. and Lake, L. W.: Scaling fluid flow through heterogeneous permeable media, SPE Adv. Technol. Ser. 3(1).
Loomis, A. G. and Crowell, D. C.: Theory and application of dimensional and inspectional analysis to study displacements in petroleum reservoirs, U.S. Bureau of Mines, Report of Investigation 6546.
Nielsen, R. L. and Tek, M. R.: Evaluation of scale-up laws for two-phase flow through porous media, Soc. Pet. Eng. J., 164–176.
Peters, E. J., Afzal, N. and Gharbi, R.: 1993 On scaling immiscible displacements in permeable media, J. Pet. Sci. Eng. 9(3).
Rapoport, L. A. and Leas, W. J.: 1953, Properties of linear waterfloods, Trans. AIME 198, 139–148.
Ruark, A. E.: 1935, Inspectional analysis: a method which supplements dimensional analysis, J. Elisha Mitchell Sci. Soc. 51, 127–132.
Saad, N.: 1989, Field scale simulation of chemical flooding, PhD Dissertation, The University of Texas, Austin.
Shook, M., Li, D. and Lake, W. L.: Scaling immiscible flow through permeable media by inspectional analysis, In situ 16(3), 311–349.
Sorbie, K. S., Feghi, F., Pickup, G. E., Ringrose, P. S. and Jensen, J. L.: 1994, Flow regimes in miscible displacements in heterogeneous correlated random fields, SPE Adv. Technol. Ser. 2(2), 78.
Waggoner, J. R., Castillo, J. L. and Lake, L. W.: 1992, Simulation of EOR processes in statistically generated permeable media, Soc. Pet. Eng. Format. Eval., 173–180.
Wahl, F. M.: 1987, Digital Image Signal Processing, Artech House, Boston, London.
Wygal, R. J.: 1963, Construction of models that simulate oil reservoirs, Soc. Pet. Eng. J. 3, 281–286.
Yang, A. P.: 1990, Stochastic heterogeneity and dispersion, PhD Dissertation, The University of Texas, Austin.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Gharbi, R.B. Dimensionally Scaled Miscible Displacements in Heterogeneous Permeable Media. Transport in Porous Media 48, 271–290 (2002). https://doi.org/10.1023/A:1015723329598
Issue Date:
DOI: https://doi.org/10.1023/A:1015723329598