WETTABILITY EFFECTS ON 2-FLUID AND 3-FLUID RELATIVE PERMEABILITIES

Specification of relative permeability (k(r))-saturation (S) relations for all fluid phases is required for the simulation of multiphase flo w and transport in porous media. Indirect methods are frequently emplo yed to estimate these k(r)-S relations owing to the time, expense, and difficulty associated with direct measurements. A common indirect app roach uses capillary pressure data in conjunction with a selected pore -size distribution model to estimate k(r)-S relations. Such methods ty pically assume perfect wettability of the solid. Natural porous media, however, are composed of a variety of mineral constituents with diffe rent adsorptive properties, which can exhibit non-zero contact angles and/or fractional wettability. Consequently, fluid distributions in na tural media may be more complex than those predicted by simple pore-si ze distribution models and, under such conditions, current estimation approaches for k(r) may be inadequate. In this work, the pore-size dis tribution model of N.T. Burdine (1953, Relative permeability calculati ons from pore-size distribution data. Transactions of the American Ins titute of Mining, Metallurgical and Petroleum Engineers 198, 71-77) is extended to incorporate wettability variations. In this model, wettin g and less wetting (non-wetting or intermediate) fluid pore classes ar e used to calculate k(r) for water or organic. The wettability of the porous medium is used to determine the contributions of the pore class es to k(r). For both two-and three-fluid systems, the model predicts t hat an increase in the contact angle (measured through water) or organ ic-wet fraction of a medium will be accompanied by an increase in the water k(r) and a decrease in the organic k(r). In three-fluid media, k (r) values for water and organic depend on both liquid saturations whe n the solid is imperfectly wetted. The model assumes that wettability variation has no influence on the air k(r). Model predictions are show n to be consistent with available experimental data. (C) 1997 Elsevier Science B.V.