Pj. Hicks et Ha. Deans, EFFECT OF PERMEABILITY DISTRIBUTION ON MISCIBLE DISPLACEMENT IN A HETEROGENEOUS CARBONATE CORE, Journal of Canadian Petroleum Technology, 33(8), 1994, pp. 28-34
Citations number
11
Categorie Soggetti
Energy & Fuels","Engineering, Chemical","Engineering, Petroleum
Three-dimensional miscible brine displacement simulations have been pe
rformed for flow through a 10.2 cm (4 inch) diameter heterogeneous cor
e containing a residual oil phase. The displacement front, as expected
, is found to be a strong function of the permeability distribution as
sumed for the core. The porosity and residual oil saturations were mea
sured previously using X-ray CT. These experimental distributions were
used as input for the simulations. Since the permeability distributio
n cannot be measured directly in three dimensions for the core, two di
fferent empirical relationships were used to estimate the permeability
distribution based on the experimental porosity and residual oil satu
ration distributions. The position of the saturation front is calculat
ed and shown for various injection volumes for simulations using the t
wo porosity-permeability relationships. Semilog and exponential porosi
ty-permeability models were tested. For our case the semilog relations
hip tends more toward the piston-like displacement, with only a couple
of fingers developing. The exponential fit has a more irregular front
. The two porosity-permeability models yield significantly different i
n situ saturation distributions with roughly equivalent matches of the
experimental effluent profiles from the displacement experiments. Thr
ough the use of CT measured in situ saturations, the porosity-permeabi
lity relationships were evaluated. The semilog relationship performed
slightly better for the core studied even though both models gave equi
valent results for the effluent profiles. This demonstrates the import
ance of developing techniques such as CT which will monitor the in sit
u saturations as well as the effluent saturations when attempting to d
evelop and validate flow models.