Page 52 - Hybrid Enhanced Oil Recovery Using Smart Waterflooding

44 Hybrid Enhanced Oil Recovery using Smart Waterflooding

dispersion for the simulations of LSWF process. The
connate water banking will be formed when connate
water and oil are displaced by low-salinity water. It flows
ahead of the front of low-salinity water. The studies
validated the effect of connate water banking on
the displacement through extended Buckley-Leverett
solution. It is explained that the higher oil recovery at
breakthrough hardly guarantees the disappearance of
FIG. 3.1 The schematic description of salinity dependence the connate water banking. Therefore, it is concluded
of residual oil saturation used in the empirical approach. that the laboratory experiments of LSWF should consider
(From Jerauld, G. R., Webb, K. J., Lin, C.-Y., & Seccombe, J. the effect of connate water banking to interpret the
C. (2008). Modeling low-salinity waterflooding. SPE Reservoir salinity-dependent relative permeability curves to be
Evaluation and Engineering, 11(6), 1000e1012. https://doi. used in simulations of LSWF. Because the mixing
org/10.2118/102239-PA.)
between connate water and low-salinity water influences
the interpretation and predictions of LSWF, the physical
low and high salinity threshold conditions using a
normalized residual oil saturation. The salt is assumed dispersion is also of importance in both laboratory and
to be an additional single-lumped component in an field tests. In the numerical simulations of LSWF, the
aqueous phase. The viscosity and density of the physical dispersion is approximated by using the numer-
aqueous phase are the function of the salinity. ical dispersion. Although the numerical dispersion fairly
Following Eqs. (3.41)e(3.45) formulate the empirical simulates the physical dispersion, the accurate modeling
approach of wettability modification modeling. of the dispersion is sensitive to the grid size and dimen-
sion of numerical simulation. In addition, the level of
S

S
k rw ¼ F IF k HS þð1 F IF Þk LS (3.41) dispersion depends on the slug size. Even though the

o
rw
rw
o
simulation uses a fine grid model to capture the physical

k ro ¼ F IF k HS S o þð1 F IF Þk LS S o (3.42) dispersion with the numerical dispersion, it requires
ro
ro
S

p c ¼ F IF p HS þð1 F IF Þp LS (3.43) significant computational time. Incorporating the
S

c
c
o
o
pseudo-relative permeability and modified salinity
LS
S or S or dependency, the simulation with a coarse grid model
F IF ¼ (3.44)
S HS S LS can provide the same results of the fine grid model
or
or
simulation and requires less simulation time. Using the
ðS o S or Þ
(3.45)
S ¼ empirical approach of wettability modification and
o
ð1 S wi S or Þ
modeling of numerical dispersion, they have simulated
where k rw is the relative permeability of aqueous phase, the LSWF process with the physical dispersion.
F IF is the interpolation factor, k HS is the relative perme-
rw
ability of aqueous phase at the high threshold salinity
condition, S is the normalized residual oil saturation, MECHANISTIC MODELING WITH

o
k LS is the relative permeability of aqueous phase at the GEOCHEMISTRY
rw
low threshold salinity condition, k ro is the relative perme- Omekeh, Friis, Fjelde, and Evje (2012) developed a nu-
ability of oleic phase, k HS is the relative permeability of merical model of Buckley-Leverett two-phase flow to
ro
oleic phase at the high salinity threshold condition, k LS simulate the core flooding of LSWF for sandstone reser-
ro
is the relative permeability of oleic phase at the low voirs. This study suggested that the LSWF modifies the
salinity threshold condition, p c is the capillary pressure, wettability of sandstone based on the MIE mechanism,
p HS is the capillary pressure at the high salinity threshold not pH increase, and the pH increase is only the result
c
condition, p LS is the capillary pressure at the low salinity of mineral dissolution and aqueous solubility of CO 2 .
c
threshold condition, S or is the residual oil saturation, S LS The numerical simulation employs the ion-exchange
or
is the residual oil saturation at the low salinity threshold reactions to model the MIE mechanism. Because the
condition, S HS is the residual oil saturation at the high geochemistry is closely related to the LSWF process,
or
salinity threshold condition, and S wi is the irreducible the modeling of the Buckley-Leverett two-phase flow
water saturation. incorporates the modeling of geochemical reactions of
In addition, these studies cautioned the phenomena aqueous reactions, mineral reactions, and the ion
including connate water banking and physical exchange. In addition, there is an assumption for the