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124 Thomas Russell et al.
Table 3.7 Tuning the fines-migration parameters (drift delay factor α, concentration
of released particles Δσ, filtration coefficient λ, and formation damage coefficient β)
from the coreflood data
Test γ J A Δσ (ppm) λ (1/m) β R 2
1 0.035 M 0.11 78.6 46.04 6696 0.96
DI 0.05 598.5 180.23 290670 0.98
2 0.035 M 0.08 101.6 28.60 70663 0.97
DI 0.05 2600 109.07 76852 0.96
3 0.035 M 0.2 9.8 70.47 205050 0.97
0.018 M 0.06 5.9 61.34 12281 0.98
DI 0.03 15.3 56.96 191230 0.98
Table 3.7 belong to common intervals reported in the literature (Oliveira
et al., 2014; Vaz et al., 2017; Yuan and Shapiro, 2011; Zeinijahromi et al.,
2013).
3.5.3 Well injectivity decline during low-salinity water
injection
Injectivity impairment is one of the main challenges of waterflooding
projects (Civan, 2014). Injectivity decline is commonly associated with
the capture of injected foreign particles and natural reservoir fines, and
also due to the formation of an external filter cake (Kalantariasl and
Bedrikovetsky, 2013; Pang and Sharma, 1997). The reliable prediction of
well injectivity highly affects planning and design of waterflooding opera-
tions. Usually, reliable well behavior prediction involves laboratory-based
mathematical modeling. This section presents a mathematical model for
injectivity decline due to fines migration during low-salinity waterflood-
ing. The assumptions of the model are the same as those formulated in
Section 3.5.1.
The governing system consists of a mass balance for suspended,
attached, and strained particles, kinetics rate for straining, expression for
maximum retention function, mass balance for salt, and Darcy’s law for
axisymmetric flow, accounting for permeability damage due to fines
straining. Assuming incompressibility of the carrier fluid, the velocity pro-
file at any distance from the well follows:
q
UrðÞ 5 ; (3.113)
2πr
where r is the radial coordinate, and q is the injection rate per unit of
formation thickness.