Page 56 - Hybrid Enhanced Oil Recovery Using Smart Waterflooding

48 Hybrid Enhanced Oil Recovery using Smart Waterflooding

models of LSWF. For the experimental results of Fjelde (A)
et al. (2012), numerical simulations with and without 0.16 Ca++ Effluent - GEM vs Experiment (Fjelde)
cation-exchange reaction of Ca 2þ are investigated in
0.14
2þ
terms of the effluent concentration of Ca . The core
flooding process is designed to inject seawater after Fjelde_Experiment
formation water and then low-salinity water after the 0.1 GEM
seawater. The simulation without the cation exchange
0.08
shows a discrepancy to the experimental result during Concentration (mol/l) 0.12
seawater injection, but the simulation with the cation 0.06
exchange provides a great match (Fig. 3.4A). The 0.04
simulation with the cation-exchange reaction also
0.02
shows an excellent match of the effluent pH against
the experimental measurement (Fig. 3.4B). The numer- 0
0 5 10 15 20 25 30 35
ical simulation describes an increase in the effluent pH, Injected Pore Volume
as the injecting brine salinity decreases. The trend of (B)
increasing pH can be explained with the dissolution 8.5
calcite mineral during LSWF. The dissolution of calcite
8
mineral by LSWF consumes the hydrogen ion and in-
creases the pH. In addition, the modeling of wettability
7.5
modification sufficiently captures the reduction in
remained oil saturation (Fig. 3.4C). For the experiment 7
(Rivet, 2009), the LSWF simulation with ion-exchange pH
reaction also successfully describes the historical results 6.5
of residual oil saturation and effluent pH. Fjelde_Experiment
Kazemi Nia Korrani, Sepehrnoori, and Delshad 6 GEM
(2013) from the University of Texas at Austin advanced
the UTCHEM, an in-house chemical flood simulator, by 5.5
0 5 10 15 20 25 30 35
coupling with IPhreeqc, a geochemical module by the Injected Pore Volume
United States Geological Survey (USGS). The IPhreeqc (C) Oil Saturation - GEM vs Experiment (Fjede)
is the open source module of the PHREEQC software. 0.7
The advanced UTCHEM can be applied to various
EOR processes, including alkali and surfactant floods 0.6
Fjelde_Experiment
in both sandstone and carbonate reservoirs. It also has GEM
a capability to mechanistically model LSWF introducing 0.5
comprehensive geochemistry. This simulator models
the wettability modification of LSWF as a function of Oil Saturation 0.4
geochemical ions and reactions. A series of studies
(Al-Shalabi, Luo, Delshad, & Sepehrnoori, 2015; 0.3
Al-Shalabi, Sepehrnoori, Delshad, & Pope, 2015;
0.2
Al-Shalabi, Sepehrnoori, Pope, & Mohanty, 2014)
have used the UTCHEM to construct the numerical 0.1
model of LSWF process in carbonate reservoirs. They 0 5 10 15 20 25 30 35
Injected Pore Volume
simulated the coreflooding experiments of carbonate
FIG. 3.4 The comparison of LSWF between simulation and
(Mohanty & Chandrasekhar, 2013; Yousef, Al-Saleh,
and Al-Jawfi 2012; Yousef, Al-Saleh, Al-Kaabi, & experiment (Fjelde et al., 2012) in terms of the (A) effluent
2þ
concentration of Ca , (B) pH, and (C) remained oil
Al-Jawfi, 2011) and reported the three methodologies saturation. (From Dang, C. T. Q., Nghiem, L. X., Chen, Z. J., &
of wettability modification modeling: (1) empirical Nguyen, Q. P. (2013). Modeling low salinity waterflooding: Ion
model using the contact angle (Al-Shalabi, Sepehrnoori, exchange, geochemistry and wettability alteration. In: Paper
et al., 2015); (2) fundamental model using the trapping presented at the SPE annual technical conference and
number (Al-Shalabi et al., 2014); and (3) mechanistic exhibition, New Orleans, Louisiana, USA, 30 Septembere2
model using the molar Gibbs free energy of solution October. https://doi.org/10.2118/166447-MS.)
(Al-Shalabi, Sepehrnoori, & Pope, 2015).