Interfacial tension experiments
Evaluation of IFT is a pivotal parameter to evaluate the performance of
chemical fluid to recover tertiary crude oil. Aqueous surfactant
solutions were prepared at concentrations ranging between 0.05% and
0.35%, wherein silica particle dosages were varied at 0.01-0.10% in
aqueous nanoparticle dispersions. Fig. 3(a) and 3(b) depicts the
variation of IFT with surfactant concentration at 303 K. It was observed
that IFT decreased with increasing surfactant/nanoparticle
concentrations up to a critical limit. In the absence of any
surface-active species, IFT value was found to be 18.2 mN/m. GS
exhibited ultralow IFT owing to their unique molecular structure and
capability to self-aggregate at low concentrations. IFT decreased
significantly with values of 0.1127 mN/m and 0.0594 mN/m at 0.05% and
0.10% 14-6-14 GS respectively. 14-6-14 GS molecules form micelles; and
arrange as mixed micellar phase existing at oil-aqueous interfaces
[51,52]. At 0.10% concentration, the interface was completely
saturated with 14-6-14 GS molecules, which is evident from minima value
of IFT. Beyond this concentration, a slight increase in IFT was observed
due to variation of distribution of adsorbed molecules/micelles,
resulting in slightly higher rate of desorption as compared to
surfactant adsorption process. Once at the interface, 14-6-14 GS
molecules readjust and orient themselves such that the two tail groups
point towards crude oil phase in order to achieve equilibrium conditions
with minimum interfacial energy and favorable oil-attracting capacity
[47,52]. Like surfactant, nanoparticles adsorbed along interface of
oil and aqueous phases; and favorably improved interfacial activity. The
IFT decreased from 18.2 mN/m to ~6.0 mN/m during
SiO2 addition. It is evident that nanoparticles do not
achieve ultralow IFT values due to less efficient adsorption activity.
However, nanoparticle strengthen the mechanical barrier effect, which
ensure improved oil mobilization ability [53].
Fig. 3. Oil-aqueous IFT profiles presented as a function of:
(a) 14-6-14 GS concentration, and (b) SiO2 nanoparticle
concentration.
In this section, surfactant/polymer/nanoparticle fluids were placed in
contact with oil to identify synergistic associations among interacting
mixed species. Fig. 4 shows the IFT behavior of 14-6-14 GS +/ PHPA
aqueous fluids in the presence and absence of silica
(SiO2). Surfactant-polymer fluids exhibited greater
values of IFT in comparison to pure surfactant solutions. PHPA addition
favors inter-polymer and intra-polymer interactions, thereby reducing
their exposure to water [54]. This reduces the number of adsorbed
14-6-14 GS molecules in mixed micelles/aggregates in solution and lower
surfactant adsorption at liquid-liquid interfaces. The electrostatic
repulsive forces between surfactant dimer head-groups increases
significantly during polymer addition. Polymer chains diffuse to
adsorption sites and cause significant variation in inter-molecular
arrangement, resulting in IFT increase [54,55]. However, polymer
addition enhances oil mobility to improve the sweep efficiency of
displaced crude oil.
Nanoparticle addition showed better activity in terms of reduced IFT,
which is attributed to their favorable adsorption at oil-aqueous
interfaces and reduction in interfacial energy barrier [53,56].
However, this behavior was observed until a favorable
SiO2 concentration, referred to as critical
concentration. For surfactant solutions, IFT was reduced from 0.0594
mN/m to 0.0194 mN/m at 0.030% SiO2. In case of
surfactant-polymer solutions, critical NP dosage of 0.025% was obtained
with IFT minima of 0.0318 mN/m. The critical NP concentration obtained
in case of surfactant-polymer-nanoparticle (SPN) fluids is lower (0.025
wt. %) as compared to that obtained for surfactant fluids (0.030 wt.
%). Beyond this limit, IFT was observed to increase gradually owing to
improved steric effect in the presence of higher concentration species
[56,57]. This indicated desorption of interacting
molecules/particles from the interface to the bulk solution phase and
consequent transition of mixed micelles to super micelles or vesicles
[56,57]. SPN fluids are able to recover oil with IFT values in the
desired optimal range and sweep crude oil with greater efficacy as
compared to surfactant-nanoparticle and surfactant formulations.
Henceforth, interfacial behavior of SPN aqueous solutions contribute
beneficially in EOR studies.
Fig. 4. Interfacial tension plots for 14-6-14 GS and {14-6-14
GS + PHPA} systems, presented as a function of silica concentration at
303 K.
Influence of polymer/nanoparticle on fluid rheology
An EOR fluid must possess favorable rheological properties to achieve
favorable displacement of crude oil through porous rock formations. The
influence of addition of surfactant (14-6-14 GS), polymer (PHPA) and
nanoparticle (SiO2) on the viscosity of chemical fluids
are studied to identify flow behavior and predict oil mobilization
ability. Figs. 5(a), 5(b) and 5(c) show plots of viscosity versus
concentration at shear rate of 10 s-1. It is evident
that apparent viscosity increases with increasing concentration. Aqueous
chemical fluids showed shear thinning or pseudoplastic flow behavior,
which is considered as desirable attributes to achieve good injectivity
and oil mobilization control. Fig. 5(d) shows the viscosity versus shear
stress plots for different aqueous fluid compositions at 303 K. With
application of increasing shear rate, hydrophobic associations are
weakened which decrease the strength of inter-molecular and
intra-molecular interactions. Viscosity of aqueous solution was observed
to be 4.93 mPa.s at 0.02% 14-6-14 GS concentration, which subsequently
increased to 6.63 mPa.s at 0.05%, 11.24 mPa.s at 0.10%, 13.84 mPa.s at
0.20% and 14.29 mPa.s at 0.35% concentrations (refer to Fig. 5(a)).
With increase in 14-6-14 GS concentration, surfactant molecules form
super-micelles or vesicles in bulk solution, which reduces the available
“free” volume and enhances fluid viscosity. Addition of polymer as
well as nanoparticle also exhibited similar behavior in terms of
viscosity for 0.10% 14-6-14 GS containing fluids. With addition of
0.05% PHPA, viscosity increased to value as high as 27.69 mPa.s, as
depicted in Fig. 5(b). This is attributed to the increased degree of
entanglement of polymer chains and formation of a network structure
consisting of “larger” mixed micelle associations [58]. Fig. 5(c)
shows further increase in aqueous solution viscosity in the presence of
SiO2 nanoparticle due to their ability to effectively
strengthen the mechanical barrier (electrostatic repulsion + steric
effects) around dispersed micelles/aggregates formed within {14-6-14 GS
+ PHPA + SiO2} solution [56,59]. This leads to more
pronounced network structure with longer mixed micelle entanglements and
consequent increase in viscosity. Surfactant-polymer-nanoparticle (SPN)
fluids showed a sharp increase in viscosity (42.82 mPa.s) until
concentration limit of 0.025% SiO2, beyond which it
increased gradually. In fact, viscosities of SPN nanoemulsions were
measured in the 34-45 mPa.s range, which is attributed to the formation
of enhanced {14-6-14 GS + PHPA + SiO2} network
structure. Hence, SPN aqueous fluids act as beneficial oil mobility
control agents for EOR studies.
Fig. 5. Viscosity profiles as function of temperature for
different aqueous formulations containing (a) 14-6-14 GS;(b) 14-6-14 GS + PHPA; and (c) 14-6-14 GS + PHPA +
SiO2. Fig 5(d) shows the pseudoplastic character of aqueous
fluids, evident from viscosity versus shear rate plots at 303 K.
Flooding experiment results
Core-flooding experiments are necessary to determine secondary and
tertiary recoveries with different formulated (aqueous) chemical slugs
[60]. In this study, gemini surfactant concentration greater than
CMC was chosen to account for adsorption losses. PHPA +/
SiO2 were introduced in 14-6-14 GS based injection
fluids as EOR performance enhancers to achieve better oil displacement
data. Cumulative oil recoveries for different fluid systems were
investigated as a function of injection pore volume, as presented in
Fig. 6. During water-flooding process, 45-47% of the original oil in
place (OOIP) was extracted. However, residual oil remained trapped
within reservoir pore-throats owing to gravity effect, inertia and
capillary forces. Once ≥ 95% water cut was achieved, recovery profile
flattened. Thereafter, gemini surfactant/polymer/silica slug was
injected as the first stage of EOR to improve oil production efficiency.
The second stage of EOR incorporated flooding with chase water to
maintain pressure differential and ensure continuous displacement of
forward-moving oil bank. Tertiary oil recoveries of ~15
% was achieved during {14-6-14 GS + chase water} flooding, which
subsequently improved to ~17% and ~18%
for {14-6-14 GS + PHPA + chase water} and {14-6-14 GS + PHPA +
SiO2 chase water} systems respectively. The secondary
and tertiary flooding data results were employed as input data for
(CMOST) assisted history-matching functions, discussed in subsequent
sections [18,19,27,37].
Fig. 6. Oil recovery performance of aqueous
surfactant/polymer/nanoparticle solution in core-flooding systems.
- STARS Modelling approach for Coreflood Simulation
- Core Model Building
The STARS (CMG) tool replicates a cylindrical sandstone core with volume
of 91.952 cm3. A Cartesian system was developed with
single porosity model, as shown in Fig. 7. A rectangular grid with 100
blocks (each length 0.0874 cm) in I-direction, height (3.243 cm) and
width (3.243 cm) was created initially such that its volume is equal to
that of laboratory core. The grid pattern was mapped as centroid
function along X-axis to obtain appropriate STARS model. In subsequent
studies, Case scenarios I, II and III refer to core-flooding simulation
models pertaining to {water-flood + surfactant EOR}, {water flood +
surfactant-polymer EOR}, and {water flood +
surfactant-polymer-nanoparticle EOR} systems respectively.