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.
  1. STARS Modelling approach for Coreflood Simulation
  2. 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.