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Abstract

The low-salinity waterflooding is an attractive eco-friendly producing method, recently, for carbonate reservoirs. When ferrous ion is present in the formation water, that is, acidic water, the injection of low-salinity water generally with neutral pH can yield precipitation or dissolution of Fe-minerals by pH mixing effect. FeSO₄ and pyrite can be precipitated and re-dissolved, or vice versa, while siderite and Fe(OH)₂ are insoluble which are precipitated, causing permeability reduction. Particularly, pyrite chemically reacts with low-salinity water and release sulfate ion, altering the wettability, favorably, to water-wet. In this aspect, we analyzed oil production focusing on dissolution of Fe-minerals and Fe-precipitation using a commercial compositional reservoir simulator. From the simulation results, the quantities of precipitation and dissolution were enormously large regardless of the type of Fe-minerals and there was almost no difference in terms of total volume in this system. However, among Fe-minerals, Fe(OH)₂ precipitation and pyrite dissolution were noticeably large compared to troilite, FeSO₄, and siderite. Therefore, it is essential to analyze precipitation or dissolution for each Fe-mineral, individually. Meanwhile, in dissolving process of pyrite, sulfate ions were released differently depending on the content of pyrite. Here, the magnitude of the generated sulfate ion was limited at certain level of pyrite content. Thus, it is necessary to pay attention for determining the concentration of sulfate ion in designing the composition of injection water. Ultimately, in the investigation of the efficiency of oil production, it was found that the oil production was enhanced due to an additional sulfate ion generated from FeS₂ dissolution.

Keywords

Low-salinity ferrous ion permeability wettability oil production carbonate

Introduction

Low-salinity waterflooding (LSWF) is a simple and environmentally friendly enhanced oil recovery (EOR) method, which can improve the oil recovery by lowering the salinity of injected brine or by adjusting the ion concentration. The recovery of oil from carbonates is below 30% since more than 80% of carbonate reservoirs possess intermediate or oil wetness (Mahmoud and Nasr-El-Din, 2014; Yue and Wang, 2015; Zhou and Yang, 2017). Through various experimental studies, it has been verified that the injection of low-salinity water (LSW) to an oil-wet carbonate reservoir has been able to alter its wettability to water-wet (Morrow et al., 1998; Standnes and Austad, 2000; Yassin et al., 2015). Besides, the salinity of injection water and the concentration of potential determining ions (PDI) such as sulfate ion (SO₄^2–), Ca²⁺, and Mg²⁺ have been reported to be major factors leading to a wettability alteration (Al-Shalabi et al., 2014; Jalilian et al., 2017; Salamat et al., 2016; Yousef et al., 2011; Zhang et al., 2007). Lager et al. (2007), McGuire et al. (2005), and Wolthers et al. (2008) confirmed that LSW injection caused the dissolution of calcite and an increase in pH due to OH^– ions generated from the dissolution as follows

H_{2} O + C a C O_{3} \leftrightarrow C a^{2 +} + H C O_{3}^{-} + O H^{-}

(1)

In other words, an increase in pH by 1 to 3 was observed as calcite within the core became dissolved through the LSWF experiments. Since there was only one equilibrium point among the oil, brine, and rock, at a specific pH, the change in pH shifted the chemical equilibrium, which could result in precipitation (Mahani et al., 2015). Zhang and Sarma (2012) demonstrated the precipitation of CaSO₄ in pores, increasing the pressure difference during the LSW injection.

When ferrous ion (Fe²⁺) ion is contained in formation water or injection water, Fe²⁺ ion as well as Ca²⁺ and Mg²⁺ can also affect the alteration in wettability. Haugen (2016) experimentally confirmed that Fe²⁺ in brines had been oxidized to Fe³⁺, and it had a greater influence on wettability than Ca²⁺ cation. Also, Fjelde et al. (2017) performed a laboratory experiment to investigate the effect of Fe²⁺ oxidation and cation bridging by Fe³⁺ on wettability, and they observed that low concentration of Fe³⁺ increased the oil wetness of rock surface and altered the wettability to less water-wet. Also, Fe²⁺ ion can react with anions such as SO₄^2–, HCO₃^–, and OH^–, yielding precipitates of FeSO₄, siderite (FeCO₃), and Fe(OH)₂, respectively. Al-Saiari et al. (2008) measured the quantity of FeCO₃ precipitation when the Fe²⁺ to Ca²⁺ molar ratio in the FW was varied and identified that 60% of the Fe²⁺ precipitated. Particularly among the Fe-precipitations, the low solubility of FeCO₃ and Fe(OH)₂ could directly affect the permeability reduction (Stumm and Lee, 1961).

Fe-minerals are present deep underground; for instance, pyrite (FeS₂), which is one of the most common sulfides in sedimentary rocks, can often be found in carbonates that are rich in organic materials (Clavier et al., 1976). When Fe-minerals such as FeS₂, troilite (FeS), and FeCO₃ exist in carbonates, the increase in pH changes during LSW injection can generally lead to the dissolution of Fe-minerals (Hanor, 1994; Liu and Millero, 2002; Rickard and Luther, 2007).

In the case of the acidic reservoir with a low pH condition, FeS₂ can be easily dissolved as mentioned in the following research works. Nicol et al. (2013) performed a laboratory experiment on the dissolution of FeS₂ and confirmed that FeS₂ dissolved to a greater extent in a solution with a low concentration of SO₄^2– such as formation water. Wolfe et al. (2016) observed through a FeS₂ dissolution experiment that FeS₂ dissolved into iron and sulfur within a solution at pH 3; iron predominantly existed in the form of Fe²⁺ ions and sulfur existed as SO₄^2– ions. According to these experimental results, the permeability change could have been caused by the dissolution of FeS₂ when it was present in carbonates. As well, EOR effects could be observed due to the generation of SO₄^2– ions via the FeS₂ dissolution.

Previous studies have focused on the optimum ion composition leading to the maximum oil recovery from a carbonate reservoir by modifying the concentrations of SO₄^2–, Ca²⁺, and Mg²⁺ in LSW. It has been suggested that increasing the concentration of SO₄^2– rather than Ca²⁺ and Mg²⁺ was more effective toward improving the recovery of oil (Fathi et al., 2010; Shariatpanahi et al., 2011; Sohal et al., 2016; Strand et al., 2006; Zhang et al., 2006). However, there has not yet been an analytical study with regard to EOR effects in consideration of precipitation and dissolution due to geochemical reactions when LSWF was applied to the carbonate reservoir containing a large quantity of Fe²⁺ ions in the FW and Fe-minerals in carbonates. Additionally, Fe-minerals have different solubilities depending on the type of mineral; some are insoluble, and thus, the permeability change could have occurred due to the reactions with LSW.

In this study, we analyzed the dissolution and precipitation of Fe-minerals resulting from geochemical reactions during the injection of LSW in the presence of Fe-minerals in carbonates. Also, Fe-mineral dissolution generated SO₄^2– and these ions promoted Fe-precipitation. Since this could lead to a change in permeability, in addition to EOR effects of the LSW injection, there may have been additional effects on improving the oil recovery. Therefore, we intended to explain the relationships between reservoir temperature, SO₄^2– concentration, and oil recovery by analyzing the change in dissolution and precipitation of Fe-minerals depending on the temperature and Fe-mineral content within carbonates.

Governing equation

Darcy’s law governs the flow of fluids in porous media. Multiple components within the aqueous phase can also be attributed to the behavior of fluids, such as dispersion and diffusion. The general partial differential flow equation for the multi-component in the fluids and mineral species is as follows

\frac{\partial}{\partial x} (y_{i l} \frac{ρ_{o} β_{c} A k_{x} k_{r o}}{μ_{o}} \frac{\partial P}{\partial x}) Δ x + q_{l} + V σ_{i, m} = \frac{V_{b}}{α_{c}} \frac{\partial}{\partial t} (\emptyset ρ_{l} S_{l} y_{i l})

(2)

where l = oil, gas, or water and i = 1, 2, …, n_c. n_c represents the number of species in fluids and mineral. As LSW is injected into the formation, the composition of formation water is changed with time. In a commercial compositional reservoir simulator GEM of Computer Modeling Group Ltd, the change of the composition in formation water is then calculated from the flow equations of aqueous phase representing of n_c components in aqueous phase.

The material balance equations for multi-component fluid flow have been provided in an adaptive-implicit manner by Collins et al. (1992) and Siu et al. (1989). Nghiem et al. (2011) have also introduced aqueous phase behavior and chemical reactions within compositional simulations. The material balance finite difference equation for the multiple components and species is as follows

Δ T_{l} y_{i l} Δ P_{l}^{n + 1} + V σ_{i, m}^{n + 1} = \frac{V_{b_{i}}}{α_{c} Δ t} [{(\emptyset ρ_{l} S_{l} y_{i l})}_{i}^{n + 1} - {(\emptyset ρ_{l} S_{l} y_{i l})}_{i}^{n}] - q_{l}

(3)

In this equation, q_l is the source/sink term and Vσ_i,m is the reaction term for rate-dependent reactions. Symbols α_c and β_c are the unit conversion factors, and other symbols are described in Appendix.

The reaction term (Vσ_i,m) of i, m in equations corresponds to the rate of precipitation and dissolution as follows

V σ_{i, m}^{n + 1} = V S_{w} \sum_{i = 1}^{n_{c}} v_{i} r_{i}

(4)

where v_i are the stoichiometry coefficients of component i and in equation (4), r_i is the reaction rate per unit bulk volume of rock, which is calculated through the following equation

r_{i} = A_{i} k_{i} (1 - \frac{Q_{i}}{K_{e q, i}})

(5)

Q_{i} = \prod_{i = 1}^{n_{c}} a_{i}^{v}

(6)

If the reaction rate, r_i, is positive ((Q_i/K_eq,i) < 1), mineral precipitation occurs; if the rate is negative ((Q_i/K_eq,i) > 1), mineral dissolution occurs, where A_i is the reactive surface area and k_i is the rate constant. In this simulation, the initial values of A_i and k_i were set as 100 m²/m³ (A_0i) and 1.58 × 10⁻⁹ mol/m²s (k_0i). These values were initially set as the same for six different minerals. As chemical reactions process into the equilibrium state, the values of A_i and k_i for different minerals were calculated by the equations shown in Table 1. In the case of k_i, since initial value of k_i (k_0i) is extremely small, the calculated values were almost same for different minerals as listed in Table 1. And also, Q_i is the activity product of mineral reaction i, K_eq,i is the chemical equilibrium constant for mineral reaction i, and a_i denotes the activity of component i. A modified Debye–Hückel model is preferred to calculate the activity determined by the molality, temperature, and ionic strength (Mistry and Lienhard, 2013). The chemical equilibrium constant K_eq,i represents the temperature-dependent constant, and tables of the K_eq,i values are provided by Delany and Lundeen (1991) and Kharaka et al. (1988). In equation (5), chemical reaction is progressed until the chemical equilibrium, in which Q_i is equal to K_eq,i (Ma et al., 2015). In this study, chemical reactions for calcite and Fe-minerals with low-salinity injection water containing SO₄^2– are applied and the involved chemical reaction equations are as follows

H^{+} + C a C O_{3} \leftrightarrow C a^{2 +} + H C O_{3}^{-}

(7)

C a S O_{4} \leftrightarrow C a^{2 +} + S O_{4}^{2 -}

(8)

2 H^{+} + F e {(O H)}_{2} \leftrightarrow F e^{2 +} + 2 H_{2} O

(9)

F e S O_{4} \leftrightarrow F e^{2 +} + S O_{4}^{2 -}

(10)

H_{2} O + F e S_{2} \leftrightarrow 0.25 H^{+} + 0.25 S O_{4}^{2 -} + F e^{2 +} + 1.75 H S^{-}

(11)

H^{+} + FeS \leftrightarrow F e^{2 +} + H S^{-}

(12)

H^{+} + F e C O_{3} \leftrightarrow F e^{2 +} + H C O_{3}^{-}

(13)

Table 1.

The reactive surface are (A_i) and the rate constant (k_i) after two pore volumes injected at location Ⓐ .

	Fe(OH)₂	FeCO₃	FeSO₄	FeS	FeS₂	CaCO₃
A_i (m²/m³)	3.76 × 10¹³	1.27 × 10²	4.14 × 10⁵	7.95 × 10	2.70 × 10	9.97 × 10
k_i (mol/m²s)	9.39 × 10^–8	9.39 × 10^–8	9.39 × 10^–8	9.39 × 10^–8	9.39 × 10^–8	9.39 × 10^–8

In the above equations, reaction to the right direction denotes dissolution and precipitation for left direction.

Equations of Ai

A_{i} = A_{0 i} \frac{N_{i}}{N_{0 i}}

where $A_{0 i}$

the reactive surface area at time zero,

N_{i}

the mole of mineral per unit grid block bulk volume at current time, and

N_{0 i}

the mole of mineral per unit grid block bulk volume at time zero.

Equations of ki

k_{i} = k_{0 i} \exp [- \frac{E_{a i}}{R} (\frac{1}{T} - \frac{1}{T_{0}})]

where $k_{0 i}$

the rate constant at time zero,

E_{a i}

the activation energy,

the gas constant (8.314 J/mol K),

the current temperature, and

T₀

reference temperature.

In this study, we used a commercial compositional reservoir simulator GEM of Computer Modeling Group Ltd. for compositional and chemical modelling. In this simulator for describing LSWF, the geochemical reacting mechanisms are selectively considered. Meanwhile, all mechanisms are involved simultaneously in the case of experiment. In this aspect, the simulational work is limited comparing to experimental work in describing the geochemical reactions. The flow equations are discretized using the adaptive-implicit method. The adaptive implicit selects a block’s implicitness dynamically during the computation and is useful complex reservoir. The Jacobian matrix is solved by Incomplete LU factorization followed by the generalized minimal residual method iterative method.

Reservoir model

The numerical one-dimensional simulation model was created with 51 grid blocks of the same width and thickness having a length of 1400 ft. As shown in Figure 1, injection well and production well were set to be at both ends of model. The model was carbonate rock composed of 90% calcite. Its pore volume was 605,895 ft³, the initial oil saturation was 88%, and the original oil in place was 70,114 bbl. The porosity and absolute permeability were 0.27 and 30 md. The initial pressure and temperature were set to 3810 psia and 120°C under isothermal conditions. Since the relative permeability is the most critical factor on oil recovery, which has the greatest uncertainty, we applied the relative permeability from the experiments of Yousef et al. (2011) to this study by performing the history matches with the SO₄^2– concentration (Beretta and Gyftopoulos, 2015; Yousef et al., 2011). Figure 2 illustrates the relative permeability curves during the initial and shifted states after wettability alteration by the LSW injection. These curves would be shifted depending on the concentration of SO₄^2– ions in aqueous, which play a major role in detaching oil and altering the wettability. In the production well, the operating pressure was specified at 1500 psia as boundary condition of right-end of the system. In the injection well, the injection rate of 70 bbl/day was specified as boundary condition at the left-end of the system. When the injection pressure was over the upper limit of 4000 psi, this pressure was set as boundary condition. The LSW was injected at the start of production and the injection rate was set to 1–2 ft/day so that the chemical reaction could occur sufficiently. The period of injection and production was 2 years for which two pore volumes were injected.

Figure 1.

One-dimensional carbonate reservoir system.

Figure 2.

Relative permeability curves used in the simulation when the wettability changes from oil-wet to water-wet (Yousef et al., 2011).

In this paper, in order to construct the simulation model for the application of LSWF to the carbonate reservoir containing Fe²⁺ ions in the FW and Fe-minerals within rock, 910 ppm of Fe²⁺ ions were included in the FW, and FeS₂, FeS, and FeCO₃ were present in the carbonate rock at content of 1.0%, 1.0%, and 0.5%, respectively (Table 2). Table 3 summarizes the ionic compositions and concentrations of the FW and injection water. The data of the FW ware at initial state, which was in equilibrium with the rocks before the injection of LSW. They were based on the ionic compositions of the FW in the Middle East where Fe²⁺ ions were present amid a low pH of 3.2. The total dissolved solids of the FW were as high as 150,000 ppm; the Ca²⁺ concentration was especially high due to the dissolution of calcite (CaCO₃), which accounted for 90% of the carbonate rock. In the case of the injection water, the seawater composition used in the laboratory coreflooding experiment by Yousef et al. (2011) was taken. Although the salinity of the seawater was twice as high as that of typical ocean seawater, it was a third of the FW salinity, so it was suitable for LSW. The injection water was set to a pH 7.8, with reference to the pH of the Persian Gulf.

Table 2.

Fe-mineral content in carbonate rock and the Fe²⁺ ion concentration in the formation water.

Fe-minerals contained in carbonate rock	FeS₂	1.0%
	FeS	1.0%
	FeCO₃	0.5%
Fe²⁺ ion concentration in formation water		910 ppm

Table 3.

Input data for ion composition and concentrations (Yousef et al., 2011).

Ion	Formation water (ppm)	Injection water (ppm)
Na⁺	17,009	18,300
Ca²⁺	37,876	650
Mg²⁺	425	2110
Fe²⁺	910	0
Cl^-	95,291	32,200
SO₄^2-	260	4290
HCO₃^-	0	120
TDS	151,800	57,670

TDS: total dissolved solids.

Results and discussion

pH change analysis

Within this study, a simulation was performed for the application of LSWF in the oil reservoir, where Fe-minerals exist in carbonate rock with Fe²⁺ ions in the FW as given in Table 2. When LSW was injected into the carbonate reservoir, Fe-mineral dissolution and precipitation occurred as the pH increased, which was the main factor influencing the chemical reactions. Thus, we examined the dissolution and precipitation as a factor of pH change. The initial pH of the FW containing 910 ppm of Fe²⁺ ions was 3.2, which was relatively low as shown in Figure 3; however, the pH at the location of Ⓐ near the injection well drastically increased to 4.0 as a result of the LSW injection. At the time of one pore volume injected (1 PVI), the mixing effects with the LSW (pH 7.8) prevailed at location Ⓐ, which promoted the dissolution of Fe-minerals (Chen et al., 2012). However, at the location Ⓑ far from the injection well, the pH for 1 PVI remained in the initial state due to the little effect by LSW injection. However, at the time of two pore volume injected (2 PVI), the pH was stabilized to 4.0 at the locations Ⓐ and Ⓑ since the mixing effects were stabilized by the injection of LSW for a long period of time. It could also be considered that the chemical reactions between ions were nearly equilibrated. Therefore, due to the above phenomena, we quantitatively analyzed the dissolution and precipitation of Fe-minerals at location Ⓐ after 2 PV injected with sufficient chemical reactions.

Figure 3.

Distribution of pH values after low-salinity water injection.

Precipitation and dissolution of minerals

As LSW was injected into the carbonate reservoir, the chemical equilibrium was broken due to differences in the ionic composition and concentration between the FW and injection water, resulting in the dissolution and precipitation of rock. Figure 4 shows the total dissolution and precipitation quantities of Fe-minerals regardless of type at location Ⓐ. The quantity of Fe-precipitation was 264.4 × 10³ gmol and the quantity of Fe-mineral dissolution was 264.8 × 10³ gmol at 2 PVI; there was almost no difference in terms of the total volume in this system. The difference was very small, but the quantity of dissolution or precipitation itself was as large as 264 × 10³ gmol. Thus, it was necessary to analyze the quantity of precipitation and dissolution in detail for each Fe-mineral. This was because the quantity of precipitation and dissolution caused by chemical reactions between the ionic composition of the FW, the injection water, and the mineral constituents of the carbonate rock were different for each type of Fe-minerals. Also, since the solubility or insolubility characteristics of each Fe-mineral were different, the permeability changed accordingly. The precipitation and dissolution quantities for each Fe-mineral were estimated as can be seen in Figure 5. In this figure, a positive value for the change in mineral moles indicated precipitation, while a negative value denoted dissolution. At the time of 2 PVI, a noticeable increase in the quantity of Fe(OH)₂ precipitation and FeS₂ dissolution yielded 220 × 10³ gmol and 200 × 10³ gmol, respectively. These quantities were significantly higher compared to the quantities for the other Fe-minerals, such as FeCO₃, FeSO₄, FeS, and the carbonate, CaCO₃. In the case of Fe(OH)₂, it was not contained within carbonate rock but was generated via precipitation; while FeS₂ existing within the carbonates was dissolved. The aspect for Fe(OH)₂ and FeS₂ precipitation or dissolution relative to each injection time is depicted in Figure 6. The reason for the significantly larger quantities of precipitation and dissolution for these two minerals compared to the other minerals could be comprehended from the equilibrium constants for the chemical reactions. The equilibrium constants could be defined as a function of temperature as follows

\log K_{e q} = a_{0} + a_{1} T + a_{2} T^{2} + a_{3} T^{3} + a_{4} T^{4}

(14)

where K_eq is the equilibrium constant, a_i is the chemical equilibrium coefficient, and T is the reservoir temperature. In this study, the equilibrium constant values and activity product values are summarized in Tables 4 to 6 according to the chemical equilibrium coefficients for each mineral reaction at a reservoir temperature of 120°C (Bethke, 1996). As shown in the results, Fe(OH)₂ precipitated because the saturation index (Q/K_eq), which was a ratio of the activity product to the equilibrium constant, was 6.26E-6 smaller than 1, while the (Q/K_eq) of FeS₂ was 5.03E + 8 and much larger than 1, resulting in the dissolution of FeS₂.

Figure 4.

The quantity of reacted minerals for the Fe-precipitation and Fe-dissolution at location Ⓐ.

Figure 5.

The quantity of precipitation and dissolution for Fe-minerals and calcite at locations Ⓐ and Ⓑ.

Figure 6.

The quantity of reacted minerals for Fe(OH)₂ and FeS₂ at location Ⓐ.

Table 4.

Chemical equilibrium coefficients (a_i) used for calculation of the equilibrium constants (K_eq) (Bethke, 1996).

	a₀	a₁	a₂	a₃	a₄
Fe(OH)₂	1.43 × 10	–6.18 × 10^–2	2.02 × 10^–4	–3.78 × 10^–7	2.19 × 10^–10
FeCO₃	2.54 × 10^–1	–1.94 × 10^–2	9.48 × 10^–6	1.17 × 10^–7	–4.12 × 10^–10
FeSO₄	3.71	–4.32 × 10^–2	7.96 × 10^–6	2.49 × 10^–7	–7.60 × 10^–10
FeS	–3.67	–2.87 × 10^–3	–5.38 × 10^–5	2.42 × 10^–7	–5.19 × 10^–10
FeS₂	–2.65 × 10	8.16 × 10^–2	–4.05 × 10^–4	1.15 × 10^–6	–1.66 × 10^–9
CaCO₃	2.07	–1.43 × 10^–2	–6.06 × 10^–6	1.46 × 10^–7	–4.19 × 10^–10

The reaction for the precipitation of Fe(OH)₂, possessing an enormously large equilibrium constant, can be seen in equation (9) as being independent of the SO₄^2– ions. On the other hand, FeS₂ dissolved when contacting the injection water, resulting in the generation of 0.25 mol of SO₄^2– ions (equation (11)). The FeS₂ dissolution is also attributed to the generation of hydrogen sulfide (H₂S) which can cause the problems for souring of oil (Al-Kindi et al., 2008). However, in this simulation study, the amount of H₂S was not enough to occur the souring problem during the period of production. Also, we focused on the effect of mineral precipitation and dissolution on the recovery of oil. In wettability alteration mechanism, SO₄^2– ions played a major role in enhancing the oil recovery by detaching oil that had attached on the carbonate rock surface forming an oil-wet condition and by causing the alteration in wettability. The initial SO₄^2– concentration of the FW in this study was 260 ppm and that of LSW was 4290 ppm. As LSW was injected into the carbonate reservoir where FeS₂ did not exist, the SO₄^2– concentration increased to about 2300 ppm due to simple mixing effects without the additional generation of SO₄^2– ions (Figure 7). However, in the presence of FeS₂ in carbonate rock, SO₄^2– ions were released from the dissolution of FeS₂ as LSW was injected and the additional SO₄^2– ion concentration reached up to 960 ppm, which played a notably important role with regard to improving the efficiency of the LSWF method. Therefore, to analyze these reactions in more detail, we examined the occurrence of SO₄^2– ions depending on the temperature and content of FeS₂, which were the primary factors influencing the above reactions.

Figure 7.

The occurrence of SO₄^2– ions due to the FeS₂ dissolution at location Ⓐ.

In order to investigate the effect of the reservoir temperature and FeS₂ content on the generation of SO₄^2– from the FeS₂ dissolution, we first performed a simulation using K_eq in Table 5 for reservoir temperatures from 50 to 120°C in intervals of 10°C. After 2 PV was injected, the quantity of dissolved FeS₂ increased by 6.4 times when the temperature was 120°C compared to 50°C, which indicated that higher reservoir temperatures yielded more SO₄^2– ions due to the dissolution of FeS₂, thereby improving the EOR efficiency through LSWF. Then, simulations for the effects of FeS₂ content were performed when FeS₂ was contained within carbonate rock from 0 to 8.5%, over 0.5% intervals. Figure 8 shows the additional SO₄^2– ions from the FeS₂ dissolution at the time of 2 PV injected, except for simple mixing effects due to the injection of LSW. As a result, the SO₄^2– concentration was close to the maximum when 7% or more FeS₂ existed within the carbonate reservoir of 120 C. Meanwhile, the quantity of generated SO₄^2– at 50 C was less than that at 120 C and SO₄^2– ions did not occur any longer even when the content of FeS₂ was 1% or more. Therefore, since the EOR effect due to SO₄^2– ions was limited at certain temperatures and FeS₂ content levels, it is necessary to pay attention to the determination of the SO₄^2– concentration for the design of PDI compositions in LSW.

Table 5.

Chemical equilibrium constants (K_eq) for various temperatures.

	Equilibrium constant (K_eq)
	50°C	60°C	70°C	80°C	90°C	100°C	110°C	120°C
Fe(OH)₂	4.45E+11	1.66E+11	6.60E+10	2.78E+10	1.24E+10	5.83E+09	2.87E+09	1.47E+09
FeCO₃	2.10E–01	1.40E–01	9.45E–02	6.44E–02	4.43E–02	3.08E–02	2.16E–02	1.53E–02
FeSO₄	3.95E+01	1.55E+01	6.19E+00	2.52E+00	1.04E+00	4.39E–01	1.88E–01	8.19E–02
FeS	1.21E–04	1.03E–04	8.71E–05	7.28E–05	6.05E–05	4.99E–05	4.10E–05	3.35E–05
FeS₂	4.78E–24	1.39E–23	3.64E–23	8.63E–23	1.87E–22	3.75E–22	6.99E–22	1.22E–21
CaCO₃	2.27E+01	1.65E+01	1.20E+01	8.84E+00	6.53E+00	4.85E+00	3.62E+00	2.72E+00

Figure 8.

The additional SO₄^2– ions due to the FeS₂ dissolution depending on the FeS₂ content at location Ⓐ.

Table 6.

Activity product at 120°C after two pore volumes injected.

	Fe(OH)₂	FeCO₃	FeSO₄	FeS	FeS₂	CaCO₃
Activity product (Q)	9.20 × 10³	3.58 × 10^–5	1.24 × 10^–7	1.88 × 10^–4	6.14 × 10^–13	1.98 × 10^–3
Saturation index (Q/K_eq)	6.26 × 10^–6	2.34 × 10^–3	1.51 × 10^–6	5.61	5.03 × 10⁸	7.28 × 10^–4

Permeability change and EOR effect analysis

When LSW was injected into the carbonate reservoir containing Fe-minerals, the precipitation or dissolution that occurred due to chemical reactions caused a permeability change (Figure 9). The simulation results analyzing this phenomenon showed that the pore volumes decreased by 250 ft³ and increased by 270 ft³ due to precipitation and dissolution including calcite dissolution, respectively, after 2 PV injections at location Ⓐ. Among the volumes, the volume reduction due to Fe-precipitation was 250 ft³ and the volume increase due to the dissolution of Fe-minerals was 210 ft³, with the exceptions of the precipitation and dissolution of calcite (CaCO₃). This indicated that the Fe-minerals precipitated more easily as opposed to dissolution. The pore volume change due to the dissolution and precipitation of Fe²⁺ is 40 ft³, which is 6.6 × 10⁻⁵ times the model total pore volume 605,895 ft³. This is almost negligible with respect to the total pore volume. Accordingly, the porosity was estimated as 27.09%, in which the change of porosity is also negligible; permeability was calculated using the Kozeny–Carman equation as follows

\frac{k}{k^{0}} = {(\frac{\emptyset}{\emptyset^{0}})}^{3} {(\frac{1 - \emptyset^{0}}{1 - \emptyset})}^{2}

(15)

Figure 9.

The estimated volumes of precipitation and dissolution at location Ⓐ.

This equation is one of the most widely accepted and simplest model for the permeability–porosity relationship, which provides a link between media properties and flow resistance in pore channels (Carman, 1937; Kozeny, 1927). The estimated permeability depending on the temperature and FeS₂ content is summarized in Table 7. As shown in the results, both quantities of precipitation and dissolution were very large; however, there was little difference between the two. Thus, it was confirmed that the permeability did not change from the initial value of 30 md. Also, the permeability did not change even when the reservoir temperature was lowered to 50°C or the FeS₂ content was increased to a value as high as 8.5%.

Table 7.

Permeability change at location Ⓐ due to precipitation and dissolution after two pore volumes injected.

T/FeS₂	Precipitation (gmol)	Dissolution (gmol)	Initial permeability (md)	Changed permeability (md)
50°C/1%	4.23 × 10⁴	4.97 × 10⁴	30	30.06
120°C/1%	2.64 × 10⁵	3.11 × 10⁵	30	30.39
120°C/8.5%	1.97 × 10⁵	2.45 × 10⁵	30	30.83

Finally, we investigated the EOR effect when LSWF was applied to the carbonate reservoir. In our system, there was almost no difference between the quantities of Fe-precipitation and Fe-mineral dissolution, it seems that the concentration of Fe²⁺ ion was almost not changed in this system, which would not affect the wettability of rock surface. Additionally, since Fe²⁺ was contained only in the formation water as 910 ppm, not in injection water, the concentration of Fe²⁺ was reduced up to 11 ppm by injecting the LSW of 0 ppm. In this aspect, we assumed that the effect of Fe²⁺ on wettability alteration was considered to be negligible. Therefore, in this paper, we mainly focused on the effect of precipitation and dissolution of Fe-minerals on oil recovery. In the case of carbonate rock containing FeS₂ as a Fe-mineral, as FeS₂ was dissolved, SO₄^2– ions were generated. These ions detached oil from the rock surface, and consequently, more oil was produced. As the results shown in Figure 10, the oil recovery for carbonates without FeS₂ was 69.06%, which was 12.41% greater than 56.65% for conventional WF due to the injection of LSW containing SO₄^2– ions. However, 76.67 and 76.70% were recovered from carbonates containing 1 and 8.5% FeS₂. This was much higher than that for conventional WF. Figure 11 shows schematically overall process in the absence and presence of FeS₂. In the case of its absence, some SO₄^2– ions in injection water attach on the carbonate rock surface, then oil is detached from rock surface. On the other hand, when FeS₂ is contained in carbonate rock, FeS₂ is dissolved releasing SO₄^2– ions near the rock surface. Therefore, more SO₄^2– ions can attach on rock surface causing the detachment of more oil. However, additional oil was not recovered for FeS₂ contents above 1%. This was because the total aqueous SO₄^2– concentration equilibrated to 3700 ppm after 2 PV injected when the FeS₂ content was 1% or more; thus, additional oil was not produced by the SO₄^2– ions. Since the equilibrium SO₄^2– ion concentration was 2300 ppm in the absence of FeS₂, this difference in the SO₄^2– concentration led to an additional 7.61% recovery of oil.

Figure 10.

A comparison of the oil recovery depending on the FeS₂ content.

Figure 11.

Schematic representation for oil detachment due to additional SO₄^2– ions from FeS₂.

Based on the above results, when applying LSWF to the carbonate reservoir containing Fe-minerals, we proposed an oil recovery relationship as a function of the temperature and SO₄^2– concentration in order to determine the optimal SO₄^2– concentration with regard to designing the PDI composition in LSW. A correlation between the oil recovery and SO₄^2– ion concentration, which was the most important PDI in LSW, and the reservoir temperature, which greatly affected the precipitation and dissolution of Fe-minerals, is represented in Figure 12.

Figure 12.

The oil recovery in relation to temperature and SO₄^2–.

Summary and conclusions

In this study, we performed several simulations to analyze the EOR effects focusing on the dissolution of Fe-minerals and Fe-precipitation when LSW containing SO₄^2– was injected into carbonate oil reservoirs.

From the results investigating precipitation and dissolution of Fe-minerals, it was found that the magnitude of precipitation and dissolution due to chemical reactions during LSW injections was enormously large, and the quantities were quite different according to the type of Fe-minerals. Among the Fe-minerals, the amounts of Fe(OH)₂ precipitation and FeS₂ dissolution were noticeably large in this system compared to FeS, FeSO₄, and FeCO₃, i.e. Fe(OH)₂ not contained in carbonate rock was precipitated, which is insoluble. On the other hand, FeS₂ contained in the rock was dissolved. This could be attributed by the saturation index criteria which was calculated by the ratio of activity product to equilibrium constant in the chemical reactions. As mentioned above, since the solubility characteristics of each Fe-mineral are different, it is essential to analyze precipitation or dissolution for each Fe-mineral individually, in which these phenomena yielded a permeability change (increase or decrease). However, in the case of this system, there was almost no difference between precipitation and dissolution in terms of total quantities of Fe-mineral, and consequently permeability was not changed.

From the analysis results for the SO₄^2– ions released from the process of precipitation and dissolution, in the dissolving process of FeS₂, the additional SO₄^2– ions were released differently depending on the content of FeS₂. However, because the generation of SO₄^2– ion was limited at certain level of FeS₂ content in carbonate rock, it is necessary to pay attention to the determination of SO₄^2– concentration for the design of PDI compositions in the injection water. Ultimately, in the investigation of EOR efficiency, oil production was enhanced due to additional SO₄^2– ions generated from the FeS₂ dissolution.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by a grant funded as part of the project “Development of IOR/EOR technologies and field verification for carbonate reservoir in UAE” by the Korean Government Ministry of Trade, Industry and Energy (MOTIE) (No. 20152510101980).

Appendix

References

Al-Kindi

Prince-Wright

Walsh

et al . (2008) Challenges for waterflooding in a deepwater environment. SPE Production & Operations 23(3): 404–410.

Al-Saiari

Yean

Tomson

et al . (2008) Iron (II)-calcium carbonate: precipitation interaction. In: SPE international oilfield scale conference, Aberdeen, UK, 28–29 May 2008, SPE Paper 114064.

Al-Shalabi

Sepehrnoori

Delshad

(2014) Mechanisms behind low salinity water injection in carbonate reservoirs. Fuel 121: 11–19.

Beretta

Gyftopoulos

(2015) What is a chemical equilibrium state? Journal of Energy Resources Technology 137(2): 4.

Bethke (1996) Geochemical Reaction Modeling: Concepts and Applications. New York: Oxford University Press.

Carman

(1937) Fluid flow through granular beds. Institution of Chemical Engineering 15: 150–166.

Chen

Qui

Fang

et al . (2012) Removal mechanism of antibiotic metronidazole from aquatic solutions by using nanoscale zero-valent iron particles. Chemical Engineering Journal 181–182: 113–119.

Clavier

Heim

Scala

(1976) Effect of pyrite on resistivity and other logging measurements. In: SPWLA 17th annual logging symposium, Denver, Colorado, 9–12 June 1976.

Collins

Nghiem

Y-K

et al . (1992) An efficient approach to adaptive-implicit compositional simulation with an equation of state. SPE Reservoir Engineering 7(2): 259–264.

10.

Delany

Lundeen

(1991) The LLNL thermochemical data base – revised data and file format for the EQ3/6 package. Technical Report. Contract NO. W-7405-ENG-48, Lawrence Livermore National Laboratory, California, USA.

11.

Fathi

Austad

Strand

(2010) Smart water as a wettability modifier in chalk: the effect of salinity and ionic composition. Energy & Fuels 24(4): 2514–2519. https://doi.org/10.1021/ef901304m.

12.

Fjelde

Omekeh

Haugen

(2017) Effect of ferrous ion Fe2+ on wettability. In: 79th EAGE conference and exhibition, Paris, France, 12–15 June 2017.

13.

Hanor

(1994) Origin of saline fluids in sedimentary basins. Geological Society of London Special Publications 78(1): 151–174.

14.

Haugen

(2016) Characterization of wettability alteration by flotation. Master’s Thesis, University of Stavanger, Norway.

15.

Jalilian

Pourafshary

Sola

et al . (2017) Optimization of smart water chemical composition for carbonate rocks through comparison of active cations performance. Journal of Energy Resources Technology 139(6): 9.

16.

Kharaka

Gunter

Aggarwal

et al . (1988) SOLMINEQ. 88: a computer program for geochemical modeling of water-rock interactions. U.S. Geological Survey. Water-Resources Investigations Report 88–4227. California: Menlo Park.

17.

Kozeny

(1927) Uber kapillare leitung der wasser in boden. Royal Academy of Science 136: 271–306.

18.

Lager

Webb

Black

CJJ

(2007) Impact of brine chemistry on oil recovery. In: 14th European symposium on improved oil recovery, Cairo, Egypt, 22–24 April 2007.

19.

Liu

Millero

(2002) The solubility of iron in seawater. Marine Chemistry 77(1): 43–54.

20.

Liu

Cheng

(2015) New relationship between resistivity index and relative permeability. Journal of Energy Resources Technology 137(3): 7.

21.

McGuire

Chatham

Paskvan

et al . (2005) Low salinity oil recovery: an exciting new EOR opportunity for Alaska’s north slope. In: SPE western regional meeting, Irvine, CA, 30 March–1 April 2005, SPE Paper 93903. https://doi.org/10.2118/93903-MS.

22.

Mahani

Keya

Berg

et al . (2015) Insights into the mechanism of wettability alteration by low-salinity flooding (LSF) in carbonates. Energy & Fuels 29(3): 1352–1367.

23.

Mahmoud

Nasr-El-Din

(2014) Challenges during shallow and deep carbonate reservoirs stimulation. Journal of Energy Resources Technology 137(1): 8.

24.

Mistry

Lienhard

VJH

(2013) Effect of nonideal solution behavior on desalination of a sodium chloride solution and comparison to seawater. Journal of Energy Resources Technology 135(4): 10.

25.

Morrow

Tang

Valat

et al . (1998) Prospects of improved oil recovery related to wettability and brine composition. Journal of Petroleum Science and Engineering 20(3–4): 267–276.

26.

Nghiem

Shrivastava

Kohse

(2011) Modeling aqueous phase behavior and chemical reactions in compositional simulation. In: SPE reservoir simulation symposium, Woodlands, Texas, 21–23 February 2011, SPE Paper 141417. https://doi.org/10.2118/141417-MS.

27.

Nicol

Miki

Basson

(2013) The effects of sulphate ions and temperature on the leaching of pyrite. 2. Dissolution rates. Hydrometallurgy 133: 182–187.

28.

Rickard

Luther

(2007) Chemistry of iron sulfides. Chemical Reviews 107(2): 514–562.

29.

Salamat

Perez

CAR

Hidrovo

(2016) Performance characterization of a capacitive deionization water desalination system with an intermediate solution and low salinity water. Journal of Energy Resources Technology 138(3): 5.

30.

Shariatpanahi

Strand

Austad

(2011) Initial wetting properties of carbonate oil reservoirs: effect of the temperature and presence of sulfate in formation water. Energy & Fuels 25(7): 3021–3028.

31.

Siu

Rozon

Y-K

et al . (1989) A fully implicit thermal wellbore model for multi-component fluid flows. In: SPE California regional meeting, Bakersfield, California, 5–7 April 1989, SPE Paper 18777, https://doi.org/10.2118/18777-MS.

32.

Sohal

Thyne

Søgaard

(2016) Review of recovery mechanisms of ionically modified waterflood in carbonate reservoirs. Energy & Fuels 30(3): 1904–1914.

33.

Standnes

Austad

(2000) Wettability alteration in chalk. 2. Mechanism for wettability alteration from oil-wet to water-wet using surfactants. Journal of Petroleum Science Engineering 28(3): 123–143.

34.

Strand

Høgnesen

Austad

(2006) Wettability alteration of carbonates – effects of potential determining ions (Ca²⁺ and SO₄^2–) and temperature. Colloids and Surfaces A: Physicochemical and Engineering Aspects 275(1–3): 1–10.

35.

Stumm

Lee

(1961) Oxygenation of ferrous iron. Industrial & Engineering Chemistry 53: 143–146.

36.

Wolfe

Stewart

Capo

et al . (2016) Iron isotope investigation of hydrothermal and sedimentary pyrite and their aqueous dissolution products. Chemical Geology 427: 73–82.

37.

Wolthers

Charlet

Cappellen

(2008) The surface chemistry of divalent metal carbonate minerals; a critical assessment of surface charge and potential data using the charge distribution multi-site ion complexation model. American Journal of Science 308: 905–941.

38.

Yassin

Ayatollahi

Rostami

et al . (2015) Micro-emulsion phase behavior of a cationic surfactant at intermediate interfacial tension in sandstone and carbonate rocks. Journal of Energy Resources Technology 137(1): 12.

39.

Yousef

Al-Saleh

Al-Kaabi

et al . (2011) Laboratory investigation of the impact of injection-water salinity and ionic content on oil recovery from carbonate reservoirs. SPE Reservoir Evaluation & Engineering 14(5): 578–593.

40.

Yue

Wang

(2015) Feasibility of waterflooding for a carbonate oil field through whole-field simulation studies. Journal of Energy Resources Technology 137(6): 8.

41.

Zhang

Tweheyo

Austad

(2006) Wettability alteration and improved oil recovery in chalk: the effect of calcium in the presence of sulfate. Energy & Fuels 20(5): 2056–2062.

42.

Zhang

Tweheyo

Austad

(2007) Wettability alteration and improved oil recovery by spontaneous imbibition of seawater into chalk: impact of the potential determining ions Ca²⁺, Mg²⁺, and SO₄². Colloids and Surfaces A: Physicochemical and Engineering Aspects 301(1–5): 199–208.

43.

Zhang

Sarma

(2012) Improving waterflood recovery efficiency in carbonate reservoirs through salinity variations and ionic exchanges: a promising low-cost “smart-waterflood” approach. In: Abu Dhabi international petroleum exhibition and conference, Abu Dhabi, UAE, 11–14 November 2012, SPE Paper 161631.

44.

Zhou

Yang

(2017) Scaling criteria for waterflooding and immiscible CO₂ flooding in heavy oil reservoirs. Journal of Energy Resources Technology 139(2): 13.

Enhanced oil recovery efficiency of low-salinity water flooding in oil reservoirs including Fe 2+ ions

Abstract

Keywords

Introduction

Governing equation

Equations of Ai

Equations of ki

Reservoir model

Results and discussion

pH change analysis

Precipitation and dissolution of minerals

Permeability change and EOR effect analysis

Summary and conclusions

Footnotes

Declaration of conflicting interests

Funding

Appendix

References