Physicochemical Constraints on Surfactant Blends ... - ACS Publications

Nov 30, 2016 - conditions. Offshore reservoirs challenge chemical flooding, e.g., low-tension and foam flooding, because of the combined hardness and ...
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Physicochemical Constraints on Surfactant Blends under Harsh Conditions and Evaluation of a Proposed Solution Griselda Garcia-Olvera,† Teresa M. Reilly,‡ Teresa E. Lehmann,¶ and Vladimir Alvarado*,†,‡ †

Department of Petroleum Engineering, ‡Department of Chemical Engineering, and ¶Department of Chemistry, University of Wyoming, Laramie, Wyoming 82071, United States ABSTRACT: Chemical-enhanced oil recovery has been applied successfully in reservoirs with mild salinity and temperature conditions. Offshore reservoirs challenge chemical flooding, e.g., low-tension and foam flooding, because of the combined hardness and salinity of seawater along with the characteristics of the reservoir connate brine. These physicochemical conditions impose severe limitations on adequate phase behavior for most commercial surfactants. The purpose of this research is to analyze surfactant phase behavior for scenarios with seawater as the main carrying fluid for surfactant systems for harsh conditions similar to those in heavy-oil reservoirs in the Gulf of Mexico. We also aim at testing a recently developed surfactant characterization technique using a recently published NMR protocol [Garcia-Olvera et al., Energy Fuels, 2016, 30, 63]. In this technique, NMR spectra of surfactants, cosurfactants, and polymers are calibrated to enable analysis of individual components in chemical blends. Critical micelle concentration was estimated from further interpretation of the calibrated NMR data. Thermal stability and solubility for a family of ENORDET surfactants and an Alpha Foamer provided by two chemical companies were analyzed. Tests were conducted using a range of simulated connate brines, of up to 100 000 ppm of salinity and up to 20% of Ca−Mg hardness, and seawater compositions. Phase behavior experiments were run to determine which blend composition and brine salinity would enable the desired phase behavior. A medium-gravity oil thoroughly studied in our lab was selected for phase behavior studies. Finally, corefloods were completed to evaluate the additional oil recovery for surfactant−polymer and polymer evaluated scenarios. Some surfactants were disregarded for further analysis because of their lack of thermal stability, i.e., dropout from solution. In some cases, cosurfactants (e.g., N25) and cosolvents were added to increase solubility in surfactant blends with a high divalent ion content, which in some cases was insufficient to stabilize the blends. Phase behavior experiments show that some surfactants did not yield type III microemulsions and therefore were disregarded for low-tension flooding applications. NMR data for surfactants, cosurfactants, and polymers yielded good results to evaluate chemical concentrations even when the NMR spectra for different blend components overlaid significantly. Softening of high-salinity brines indeed improved microemulsion volume in the phase behavior tests, as demonstrated in the coreflooding results of up to 87% total recovery factor. However, this strategy is shown through geochemical analysis to be risky for more reactive reservoir lithologies, where dissolution and precipitation events are prompted by reduction in hardness in the injection brine.

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INTRODUCTION

High potential for application of surfactant (S), surfactant− polymer (SP), and alkali−surfactant−polymer (ASP) processes have been demonstrated for sandstone reservoirs with mild salinity and temperature conditions.4 The situation is different for carbonate reservoirs under harsh conditions with only a handful of studies conducted. Surfactants may be classified according to the ionic nature of the headgroup as anionic, cationic, nonionic, or zwitterionic.5 Anionic surfactants are generally evaluated and used in cEOR in sandstone formations because of their low adsorption, resulting from the typical negative charge of sandstone surfaces. In many cases, nonionic surfactants are used as cosolvents to improve solubility in phase behavior experiments. They tolerate high salinity, though the interfacial tension (IFT) is reduced in a limited way. Cationic surfactants are recommended for carbonate formations because of the repulsion between the surfactant head charge and positively charged carbonate surfaces. Also, they may change carbonate wettability toward water wetness.

Crude oil, natural gas, and coal accounted for 85% of global energy consumption in 2015. The U.S. Energy Information Administration (2015) reports that the energy consumption in the United States grew at a moderate rate over the projection, with reductions in energy intensity resulting from improved technologies.2 In the United States, 36% of the total energy consumed in 2013 comes from petroleum, and the forecast is 33% by 2040. Regardless of the decrement, petroleum and natural gas still support more than 60% of the total energy consumption, and this is projected to continue until 2040. This clearly highlights the need to further production, particularly through increased production efficiency in mature fields. Carbonate reservoirs, i.e., limestone, chalk, and dolomite, contain over 60% of the world’s remaining conventional oil reserves and account for over 30% of the world’s daily oil production. However, the oil recovery in carbonates is low, probably below 35% on average.3 On the other hand, a considerable volume of these carbonates are located offshore, where seawater is the main source for waterflooding and pressure maintenance and for use as carrying fluid for chemical-enhanced oil recovery (cEOR) components. © XXXX American Chemical Society

Received: June 9, 2016 Revised: November 28, 2016 Published: November 30, 2016 A

DOI: 10.1021/acs.energyfuels.6b01413 Energy Fuels XXXX, XXX, XXX−XXX

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although the total oil recovery was not significant because many wells failed, despite outstanding performance from the remaining wells. The mechanism proposed was wettability alteration, and the IFT changes were irrelevant.16 On the other hand, mobility control is an important concept in cEOR. Mobility is defined for each fluid phase as the effective fluid permeability to viscosity ratio. However, the specific value depends on fluid saturation. In theory, during flooding, the displacing fluid mobility upstream should be less or at least equal to the displaced fluid downstream. If this does not occur, viscous fingering can arise, and as consequence, sweep efficiency is impaired. In carbonated formations, generally containing fractures and vugs, the mobility control becomes critical. To solve or at least minimize this problem, it might be necessary to decrease the displaced fluid viscosity or to increase the displacing fluid viscosity. The latter is usually accomplished through the addition of water-soluble polymers. Viscosity is the most important parameter for polymer solutions. Some important factors that affect polymer rheology are polymer concentration, salinity, shear rate, pH, and temperature.4 The polymer solution viscosity increases exponentially as a function of polymer concentration. Solution viscosity decreases as the salinity increases, and divalent cations have a larger effect than monovalent cations at the same concentration. Practically, viscosity decreases at higher shear rate. In general, a polymer solution acts as a pseudoplastic fluid, except at high and low shear rates.17 Carreau proposed a general model in which polymer viscosity behaves like a Bingham fluid at low shear rate; it acts as a pseudoplastic fluid for intermediate shear rates; for high shear rate (approaching infinity), the polymer viscosity is taken as that of water.18 The value of pH affects hydrolysis, and adding alkali eventually results in a decrease in the viscosity, though the effect has been shown to depend more strongly on salinity, rather than alkalinity.19 Finally, when the temperature is increased, the activity of the polymer chains is enhanced and the friction between molecules is reduced, and as a result, the flow resistance and viscosity are reduced. Losses of polymer during flooding may affect cEOR projects. The polymer retention is associated with adsorption, mechanical trapping, and hydrodynamic retention. The first two effects occur only in flow through porous media. Adsorption is due to interactions between polymer molecules and the rock surface. In this sense, the molecules bind the rock surface by physical adsorption, van der Waals forces, and hydrogen bonding. Mechanical trapping depends on the pore size distribution and the polymer molecular weight and structure. In general, polymer flooding might be risky in low-permeability formations, as the area around the injection site may be plugged excessively. Published experimental results show that the static adsorption using ground rock, i.e., in the absence of flow, does not correlate well to polymer concentration in dynamic adsorption tests (in the presence of flow). These tests differ significantly for two main reasons: first, the large difference in specific surface area and second, the mechanical retention in corefloods.4 A prime example of an offshore polymer pilot test in Bohai Bay, China has been documented in several papers.8,20,21 Seawater was injected for eight years prior to the injection of 0.037 pore volumes (PV) of polymer solution. The production wells responded after 10 months, as shown by a decrease in watercut and the increase in oil rate. The pilot test reported limitations such as the large well spacing and limited work area

The critical micelle concentration (CMC) is an important characteristic of a surfactant. Adding surfactant causes the IFT to decrease sharply, reaching a minimum at CMC, remaining constant or slightly increasing at higher surfactant concentrations. In our previous paper,1 we observed that for a surfactant blend, the CMC is reached at lower concentration when present in a blend than when each surfactant is by itself in solution. The surfactant molecule lowers the IFT between oil and water as to allow emulsification. The emulsions depend on surfactant type and concentration, addition of cosolvents, hydrocarbons, brine salinity, equivalent alkane carbon number (EACN), temperature, and to a lesser degree pressure.4,6 The most frequently alluded microemulsion classification was first proposed by Winsor (1954) as Winsor type I, II, and III.7 For type I, the surfactant is preferentially soluble in water and oil in water (o/w) microemulsions form. In microemulsions type II, the surfactant resides mainly in the oil phase. A type III microemulsion is a three-phase system where a surfactant-rich middle phase coexists with both excess water and oil. The latter is often referred to as bicontinuous microemulsions, because they are thought to form lamellas with the two phases. In low-tension flooding projects, the use of alcohols or cosolvents is common. They are added to enhance solubility, minimize occurrence of gels and liquid crystals, lower equilibrium time, and reduce microemulsion viscosity, and the surfactant-to-co-solvent ratio is usually 2−3. However, with alcohols, the IFT of the formulation rises.8 High carbon number crude oils require higher carbon number surfactants to solubilize the oil and hence cosurfactants or cosolvents to achieve the desired phase behavior.9 In many cases, solubility is reached by decreasing the surfactant concentration without the need to use cosolvents or a combination of both surfactants and cosolvents. Because of the well-known relationship between the microemulsions, phase behavior, and IFT, the phase behavior of surfactant−brine−oil system at a given temperature is an important factor in interpreting the performance of oil recovery in low-tension designs. The optimum formulation can be found by analyzing the three-phase behavior of oil−brine−surfactants systems in bottle tests. Surfactant retention depends upon several variables such as surfactant structure, mineralogy, salinity and pH. For instance, in carbonate reservoirs the process is complicated by the complex pore structure that leads to high retention. One of the most difficult problems to solve in surfactant flooding projects is the large loss of surfactants in the formation during flooding. The suggestions to decrease surfactant adsorption are divided into three main categories: sacrificial agents injected before the surfactant slug,10 chelating agents,11 or addition of alkali to the formulation. However, these may affect considerably the economic performance of the project, which is compounded by undesirable reactions with the rock, and as a consequence not all reservoirs are candidates for this process.12 There are a few reported cEOR projects in carbonate reservoirs,13 such as the Mauddud carbonate reservoir in the Middle East. Results of the surfactant injection in six wells showed a residual oil saturation (Sor) reduction of the order of 10−15%.14 Another example is the Yates Field in Texas. In the latter case, surfactant injection in the oil/water transition zone increased oil recovery as the result of IFT reduction and wettability alteration.15 The Cottonwood Creek Field in Wyoming had 23 wells stimulated with surfactants, and the production results exhibited a general trend toward increased oil recovery, B

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Energy & Fuels Table 1. Brine Characteristics at 25°C brine

TDS (ppm)

density (g/cm3)

pH

Ca (ppm)

Mg (ppm)

Ca−Mg/TDS (%)

ionic strength (M)

CW SW

136 370 35 220

1.094 1.027

6.44 7.72

13 760 480

1 458 1 044

11 4

2.56 0.65

on the platform. Later, this field was subject to an SP process. The oil production was increased from 300 to 400 BPD, and the watercut decreased from 80 to 70% to date. There are a few polymer projects in carbonates, with some showing good results. For example, the largest polymer injection project in the United States was conducted in the Eliasville Field, a limestone formation with 165 000 ppm connate water salinity. The project involved polymer injection during 34 months amounting to 0.129 PV in total. The oil production increased from 375 to 1622 BOPD. The estimated effectiveness of the flood was 0.46 barrels of oil per pound of polymer injected.13 To develop an optimal formulation for SP projects, both in efficiency and cost, there are thousands of possible combinations of surfactants, cosurfactants, cosolvents, and polymers and a range of possible salinities and hardness at reservoir temperature for proper evaluation. Extensive evaluation could take a long time and be expensive. Therefore, experience, scientific understanding of the products, and evidence from the literature play an important role in this analysis. It is important for the SP slug to be stable, clear, and without phase separation or precipitation.22 Otherwise, the injection will be less efficient, and in the worst cases, injectivity reduction is associated with formation plugging. Surfactant blends have to produce ultralow IFT, and thereby good microemulsions in phase behavior experiments, including large phase solubilization. They also need to be stable while in the reservoir and travel long distances with low retention under low pressure gradient. All these evaluations are necessary before coreflooding takes place to evaluate additional oil recovery due to chemical processes. The purpose of this paper is two-fold. First, we aim at analyzing the impact of physicochemical conditions specific of seawater and highly saline reservoir brine for heavy oil of a group of reservoirs in the Gulf of Mexico on formulations for low-tension applications such as SP. Second, we examine our recently developed technique for surfactant analysis based on nuclear magnetic resonance.1 We demonstrate that it is possible to develop adequate surfactant formulations, but challenges remain given the lack of availability of efficient surfactants and harsh conditions offshore.

Rocks. Indiana limestone (IL), an outcrop carbonate from Kocurek Industries, Inc., was selected for corefloodings. Routine core analysis was first conducted. Dimensions, porosity, and pore volumes (PV) are listed in Table 2. Additionally, ground Berea Table 2. Basic Core Sample Characteristics core

length (cm)

diameter (cm)

PV (cc)

porosity (%)

IL-GBSP1 IL-GBP1

26.3 27.5

3.77 3.77

48.01 48.63

16.29 15.78

sandstone and Indiana limestone were used for the static adsorption tests. Surfactants and Polymers. The following chemical products were selected and analyzed in this research: Surfactants. An anionic foaming agent, Alpha Foamer (ammonium alkyl ether sulfate), from Stepan Company; four anionic internal olefin sulfonate (IOS) surfactants ENORDET O242 (IOS C20-24), ENORDET O332 (C15-18), ENORDET O342 (C19-23), and ENORDET O352 (C24-28); and two nonionic NEODOL surfactants, N91-8 (C9-11 8EO), and N25-12 (C12-15 12 EO) from Shell Chemicals. The composition of the IOS family of surfactants are described by Barnes et al. (2010).23 Cosolvents. Secondary butyl alcohol (SBA) and + isobutyl alcohol (IBA) from Sigma-Aldrich. Polymer. Hydrolyzed polyacrylamides (HPAm), Flopaam 3630S, from SNF.

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EXPERIMENTAL METHODS AND EQUIPMENT

Density. Density is measured with an Anton Paar density meter, model 4500. The instrument is cleaned with toluene and methanol and dried with air after crude oil measurments and rinsed with DW and airdried after brine measurements. After the instrument is cleaned, the required temperature is set up and the measuring cell is completely filled with the fluid, avoiding air bubbles. A minimum of three measurements are completed to develop a confidence interval. Bulk Rheology. The viscosity of the crude oil is measured using an ARES rheometer, TA Instruments. Parallel-plate geometry with 50 mm stainless plates at a gap of 0.9 mm is used to measure shear viscosity in frequency-sweep tests. The linear viscoelastic region is determined running a strain-sweep test at 10 s−1. Temperature is controlled using the bottom Peltier plate in the rheometer, and the viscosity is reported at 10 s−1. Aqueous Stability. The aqueous phase (surfactants and brine) is poured in Pyrex bottles and placed in an oven to track precipitation or changes in the solution for several days at different temperatures. Photographs and annotations were recorded to examine the stability of the samples at different temperatures. Phase Behavior. Phase behavior experiments quantitatively determine the oil and water solubilization ratios by measuring the volumes of water, microemulsion, and oil phase. For this purpose, aqueous (surfactant in brine)/oil mixtures with an oil:water ratio of 1:1 (v/v) are placed in sealed pipetts. The pipetts are arranged in order of increasing salinity in racks and placed in an oven at 70 °C. They are gently agitated by repeated inversion in order to facilitate mixing of fluids. The level of fluid interfaces and pictures of each tube are recorded periodically to determine the surfactant combination that produces the largest microemulsion volume and therefore the optimum salinity.

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MATERIALS Crude Oil. A dead oil from Wyoming sandy reservoir (GB) was used in this research. The basic properties of this crude oil at 25 °C are a destiny of 0.92 g/cm3, viscosity of 105 cP, pentaneasphaltene content of 9.96 wt %, and a refractive index of 1.527. Brines. All synthetic brines were prepared in the laboratory by dissolving specific amounts of reagent-grade salts (NaCl, Na2 SO4, NaHCO3, MgCl2·6H2O, and CaCl2·2H2O) in deionized water (DW). The main characteristics for the two aqueous solutions are shown in Table 1. Connate water (CW) represents the in situ reservoir brine in an offshore carbonate reservoir, and SW is a synthetic version of the seawater from the Gulf of Mexico. Ca−Mg/TDS represents the calcium and magnesium concentration with respect to the total dissolved solids (TDS) in the brine, as a reference of hardness. C

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Figure 1. Foamer, O242, O332, O342, and O352 surfactants in DW and NaCl brines at 70 °C aged for 10 days. The different bottles in each row show the response to increasing salinity from 0 to 100 000 ppm. Clear solutions, e.g., top row for Foamer, show good solubility, while turbid ones, e.g., bottom row for O352, indicate poor solubility. Coreflooding. Two corefloods were conducted using the cores samples listed in Table 2. The cores were air-blown to remove loose particles and visually inspected to check for any induced fractures during cutting. The core dimensions were measured and weighed under dry and brine saturated conditions to estimate pore volume and consequently porosity. The experiments were conducted at 70 °C and 500 psi of confining pressure. The core was saturated and aged with CW brine; then CW brine was injected at several flow rates, and the pressure-flow rate results were used to estimate water permeability through Darcy’s law. Then, the GB crude oil was injected until initial water saturation (Swi), and oil permeability was measured by using four different flow rates. The cores were aged for 3 weeks in the oven at 70 °C. Because of the carbonate lithology, time, and temperature, changes in wettability may happen. After 3 weeks, GB crude oil was injected again until no additional brine was produced, and the oil permeability was measured again. Later, SW was injected at a flow rate of 0.35 cc/min for 5 pore volumes (PV). Subsequently, for the IL-GBSP1, the brine was switched to SW with the blend of surfactants and polymer for 1 PV. Then, SW with polymer was injected for an additional PV, and finally the experiment was finished after the injection of 5 PV of SW. While for the experiment IL-GBP1, SW was injected at a flow rate of 0.35 cc/min for 5 PV, then the brine was switched to SW with polymer for an additional 2PV, and finally the experiment was finished by the injection of 5 PV of SW. During the experiments, differential pressure (Dp), total fluid production, and oil and water volumes were recorded over time to calculate the incremental oil recovery and watercut and Dp during the whole process. The purposes were to estimate the oil recovery factor (RF) under SW injection in primary mode and the additional RF by injecting polymer only to compare with the last coreflood. Additionally, effluent samples were collected to track the concentration of the cEOR components and thereby estimate their dynamic adsorption using our NMR protocol. Concentration Determination through NMR. Chemical concentration in the effluent and in static adsorption tests were estimated using one-dimensional (1D) °H NMR according to GarciaOlvera et al.1 The samples were prepared at their full concentrations, and 90% water (brine)−10% D2O solutions were analyzed with NMR. In this way the dilution from the 10% D2O was consistent for all calibration curves as the tubes underwent the same dilution because no D2O was used in the coreflood. The 1D 1H experiments were conducted on Bruker Avance III 300 and 600 MHz instruments.

The quantitative information from the NMR was calculated by normalizing the absolute intensity with the applied gain and plotting this against the concentration. Chemical Static Adsorption. Indiana limestone and Berea sandstone rocks were sampled via splitting (quartering) method. Because in many cases the chemical adsorption is affected by the surface area, and the objective was to compare static adsorption between these two lithologies, standard sieves were used to sort the rock particles. Particles between 0.0059 and 0.0041 in. diameter from Berea sandstone and Indiana limestone were used for this experiment. The 2 g rock samples were put into vials, and 4 mL of chemical blend in SW were added. The vials were tightly closed, kept in the oven at 70 °C for 2 days, and were gently stirred frequently. Subsequently, after an equilibration time, samples from the aqueous phase were taken to be analyzed using one-dimensional (1D) 1H NMR spectroscopy.

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RESULTS AND DISCUSSION Phase Behavior: Selection of Viable Chemical Blends. The first experiments, regarding solubility and stability, were conducted using NaCl and DW at 25, 40, and 70 °C. A set of DW and NaCl brines with 0.5 wt % of the available surfactants were blended and kept in bottles in the oven. Observations and photographs were recorded for 1 week at the aforementioned temperatures. For simplicity, surfactant names were simplified, e.g. ENORDET O242 (IOS C20-24) is referred to as O242 and Alpha Foamer as Foamer. We found that Foamer is soluble and stable in DW and NaCl brines ranging from 10 000 to 100 000 ppm. O242 is soluble in DW. However, the samples remained cloudy in the salinity range from 10 000 to 100 000 ppm NaCl. O332 solutions in DW and brines from 10 000 to 70 000 ppm NaCl are clean and stable, but for NaCl brines from 80 000 to 100 000 ppm, the samples remained cloudy. O342 is soluble in DW. However, from 10 000 to 100 000 ppm NaCl, all the samples are cloudy at 25 °C and from 10 000 to 20 000 ppm NaCl, they were visually clean from 10 000 and 20 000 ppm NaCl at 40 and 70 °C. O352 in blends remain cloudy for DW and NaCl brines from 10 000 to 100 000 ppm and at all the temperatures, except for the sample in DW at 70 °C. The samples at 70 °C are shown in Figure 1. D

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Figure 2. Cosolvents N91 and N25 in DW in NaCl brines at 70 °C aged for 10 days. N91 (top) becomes insoluble above 10 000 ppm as indicated by the turbid solution. N25 (bottom) remains soluble, except at 90 000 and 100 000 ppm.

Figure 3. Phase behavior with DW and NaCl brines from 10 000 to 100 000 ppm at 70 °C aged for 10 days. Encircled regions correspond to desirable surfactant phase behavior.

To improve solubility, two cosurfactants were tested using the same brines, i.e., N91 and N25. These were blended at 3 wt % and kept in bottles in the oven. N91 surfactant blends were clean and stable from DW and from 10 000 to 100 000 ppm NaCl at 25 and 40 °C. However, at 70 °C, the samples in DW and 10 000 NaCl ppm remained clean, and the rest were cloudy. On the other hand, N25 in DW and from 10 000 to 100 000 ppm NaCl were clean and stable at 25 and 40 °C, but at 70 °C, the samples at 90 000 and 100 000 ppm NaCl remained cloudy. The samples at 70 °C are shown in Figure 2. From visual inspection, N25 is shown to be robust at higher salinity at 70 °C; therefore, this surfactant was used as cosurfactant to enhance surfactant solubility. Adding N25 improved surfactant solubility in NaCl brines. At 70 °C, O242 is soluble and stable up to 60 000 ppm, O332 soluble and stable up to 90 000 ppm, O342 soluble and stable up to 70 000 ppm, and O352 soluble and stable up to 60 000 ppm. The remaining samples remained slightly cloudy. With the aforementioned brines, we ran phase behavior experiments using GB with an oil:brine ratio of 1:1 at 70 °C. Photographs of the phase behavior tubes were taken every day. After 1 day, we observed type I and type III microemulsions in some of the tubes. Figure 3 shows the phase behavior for Foamer, O242, 0332, O342, and O352 surfactants at 70 °C. Eleven tubes from each set are arranged from left to right, DW and 10 000 to 100 000 ppm NaCl. While the total acid number (TAN) of the GB oil is unknown, on the basis of the 1D NMR analysis of partition tests from ref 24, we assume that the acidity of the GB oil is low. On the basis of the phase behavior, GB oil does not produce important microemulsions from any brines with Foamer or O332, while O242, O342, and O352 do. The O242 surfactant produces microemulsion type III from 60 000 to 100 000 ppm

NaCl, indicating an optimum salinity of roughly 75 000 ppm NaCl. The O342 surfactant produces microemulsions type III only for 90 000 and 100 000 ppm NaCl brines, and finally, O352 surfactant produces microemulsion type III from 60 000 to 90 000 ppm; the optimum salinity is 75 000 ppm. Taking into account that salinity and hardness affect emulsion formation, given that connate water in carbonate reservoirs and SW sometimes contains significant concentrations of Ca2+ and Mg2+, we evaluated three sets of bulk salinities (20 000, 40 000, and 60 000 ppm) with six hardness ratios, as shown in Table 3, with the three surfactants that produced good Table 3. Sets of Brines Used for Analyzing Effects of Hardness salinity (ppm) NaCl Ca−Mg

20 000−40 000−60 000 100% 0%

98% 2%

95% 5%

90% 10%

85% 15%

80% 20%

microemulsions in the aforementioned phase behavior, i.e., O242, O342, and O352. Blends with surfactants O242, O342, and O352 at 0.5 wt % concentration and brines shown in Table 3 were prepared and evaluated at 70 °C. All the samples were very cloudy, but turbidity was decreased by adding N25. Solubility was enhanced by increasing N25 concentration in the blends, in ratio surfactant:N25 of 1:1 and 1:2, and in some cases 1:5. The O242 surfactant blends were clear and stable at 20 000 ppm with a ratio 1:1. For salinities 40 000 and 60 000 ppm, higher concentration of N25 was needed to produce clear and stable emulsions. For the O342 and O352 surfactant blend, the solubility was improved a little by adding N25; however, it was not enough to produce clear blends. A phase behavior was run with these blends and GB oil−brine at a ratio 1:1 at 70 °C. E

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Figure 4. Phase behavior with NaCl, Ca, and Mg brines from 20 000 to 60 000 ppm at 70 °C aged for 10 days. Encircled regions correspond to desired surfactant phase behavior.

Photographs of the tubes were taken every day. Figure 4 shows the phase behavior for the O242, O342, and O352 surfactants at 70 °C. For each surfactant, 18 tubes were arranged from left to right from 20 000, 40 000, and 60 000 ppm, and from 0% Ca−Mg to 20% Ca−Mg. The phase behavior, in general, shows that the O242 surfactant produces microemulsions type III at high salinity, even at high Ca2+ and Mg2+ concentration in a wide range of salinity. The O342 and O352 surfactants have a better performance at 60 000 than at 20 000 ppm. The O342 surfactant produces only a light microemulsion type I, and the O352 surfactant produces microemulsions type I and type III, preferentially at high salinity. We tried to improve the solubility for the O342 and O352 surfactants by adding cosolvents SBA and IBA, and indeed the solubility improved somewhat; however, the blends showed noticeable precipitation, and on the basis of the assumption that adding these products to the solutions decreases the IFT, we decided to produce stable blends by using N25 and a lower concentration of O342 and O352 surfactants to avoid cosolvents. On the basis of our observations, a combination of high N25 concentration and low O342 and O352 surfactant concentration may produce stable blends with relatively high Ca2+ and Mg2+ concentrations in the range of seawater and higher salinities, although it is important to perform a detailed analysis to optimize solubility and IFT, and consequently emulsion types. Seawater is the dominant available water source offshore, and in many cases it is used for waterflooding beyond primary production to support pressure and to displace oil. Seawater injection in a mature offshore reservoir represents a progressive change in the connate water near to seawater composition. Considering a mature offshore reservoir after seawater flooding and using seawater as the main carrying fluid for surfactant injection, aqueous stability and phase behavior experiments using seawater were run using O242, O342, and O352 surfactants in combination with N25 at 70 °C. To obtain clear and stable blends, it was necessary to decrease the main surfactant concentration and increase the cosurfactant concentration, N25. Figure 5 shows the experiment at 70 °C aged for 10 days. The phase behavior experiments show that the O242 surfactant does not produce extensive type III volume, but an important volume of type I is formed. The wide salinity and hardness flexibility of this surfactant is an indication that it may perform well when combined with the SW brine.

Figure 5. Phase behavior with O242, O352, and O342 in SW at 70 °C aged for 10 days.

To improve volumetric sweep efficiency, polymer Flopaam 3630S at different concentrations was blended in SW. The viscosities of blends with SW and polymer Flopaam 3630S concentration from 1000 to 5000 ppm were measured. The temperature for the corefloodings was 70 °C. However, the viscosity measurements were taken at 25, 40, 60, and 70 °C. The viscosity at rate 10/s of the GB crude oil and the blends mentioned above are shown in Figure 6. On the basis of the previous results, at 70 °C, SW and 3000 ppm of polymer Flopaam 3630S exhibits a viscosity slightly higher than that of the oil. Therefore, this polymer concentration was used to enhance mobility control during the corefloodings IL-GBSP1 and IL-GBP1. Further analysis is necessary to optimize the polymer concentration in the blend, but this is beyond the scope of this paper. Coreflooding Results. To see the effect of the blend surfactants and polymer in oil recovery, the IL-GBSP1 coreflooding was run at 70 °C. As indicated in the previous subsection, the most viable blend was selected from phase behavior and solubility tests. The corefloods follow the traditional approach of waterflooding to residual oil saturation, followed by the low-tension flood. After the primary drainage throught the F

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the further formation of the oil bank. However, this is not atypical in this type of flood. The last injection slug, i.e., 4 PV of SW, did not have any significant effect on RF. The final oil recovery was 87.0%. Figure 7 shows the differential pressure and oil recovery factor for the IL-GBSP1 coreflood, and the main results are presented in Table 4. To discern contributions of polymer and surfactants to oil recovery separately, the IL-GBP1 coreflood was run under the same aforementioned conditions, with the only difference being that for this one only polymer was injected. After drainage, a relatively high value of Swi (51.1%) was estimated. Similarly to the previous experiment, the final Swi was reduced to 45.0% after aging and injecting GB oil. Simulating secondary recovery by SW injection led to an oilrecovery factor of 40.2%, after 5 PV of SW. Similar to the previous experiment, most of this oil was recovered before 2 PV, and unimportant additional oil was produced for the subsequent 3 PV. After 5 PV of SW, 2 PV of the polymer in SW containing 3000 ppm Flopaam 3630S were injected. The differential pressure increased from the beginning of the injection, but the additional oil production began after 0.5 PV of injection. The oil recovery factor reached 45.5%, representing an increase of 5.3% additional recovery. The last injection slug, i.e., 5 PV of SW, did not have any significant effect on RF. The final oil recovery was 46.0%. Figure 8 shows the differential pressure and oil recovery factor for the IL-GBP1 coreflooding, and the main results are presented in Table 4. These two experiments show the benefit of surfactants and polymer injection compared with in secondary recovery mode using SW only, and compared to mobility control alone through polymer flooding. Because a blend of two surfactants and one polymer was used for the IL-GBSP1 and one polymer for the IL-GBP1 in the chemical injection, the first step in collecting NMR spectra was to detect the characteristic peaks for each component in the blend. Figure 9 shows the 1H NMR spectra at 25 °C for O242 collected at 600 MHz and N25 and Flopaam 3630S collected at 300 MHz. We considered it convenient to use 600 MHz to maximize resolution for small peaks in the blend O242−N25− polymer that can be used for individual chemical analysis. However, for Flopaam 3630S and N25, individual analysis at 300 MHz is more than enough to detect any of their strong signals. As seen in Figure 9, O242 has a NMR signature very

Figure 6. Viscosity of GB oil and F3630S in SW at different concentrations and temperatures.

injection of GB oil, a relatively high value of Swi (55%) was estimated. However, after aging for 3 weeks, GB oil was injected again and additional water was produced, then Swi was recalculated to be 45.6%. We assume that the change in Swi was due to wettability alteration toward a more oil-wet state. The latter is highly possible, because the rock is carbonate and the core was aged at high temperature for a relatively long time. Simulating secondary recovery by SW injection led to an oilrecovery factor of 37.36%, after 5 PV of SW injection. Most of this oil was recovered before 2 PV, and a small additional oil volume was produced for the subsequent 3 PV, possibly due to frequent occurrence of snap-off under high salinity injection conditions. After 5 PV of SW, 1 PV of the SP blend in SW, containing 0.25 wt % O242, 1 wt % N25, and 3000 ppm Flopaam 3630S, was injected. The differential pressure increased from the beginning of the injection, but the additional oil production began after 0.5PV of injection. The oil recovery factor reached 60.92%, an increase of 23.56%. After SP injection, 1 PV of polymer in SW was injected. The oil recovery reached 85.82%, though most of the recovery took place after only 0.3 PV possibly due to the effect of the remaining surfactant in the core. Pressure increases because of a higher viscosity of the SP blend. Every time a different fluid is injected, some of the valves are closed and some are opened, which leads to transient flow periods. When this is done to conduct the polymer flood, this led to a somewhat complex pressure change associated with the non-Newtonian character of the polymeric solution as well as

Figure 7. Recovery factor and pressure drop for the IL-GBSP1 coreflooding. G

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Energy & Fuels Table 4. Summary Results for the Corefloods core IL-GBSP1 IL-GBP1 a

Kw (mD) 341 170

Ko (mD)

Swi (%)

Ko (mD)

bef. ag.

bef. ag.

aft. ag.

447 314

55.0 51.1

RF (%) Swi (%)

314 289

45.6 45.0

SW a

37.36 40.10a

SW+SP

SW+P

final RF (%)

60.92

85.82 45.30

87.0 46.0

After 5PV.

Figure 8. Recovery factor and pressure drop for the IL-GBP1 coreflooding.

Figure 9. 1H NMR spectra for O242, N25−12, and Flopaam 3630S in SW at 25 °C.

On the basis of the good correlation between the normalized NMR signal intensity and surfactants and polymer concentrations, we swept each species concentration to develop calibration curves, which later served to estimate CMC and chemical adsorption by comparing these with samples that were in contact with rock. O242 and N25 CMC values in DW were

similar to that of the N25, with only one peak characteristic of O242 in the blend, appearing at 1.9 ppm. N25 exhibits one distinct intense peak at 3.4 ppm, and finally, for polymer 3630S, the peak at 2.14 ppm was selected as the identifier for this component in the samples. As can be observed, the blend maintains the peak locations for all species present. H

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Energy & Fuels estimated using the most intense NMR peaks. Using the absolute intensity versus surfactant concentration, the CMC at 25 °C was estimated for O242 and N25 to be approximately 0.7 and 0.8 wt %, respectively, as Figure 10 shows.

Figure 13. Normalized intensity versus O242−N25 surfactant concentration in SW at 25 °C collected at 600 MHz.

Figure 10. Absolute intensity versus surfactant concentration in DW at 25 °C at 300 MHz.

We were unable to conduct the individual analysis for O242 because of its low solubility in SW. Instead, a calibration curve was created for both components in a blend of O242 and N25 and a blend of both surfactants with polymer 3630S using the 600 MHz instrument. Figures 10−14 show the calibration

Figure 14. Normalized intensity versus O242−N25−3630S concentration in SW at 25 °C, collected at 600 MHz.

curves for N25, polymer 3630S, and O242−N25 and O242− N25−polymer blends. Because the designed blend was 0.25 wt % O242, 1 wt % N25, and 3000 ppm polymer 3630S, this was defined as 100% and then diluted with SW to form lower blend concentrations. Berea sandstone and Indiana limestone were sampled via splitting to estimate static adsorption. The ground rock samples were placed in contact with N25, O242−N25, O242−N25− polymer 3630S, and polymer 3630S in SW brine and kept at 70 °C (Figure 15). Aqueous phase samples were taken to collect 1H NMR spectra. Spectra of chemical solutions after contacting sandstone and carbonate were compared with the calibration curves (Figures 10−14) and thereby used to estimate static adsorption. The results are presented in Table 5. It is interesesting to note that polymer adsorption is high when only polymer is present in the aqueous phase, and when surfactants are in the blend, the polymer adsorption decreases considerably. On the other hand, the static adsorption in Berea sanstone is higher than that in Indiana carbonate, even when similar particle sizes were used from both lithologies. Effluentes from IL-GBSP1 and IL-GBP1 were analyzed using NMR to determine the chemical concentration by comparing the effluent NMR signals with the calibration curves from Figures 12 and 14. The NMR spectra for the effluent samples show the same surfactant peaks as the individual surfactant analyzed and two additional peaks, with a major one at 3.3 and another at 2.15 ppm. The locations for the new large peaks correlate with methylene, which is the most abundant of the

Figure 11. Normalized intensity versus N25 surfactant concentration in SW at 25 °C collected at 300 MHz.

Figure 12. Normalized intensity versus polymer 3630S concentration in SW at 25 °C collected at 300 MHz. I

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Figure 15. Chemical solutions in contact with sandstone and carbonate to estimate static adsorption. Bottles contain ground rock (bottle brownish phase) and chemical solutions (above the ground rock level). Bottle labels indicate the chemical and rocks used. Berea is for Berea sandstone, and INDIANA is for Indiana limestone.

Table 5. Static Adsorption Estimation by 1H NMR Spectra

For IL-GBSP1 data, one of the oil peaks overlaps the polymer blend and in some instances made determining the intensity of the polymer peak difficult. For this reason fewer polymer concentration points were obtained. The presence of oil, a large molecule that tumbles slowly in solution, is also known to cause broadening of NMR signals. The characteristic peak of O242 is already shorter than the other identifying peaks, and with the addition of oil, it suffers further broadening and narrowing; the tubes where the characteristic peak for O242 could not be distinguished were omitted in Figure 17. The results in Figure 17 show the produced surfactants and polymer concentrations in aqueous phase for the IL-GBSP1 coreflood. The analyses come from the brine, type I microemulsions mainly, and these are plotted versus injected PV. The figure includes the RF to show the connection between

adsorption (%) sample

rock

N25

O242

polymer 3630S

N25 N25 polymer polymer O242−N25 O242−N25 O242−N25−polymer O242−N25−polymer

sandstone Indiana sandstone Indiana sandstone Indiana sandstone Indiana

16 10 − − 13 7 15 6

− − − − 20 5 17 4

− − 6 18 − − 3 1

saturated alkanes. We assume these new peaks can be associated with the oil present in the sample (Figure 16).

Figure 16. 1H NMR spectra for the IL-GBSP1 effluents collected with the 600 MHz spectrometer at 25 °C. J

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somewhat consistent with the static adsorption experiment. The large increment in the Dp observed in Figure 18 may be a consequence of this high polymer adsorption in the rock as well as plugging. Additional experiments were run to estimate the chemical concentration in the oil phase, near the interface, in the interface region, or in the microemulsion. For the polymer analysis, GB crude oil and polymer 3000 ppm concentration in SW, volume ratio 1:1, was poured in a funnel and aged in the oven at 70 °C. After 1 week, the aqueous phase was removed for analysis with NMR. For the surfactants analysis, GB crude oil and SW with N25 and O242 surfactants, 0.25 and 1 wt %, respectively, in volume ratio 1:1 was poured in a funnel and aged in the oven at 70 °C. Two more sets of surfactant combinations were prepared, one at 50% blend of original concentration and the other at 30%. Oil and water with chemicals were present in these experiments, so we assume that the missing chemical concentration in the aqueous phase resides in the oil or in the interface. Results are presented in Table 6.

Figure 17. Surfactants and polymer concentration of the IL-GBSP1 effluents using 1D 1H NMR.

increased RF and the breakthrough of chemicals in the effluents. On the other hand, a clear delay between chemical injection and the recovery benefit as the additional recovery is observed. The last results show the presence of chemicals in the effluents after 0.3 PV of SP injection, but at very low concentration. These can be explained through spreading and dispersion. We speculate that the first SP volume flowed through a mostly water-saturated channel at irreducible oil and was diluted abruptly in contact with SW contained in the porous rock. As the SP slug continues to be injected, dilution became less important, and microemulsions (w/o) started to form and moved downstream. Consequently, additional oil was produced at the same time as polymer and surfactants broke through. The increment in oil recovery and chemical concentration in the effluents appear to match well. At the beginning of the SP slug, we estimate a maximum concentration of chemicals. However, this did not reach 100% of the injected concentration. We assume that adsorption, trapping, dilution, and presence of chemicals in the oil phase were the causes. In the effluents, the surfactant concentrations depleted gradually, and the additional oil production did too until no additional oil or chemicals were produced. Figure 18 shows the polymer concentration in the effluents and the oil recovery factor for the IL-GBP1 coreflood. Similar

Table 6. Chemical Concentration Using 1H NMR Spectra after 1 Week sample

concentration in aqueous phase (%)

polymer 3630S 100% (0242−N25) O242 N25 50% (0242−N25) O242 N25 30% (0242−N25) O242 N25

94.4 25.0 50.6 28.4 21.2 26.5 3.1

On the basis of these results, we estimate that most of the polymer remains in the aqueous phase and only 5% goes to near the interface or the oil phase. On the other hand, 75% of the surfactant O242 and 50% of the surfactant N25 goes to near the interface or to the oil phase when the original blend (100%) was analyzed. A similar change in O242 concentration occurs when the original surfactant blend is diluted with SW at 50 and 30%. However, the changes in N25 concentration in the aqueous phase depend on the surfactant concentration in the blend, suggesting that this surfactant is more hydrophobic.

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CONCLUSIONS In a thorough approach, we tested different commercial surfactants at different temperatures, brines, and Ca2+ and Mg2+ concentrations. Most of the surfactants were affected by hardness, which hampered the formation of stable blends. Phase behavior experiments and a coreflood show the potential for some surfactants to recover oil using SW as the carrying fluid. The following conclusions can be drawn for the results: 1. Most of the analyzed surfactants need a cosurfactant to improve solubility, and N25 worked well at relatively high salinity. However, when Ca2+ and Mg2+ are present, the surfactant concentration had to be diminished in the blend to avoid precipitation. 2. The O242 surfactant in combination with N25 in SW produced microemulsions type I and III in phase behavior experiments with the GB oil at 70 °C without the need of additional cosolvents.

Figure 18. Polymer concentration of the IL-GBP1 effluents using 1D 1 H NMR.

to the previous analysis, there is a delay between chemical injection and the recovery benefit as the additional recovery is observed. The high polymer adsorption during coreflooding is K

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(10) Novosad, J. Laboratory evaluation of lignosulfonates as sacrificial adsorbates in surfactant flooding. J. Can. Pet. Technol. 1984, 23. DOI: 10.2118/84-03-01. (11) Yang, H. T.; Britton, C.; Liyanage, P. J.; Solairaj, S.; Kim, D. H.; Nguyen, Q. P.; Weerasooriya, U.; Pope, G. A. Low-cost, highperformance chemicals for enhanced oil recovery. SPE Improved Oil Recovery Symposium 2010; SPE 129978. (12) Peru, D. A.; Lorenz, P. B. Surfactant-enhanced low-pH alkaline flooding. SPE Reservoir Eng. 1990, 5, 327−332. (13) Manrique, E. J.; Muci, V. E.; Gurfinkel, M. E. EOR field experiences in carbonate reservoirs in the United States. SPE/DOE Symposium on Improved Oil Recovery 2006; SPE 100063. (14) Zubari, H. K.; Sivakumar, V. C. Single Well Tests to Determine the Efficiency of Alkaline-Surfactant Injection in a Highly Oil-Wet Limestone Reservoir. Middle East Oil Show 2003; SPE 81464. (15) Chen, H. L.; Lucas, L. R.; Nogaret, L. A. D.; Yang, H. D.; Kenyon, D. E. Laboratory monitoring of surfactant imbibition using computerized tomography. SPE International Petroleum Conference and Exhibition in Mexico 2000; SPE 59006. (16) Weiss, W. W.; Xie, X.; Weiss, J.; Subramanian, V.; Taylor, A. R.; Edens, F. J. Artificial intelligence used to evaluate 23 single-well surfactant-soak treatments. SPE Reservoir Evaluation & Engineering 2006, 9, 209−216. (17) Sorbie, K. S. Polymer-improved oil recovery; Springer Science & Business Media: Amsterdam, 2013. (18) Carreau, P. J. Rheological equations from molecular network theories. J. Rheol. (Melville, NY, U. S.) 1972, 16, 99−127. (19) Kazempour, M.; Sundstrom, E. A.; Alvarado, V. Effect of alkalinity on oil recovery during polymer floods in standstone. SPE International Symposium on Oilfield Chemistry 2011; SPE 141331. (20) Han, M.; Xiang, W.; Zhang, J.; Jiang, W.; Sun, F. Application of EOR technology by means of polymer flooding in Bohai oilfields. International Oil & Gas Conference and Exhibition in China 2006; SPE 104432. (21) Lu, Q.; Ning, Y.; Wang, J.; Yang, X. Full Field Offshore Surfactant-Polymer Flooding in Bohai Bay China. SPE Asia Pacific Enhanced Oil Recovery Conference 2015; SPE 174591. (22) Sahni, V.; Dean, R. M.; Britton, C.; Kim, D. H.; Weerasooriya, U.; Pope, G. A. The role of co-solvents and co-surfactants in making chemical floods robust. SPE Improved Oil Recovery Symposium 2010; SPE 130007. (23) Barnes, J. R.; Dirkzwager, H.; Smit, J.; Smit, J.; On, A.; Navarrete, R. C.; Ellison, B.; Buijse, M. A. Application of internal olefin sulfonates and other surfactants to EOR. Part 1: Structure-Performance relationships for selection at different reservoir conditions. SPE Improved Oil Recovery Symposium 2010; SPE 129766. (24) Alvarado, V.; Garcia-Olvera, G.; Hoyer, P.; Lehmann, T. E. Impact of polar components on crude oil-water interfacial film formation: A mechanisms for low-salinity waterflooding. SPE Annual Technical Conference and Exhibition 2014; SPE 170807.

3. The coreflooding experiment shows that the additional recovery by the SP process after secondary mode by SW injection represents almost 48% of additional oil recovery with respect to the original oil in place and almost doubles the secondary recovery. 4. The coreflooding experiment shows that the additional recovery by polymer injection after secondary mode by SW has an abridged value; however, the high polymer adsorption may be the main reason for this poor performance, also indicating the need for a low-tension condition. 5. The results of this research show that NMR spectroscopy is a powerful technique to analyze individual components in chemical blends, and it can be successfully applied for both static and dynamic experiments. Because NMR signals can overlap for the products injected in an SP project, one distinct identifying peak is not always guaranteed. A statistical algorithm to detect the individual NMR signals for each chemical component would be beneficial. We are currently working to address this problem.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: +1(307) 766-6464. Fax: +1(307) 766-6777. ORCID

Vladimir Alvarado: 0000-0001-9559-0565 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors acknowledge the Enhanced-Oil Recovery Institute for financial support. The authors thank Shell Global Solution and Stepan Company for providing the surfactants used in this work. G.G.-O. is thankful to Pemex and CONACYT-SENER fund for providing the financial support for her graduate studies at the University of Wyoming.

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REFERENCES

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DOI: 10.1021/acs.energyfuels.6b01413 Energy Fuels XXXX, XXX, XXX−XXX