An automated analytical method to determine solution alkalinity of

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An automated analytical method to determine solution alkalinity of oilfield brine in the presence of weak organic acids Ping Zhang, Siyuan Huang, Nan Zhang, Amy T. Kan, and Mason B. Tomson Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.8b05333 • Publication Date (Web): 02 Mar 2019 Downloaded from http://pubs.acs.org on March 3, 2019

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Industrial & Engineering Chemistry Research

An automated analytical method to determine solution alkalinity of oilfield brine in the presence of weak organic acids Ping Zhang a *, Siyuan Huang a, Nan Zhang b, †, Amy T. Kan b, c, Mason B. Tomson b, c a Department

of Civil and Environmental Engineering, Faculty of Science and Technology, University of Macau, Macau, China b Department

of Civil and Environmental Engineering,

Rice University, Houston, Texas, USA

c

Nanosystems Engineering Research Center for Nanotechnology-Enabled Water Treatment,

Rice University, Houston, Texas, USA

† Presently

at Statoil Inc., 6300 Bridge Point Pkwy, Austin, TX, USA

Manuscript prepared for Industrial & Engineering Chemistry Research

* To whom correspondence should be addressed: Ping Zhang: [email protected] Tel: (+853) 8822 4917

Electronic supporting information (ESI) available

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Abstract Oilfield produced brine can cause significant corrosion and mineral scaling issues to the production system and the environment. Solution alkalinity is an important parameter dictating the corrosion and scaling threat of oilfield brine. However, it remains an ongoing challenge to accurately measure oilfield brine alkalinity, especially in the presence of weak organic acids, such as carboxylic acids. Conventional titration method for oilfield alkalinity measurement does not consider the impact of organic acid on alkalinity, leading to an erroneous measurement result. In this study, an analytical method was presented to simultaneously measure total alkalinity and weak organic acid (acetic acid) concentrations of the brine via an automated titration approach. It shows that the automated method substantially outperformed the conventional method in terms of accurately measuring both solution alkalinity and organic acid concentration with one titration effort. The automated analytical method is considerably robust and is not highly sensitive to the introduction of random error. Modeling calculation shows that the automated analytical method exceeds the conventional method in determining solution alkalinity with an enhanced accuracy for scale threat predictions. This is the first study to report such an accurate and convenient analytical method to measure solution alkalinity and organic acid concentrations for oilfield produced brine. Given the accuracy and convenience of this reported analytical method, this method can find wide industrial applications within oilfield and beyond, including corrosion and scaling control, water resources management and environmental pollution control. Keywords: alkalinity; bicarbonate; organic acid; pH; automated; titration

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1. Introduction 1.1 Measurement of oilfield brine alkalinity During oil and gas productions, saline water (brine) is commonly produced together with the hydrocarbons. The volume of the produced brine can be as high as over 90% of the total volume of the produced fluid, especially in the later oilfield life.1, 2 Oilfield produced brine is corrosive in nature threatening the integrity of oilfield production facilities.3, 4 In addition, oilfield brine can cause significant mineral scaling issue by reducing the throughput of production tubing and transporting pipeline.3 The detrimental impact of oilfield brine can be exacerbated by water flooding operations where a considerable amount of injection water is comingled with the formation water flowing from reservoir to processing facilities.2 It remains an ongoing challenge to accurately characterize the solution chemistry of oilfield produced brine, such as determination of aqueous concentrations of inorganic and organic species, production chemicals, dissolved petroleum constituents, etc.5-8 Thus, it is necessary to implement an appropriate management strategy to handle the oilfield brine to minimize the damaging impact of brine onto the oilfield production system and the environment. Assessing the produced brine chemistry plays a vital role in understanding the corrosivity and scaling threats of the brine and in developing the brine management strategy. Among various brine chemistry parameters, alkalinity can have a substantial impact on the brine corrosion and scaling threats.3, 4

However, it is often a challenge for the petroleum industry to correctly evaluate the solution alkalinity at

field conditions. Details will be given below as of the difficulties in oilfield alkalinity measurements.

Alkalinity, defined as the capacity of an aqueous solution to neutralize an acid, is an important water chemistry parameter related to various water-based phenomena, such as mineral scale formation and pipe corrosion.9-12 The solution alkalinity in natural and industrial systems is controlled by the equilibrium of various dissolved species, such as carbonates, sulfides, organic acids, borates, silicates, ammonia and phosphates, as defined in Eqn. 1: Alkalinity=[HCO3- ]+2[CO32- ]+[Ac- ]+[HS- ]+2[S2- ] +[NH 4 ]+[B(OH) 4  ]+[H 3SiO-4 ]+2[H 2SiO 2-4 ] 24

34

-

+

+[HPO ]+2[PO ]-[H 3 PO 4 ]+[OH ]-[H ]


(1)


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where the term “Alkalinity” in Eqn. 1 denotes the total alkalinity (equiv. L-1) of the solution and [Ac-] represents acetate ion. The bracket represents the total concentration of each species. Normally, for an oilfield brine within the pH range of 4-9, the contributions of borate, silica, phosphate and ammonia to solution alkalinity are typically assumed to be insignificant due to their limited concentrations.13 It should be noted that the total alkalinity, not bicarbonate concentration, is a conservative property of the brine.9 Solution pH will increase as CO2 and H2S gases are released from solution into gas phase due to system pressure reduction. As the solution pH changes, the relative amount of various weak organic acids on the right hand side of Eqn. 1 will change as well, but the solution total alkalinity will be maintained unchanged.9 In a similar manner, adding weak acids, such as acetic acid, into a brine will not change the total alkalinity, although solution pH will be lowered. Therefore, because of the conservative nature of alkalinity, alkalinity is a robust tool to calculate solution pH, bicarbonate concentration, corrosivity and carbonate scaling tendencies at different conditions of a production system.

1.2 Difficulty of alkalinity measurement Alkalinity is often incorrectly assumed to be equal to the bicarbonate concentration. However, this assumption will no longer hold in the presence of a considerable amount of weak organic acids. It has been reported that as much as over 5,000 mg L-1 of organic acid anions are present in water samples collected from a number of oil and gas fields.2 These observed organic acids are mainly carboxylates, such as acetate, propionate, butyrate and valerate. It has been reported that the organic acids can contribute to more than 50% and sometimes up to 100% of the measured alkalinity.13 In other words, it can occur that the total alkalinity of a produced brine arises predominately from organic acids instead of bicarbonate. There is no easy method to measure alkalinity when organic acid concentration accounts for a significant fraction of the total alkalinity. Alkalinity can be conventionally determined by standard titration procedure when bicarbonate is the predominant contributor to total alkalinity.12, 14 Numerous efforts have been made to accurately determine the ending point when the bicarbonate alkalinity was titrated.15-17 However, in the presence of a high fraction of weak organic acids, the titration end point is smeared and it is difficult to 4 ACS Paragon Plus Environment

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determine the ending point and hence the total alkalinity, as shown in section S1 of the Electronic Supporting Information (ESI). Furthermore, the total alkalinity often deteriorates rapidly during the shipping and storage of brine samples, especially when proper sampling procedure is not followed. Therefore, sampling procedure and alkalinity measurement remains one of the most difficult oilfield brine chemistry problems and there is, as yet, no automated analytical method to measure alkalinity in a convenient manner.

1.3 Simultaneous measurement of alkalinity and organic acids In a previous study, a rigorous theoretical solution to determine total alkalinity and organic acid concentrations has been proposed with a corresponding experimental procedure to accurately measure both bicarbonate and weak acids simultaneously.18 This method is based upon the assumption that the species concentrations of borate, silica and phosphate are negligible compared to those of carbonates and notable organic acids, such as acetic acid. Therefore, the calculation of alkalinity can be simplified by considering aqueous pH, bicarbonate, carbonate and notable organic acids, as shown in Eqn. 2, where the activity coefficients are ignored for clarity.

Alkalinity ≅ [HCO3- ] +2[CO23 - ] + [Ac - ] + [OH - ] - [H + ] ≅

K1, H2CO3KCO2, gasPCO2,gas 10 -pH

THAc ∙

+

𝐾2, 𝐻𝐶𝑂 ― 𝐾1, 3

+2 ∙

KHAc

10 -pH + KHAc

Kw

+ 10 -pH ― 10

𝐻2𝐶𝑂3𝐾

P

CO2, gas CO ,gas 2

(10 -pH)2 -pH

(2) where K represents dissociation constants of different species. THAc (mg L-1) denotes the sum of acetate species. PCO (atm) corresponds to the partial pressure of CO2 in the gas phase. Kw is the water dissociation 2

constant. Typically for a production system, the gas phase CO2 concentration is measured from compositional analysis of either a surface sample or a reservoir fluid sample. Then, the CO2 partial pressure can be calculated with equation of state and mass balance relationship at any production condition. Essentially, Eqn. 2 is the working equation to simultaneously calculate total alkalinity and organic acid 5 ACS Paragon Plus Environment


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concentrations. There are only two unknowns in Eqn. 2, i.e., THAc and alkalinity. By titrating the sample solution with a standard acid, such as HCl, the solution pH will be lowered. Solution alkalinity will be changed accordingly together with solution pH, while THAc will remain unchanged. Eqn. 2 can be solved by continuously titrating the sample solution with standard acid. The obtained pH and the addition amount of standard acid during the titration process can be utilized to calculate solution alkalinity and organic acid concentration via an Excel-based computer program following a Newton-Raphson procedure.18

1.4 Development in the present study In this study, the aforementioned titration method has been automated with continuous addition of standard acid solution into the test solution. With the aid of this improved analytical method, the solution pH, scaling and corrosion tendencies of a production system can be determined in an automated manner. The automated analytical method can simultaneously measure the organic acids and total alkalinity within one titration effort. This will significantly facilitate the in-situ alkalinity measurement in the field. Moreover, with the recent development of deepwater offshore hydrocarbon productions and shale oil productions, produced water samples containing a considerable amount of previously assumed “negligible” species, such as silicate, borate and phosphate, are not uncommon.19 Thus, in this improved method, the contributions of silicate, ammonia, borate, and phosphate species on alkalinity were also considered in the updated version of the computer program. A complete expression of alkalinity calculation including all considered aqueous species and corresponding activity coefficients can be found in Section S2 of the ESI. To the best of our knowledge, this is the first study to report such an accurate and convenient analytical method to satisfy the requirement of measuring solution alkalinity and organic acid concentrations for oilfield produced brine in an automated manner to facilitate oilfield corrosion and scale control. Given the accuracy and convenience of this method, this method can find wider applications in natural water resources management, industrial water management and environmental pollution control.


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2. Materials and methods 2.1 Water sample preparation and particulate alkalinity measurement All chemicals used in this study were analytical grade. Synthetic brines (labelled as Brine #1 to #3 in section S3 in the ESI) with a total alkalinity from 200 to 2,000 mg L-1 were prepared to evaluate the accuracy of the automated analytical method. Produced water samples from a Texas shale basin reservoir (labelled as Brine #4 to #7 in section S4 in the ESI) were collected by using screw-cap sample bottles and stored at 4 ̊C. The water samples were analyzed shortly after the solutions were allowed to return to room temperature (22oC). The compositions of the synthetic brines and the field samples are listed in the ESI at section S3 and S4, respectively. Firstly, all the water samples were filtered by a 0.45 µm filter. Next, a volume of 1% nitric acid (typically in the range of 0.2 to 0.3 mL) was added into 50 mL of the water sample to dissolve Ca and Fe solid precipitates. Dissolved Ca2+ and Fe2+ concentrations in the acidified samples were analyzed by inductively coupled plasma-optical emission spectrometry (ICP-OES, Perkin Elmer Optima 4000 DV). Thus, the solid mass of Ca and Fe precipitates can be determined based upon the measured Ca2+ and Fe2+ concentrations in the acidified samples. The obtained solid mass of Ca and Fe precipitates will be accounted for in determining the total solution alkalinity. 2.2 Automated titration with standard acid solution A schematic representation of the experimental apparatus is shown in section S5 in the ESI. Prior to the titration for alkalinity measurement, water sample pH was measured by a pH electrode (ThermoFisher Scientific). Subsequently, 100 mL of the filtered sample was vigorously sparged with N2 gas containing 1% CO2 for about 20-30 min until the solution pH was stabilized. This indicates that the sample solution was fully saturated with 1% CO2. The N2/CO2 gas was firstly sparged into deionized water before being introduced into the samples to avoid the water evaporation from samples during vigorous sparging. Following the CO2 gas sparging, HCl standard solution (1.000 N) was delivered into the sample with a slow flow rate of 2 mL h-1 controlled by a syringe pump (NE300 Just InfusionTM Syringe Pump) so that the solution pH can be re-stabilized shortly after introducing each drop of HCl acid. An even lower acid



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delivery rate of 0.5 mL h-1 was used for samples with a total alkalinity of 100 mg L-1 or lower. Solution pH was measured by the pH electrode and recorded automatically by a data logger. The end point of the titration was approximately 3 pH. The previously developed software package18 was modified to accommodate automated titration data acquisition and data analysis. The obtained pH values together with the amount of HCl added during the course of titration were entered into this modified software package to determine the total alkalinity and organic acid concentrations. This software is able to automatically select twenty evenly spaced points for the curve fitting. Subsequently, the software computes the sum of squared errors of the calculated and observed pH versus the amount of HCl added and minimizes the error by changing the values of Alkalinity and THAc via a Newton-Raphson procedure. Standard deviations of the curve-fitted parameters and correlation coefficients of the fit can be calculated as well.


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3. Results and discussion 3.1 Impact of sulfide species and particulate solids on solution alkalinity Note that, due to the conservative nature of alkalinity, adding or removing neutral CO2 or H2S compounds from brine solution has no impact on solution alkalinity. The benefit of sparging the solution with CO2 gas is to remove any residual sulfide species so as to simplify the alkalinity titration and calculation detailed in this study. By sparging the brine with CO2 gas, the sulfide species in solution can be removed as H2S gas and each mole of sulfide species is substituted by one mole of bicarbonate (Eqn. 3). Because of this treatment, the curve fitting equation for determining the solution alkalinity and organic acid concentration can be simplified without consideration of the presence of sulfide species. HS ― + CO2, gas→HCO3― + H2Sgas

(3)

On the other hand, the alkalinity originated from particulates, especially Ca and Fe particulates, cannot be ignored. Brine solution alkalinity can transfer from aqueous phase to particulate solids due to the following oxidation and precipitation reactions (Eqn. 4-6)

Oxidation: Fe2 + +0.25O2 +2.5H2O→Fe(OH)3, solid +2H + Precipitation: 𝐶𝑎2 + +2𝐻𝐶𝑂3― →𝐶𝑎𝐶𝑂3, 𝑠𝑜𝑙𝑖𝑑 + 𝐻2𝐶𝑂3, 𝑎𝑞 Precipitation: 𝐹𝑒2 + +2𝐻𝐶𝑂3― →𝐹𝑒𝐶𝑂3, 𝑠𝑜𝑙𝑖𝑑 + 𝐻2𝐶𝑂3, 𝑎𝑞

(4) (5) (6)

Therefore, each mole of the precipitated Fe or Ca solids can consume two equivalent moles of alkalinity. By measuring the solid alkalinity associated with Fe or Ca particulates, the total alkalinity can be adjusted by considering the titration measurement of the solid alkalinity.



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3.2 Automated analytical methodology The merit of the automated analytical method is the automated measurement of total alkalinity and concentration of organic acids simultaneously in one titration effort. Essentially, this method involves the automated titration of a filtered solution from the original solution pH to ca. 3 pH. The titration was carried out at a fixed PCO of 0.01 atm (1% CO2). A theoretical equation derived 2

from the general alkalinity equation is used to calculate HCl needed at each titration point (Eqn. S1 in the ESI). This theoretical equation considers the impact on alkalinity from common aqueous acidic and basic species. Detailed derivation of the curve fitting equation is discussed in Section S6 of the ESI. In order to accommodate a wide variety of water samples, in this study the alkalinity equation used in curve fitting was modified to include more anionic species encountered in oilfield produced water, such as carbonate and carboxylates, as well as borate, silica, phosphate, ammonia, as shown in Eqn. 1. The silica, boron and phosphorus concentrations can be measured by ICPOES. Note that all possible oilfield weak acid species can be accommodated as long as the total acid concentration is known along with ionization constants of the acids, such as humic acids, naphthenic acids, etc. The alkalinity equation can be expanded as below (Eqn. 7):

Alkalinity ≅

K1, H2CO3KCO2, gasPCO2,gas -pH

+

10

-pH

K2, HCO3― K1, +2 ∙

H2CO3KCO2, gasPCO ,gas 2

(10

-pH 2

)

+ THAc ∙

KHAc 10

-pH

+ KHAc

+

Kw 10 -pH

― 10

∑(𝐴𝑙𝑙 𝑎𝑑𝑑𝑖𝑡𝑖𝑜𝑛𝑎𝑙 𝑑𝑒𝑝𝑟𝑜𝑡𝑜𝑛𝑎𝑡𝑒𝑑 𝑤𝑒𝑎𝑘 𝑎𝑐𝑖𝑑 𝑠𝑝𝑒𝑐𝑖𝑒𝑠 𝑓𝑜𝑟 𝑤ℎ𝑖𝑐ℎ 𝑡𝑜𝑡𝑎𝑙 𝑎𝑐𝑖𝑑 𝑐𝑜𝑛𝑐𝑒𝑛𝑡𝑟𝑎𝑡𝑖𝑜𝑛𝑠 𝑎𝑟𝑒 𝑘𝑛𝑜𝑤𝑛) (7)

In this study, acetic acid is used as a model species for all organic acids, which share a similar pKa value of ca. 4.7 at standard temperature and pressure conditions.


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3.3 Alkalinity measurement results As shown in section S3 of the ESI, an excellent agreement between the calculated and the true alkalinity and acetate concentrations in three sythetic brines (#1 to #3) can be obtained. 0.9 M and 0.01 M NaCl were added into Brine #1&2 and Brine #3, respectively, as the background electrolyte. The only source of alkalinity for Brine #1 and Brine #3 was the added bicarbonate. Brine #2 was prepared with a similar bicarbonate concentration as Brine #1 but with a different total alkalinity due to the addition of sodium acetate into Brine #2. The automated analytical method was adopted to calculate total alkalinity and organic acid concentrations for all three brines with an error less than 3%. It also shows that in this study, all the experimental titration data fit the theoretical equation well with a correlation coefficient (r2) of 0.999 or above. In addition, this result suggests that the automated analytical method is able to correctly measure the solution alkalinity for a wide range of TDS from less than 900 to over 51,000 mg L-1 employed in this study. As disscussed in the previous study18, the organic acid concetrations in oilfield brines can not be easily determined independently through gas chromatography and/or ion chromatography. The level of measurement accuracy reported in this study is especially useful in the prediction of mineral scale threat, due to the strong dependent relationship between bicarbonate concentration and carbonate scaling threat. Additional studies are required to evaluate the impact of high solution TDS beyond 51,000 mg L-1 tested in this study, due to the ultra high oilfield brine TDS encounted in many field operations, such as those in the shale field productions.

In this method, the alkalinity is determined by analyzing the shape of the titration curve instead of the titration end point as is conducted in the conventional titration. Therefore, one might speculate that the quality of the curve fitting, i.e., the r2 value, is critial for the accuracy of the calculated 11 ACS Paragon Plus Environment


alkalinity value. To further evaluate the quality of this method and the impact of curve fitting, Brine #3 titration data were utilized to assess a number of scenarios with different random errors. The random errors are the arbitrarily made errors to the measurement data. This exercise is to illustrate the technical difficulty in accurate brine chemistry measurement. An effort was made to compare the base case or theoretical pH values (no random error) and the calculated pH values based upon up to 6% random error. The theoretical pH values are calculated based on the alkalinity equation (Eqn. S-1 in the ESI) with 0.01 mol L-1 (610 mg L-1) total alkalinity in Brine #3. Introduction of random error leads to a deterioration of the r2 value to as low as 0.849. Figure 1 plots the theoretical and calculated pH with different levels of random errors as a function of HCl added. It shows that the pH lines arising from different levels of errors were not obviously deviated from the theoretical pH line, especially during the second half of HCl addition process. Because of the insignificant change in the relation of pH with HCl added from the theoretical pH line, even with up to 6% random error and a r2 value of only 0.849, the calculated total alkalinity in each scenario with random error was maintained within 608±15 mg L-1. Similarly, the calcualted organic acid concentrations for the scenarios with random error was close to zero. The insignificant variation in the calculated alkalinity and organic acid against the true values suggests that the automated method is considerably robust and is not highly sensitive to introduction of random error.


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r2 Total Alkalinity (mg L-1) Organic acid (mg L-1)

No Error (Theoretical) 1.00 610 ± 0 0±0

2% Error

4% Error

6% Error

0.996 612 ± 3 0±0

0.931 610 ± 20 4±3

0.849 608 ± 15 0±0

Figure 1 Impact of introducing random error in titration data. The table below lists the corresponding total alkalinity and organic acid concentration.

The automated analytical method was also tested to measure the total alkalinity and organic acid concentrations of actual oilfield brine samples. In another study, four produced brine samples (Brine #4 to Brine #7 in section S4 of the ESI) collected from a Texas shale basin reservoir were tested by this automated titration procedure. As a comparison, solution alkalinity was also determined by the conventional alkalinity method.12, 14 A substantial amount of carboxylates (ca. 200 to over 900 mg L-1 as acetate) was present in each shale brine sample. Table 1 compares the measurement results from the automated analytical method and the conventional method. It shows that, as expected, the conventional alkalinity method underestimates the total alkalinity when a considerable amount of organic acids were present. The conventional method does not consider the impact of the presence of organic acids, not to mention that the titration end point becomes exceedingly difficult to identify (titration curves of these four Texas shale brines shown in section S7 of the ESI). However, a significant amount of organic acids can be often found in oilfield 13 ACS Paragon Plus Environment


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brines.2, 13 Thus, the automated analytical method substantially outperformed the conventional method in terms of accurately determining the concentrations of total alkalinity and organic acids simultaneously with one titration effort.

Table 1 Comparison of alkalinity and organic acid concentrations of four produced brines from a Texas shale basin measured by the automated analytical method and by the conventional method Automated Analytical Method Brine # *

4 5 6 7

Total Alkalinity (mg L-1) 619 ± 7 395 ± 4 1459 ± 35 699 ± 47

Organic Acids (mg L-1) 305 ± 26 236 ± 10 918 ± 37 196 ± 49

Conventional Method Total Alkalinity (mg L-1) 340 283 1179 648

Organic Acids (mg L-1)

Not available in the conventional titration method

* The exact compositions of Brine #4 to #7 are shown in section S4 of the ESI. 3.4 Significance on mineral scale threat prediction In order to illustrate the significance of correctly evaluating solution alkalinity in the presence of organic acids and other minor species, the impact on mineral scale threat assessment is discussed hereafter. Mineral scale (scale) is the inorganic solid deposit from aqueous solution.2, 3 In oilfield operations, scale deposition is a major water-related operational issue threatening the operational safety and financial viability from reservoir to processing facilities. Scale deposition can lead to throughput reduction of oilfield operational systems and also the change of surface properties of the processing equipment.20-25 The severity of scale threat can be assessed by calculating the saturation ratio (SR) for a certain type of mineral scale. For instance of calcium carbonate (CaCO3) scale, SR can be calculated as: SR(CaCO3) =

(Ca2 + ) × (CO23 - )

(8)

Ksp (T,P)

where SR(CaCO3) corresponds to the saturation ratio of CaCO3 solid. (Ca2+) and (CO32-) denote the activities of calcium and carbonate species, respectively. The term Ksp 14 ACS Paragon Plus Environment

(T,P)

represents the

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solubility product of CaCO3 at a certain temperature and pressure condition. The notion of saturation index (SI) is also used to evaluate the tendency of scale threat and is defined as the base10 logarithm of SR as: SI(CaCO3) = log10[SR(CaCO3)] = log10

(Ca2 + ) × (CO23 - ) Ksp (T,P)

(9)

According to the definition of SI, if SI equals to zero, the aqueous system is regarded as in exact equilibrium with respect to the scale solid of interest; if SI is higher than zero, the solution is oversaturated with respect to the scale solid. Obviously, an increase in the calculated SI value indicates an increase of the scale threat. Calculation of SI for carbonate scales, such as calcium carbonate and iron carbonate, requires an accurate understanding of aqueous bicarbonate concentration in that bicarbonate species can be converted into carbonate species, followed by formation and deposition of metal-carbonate precipitates. Thus, correctly assessing aqueous phase bicarbonate concentration can be of vital importance in evaluating carbonate scale threat. As a matter of fact, many of the reported failure events in predicting carbonate scale threat are related to erroneous bicarbonate concentration determination.26 In order to demonstrate the significance of correctly assessing bicarbonate concentration for scale threat prediction, brine chemistry of a produced brine from a Norwegian oil production well (shown in section S8 of the ESI) was adopted for scale threat prediction. The brine solution was collected from a surface processing facility. The original brine composition (Brine #8 in the ESI) was modified to create two additional brines (Brine #9 & #10 in the ESI) with the same total alkalinity. These three brine compositions differ by their bicarbonate and acetate concentrations, where Brine #9 has only half of Brine #8 bicarbonate concentration and Brine #10 has no bicarbonate species. Concentrations of all other ionic species among these three brines are the same. Scale threats as well as solution pH were



calculated at a reservoir condition of 170C and 480 atm by use of the ScaleSoftPitzerTM (SSP 2018) software package.3

In the presence of an increasing amount of acetate and a decreasing amount of bicarbonate, the reservoir solution pH is calculated to reduce from 5.86 to 5.08, as shown in Figure 2. This is because the reduction in aqueous bicarbonate concentration leads to a decrease in the aqueous buffering capacity against protons, resulting in a lower pH caused by various aqueous phase deprotonation reactions.12 With the decrease of solution pH, the calculated reservoir scale threats for calcium carbonate (CaCO3) and iron carbonate (FeCO3) reduce as well. For instance, CaCO3 scale threat at reservoir condition is predicted to reduce from being oversaturated with an SI of 1.03 for Brine #8 to being undersaturated with an SI of -0.52 for Brine #10. A similar SI reduction was also predicted for FeCO3 scale, as shown in Figure 2. As discussed above, compared with the automated analytical method, the conventional method is unable to accurately determine solution alkalinity in the presence of considerable organic acids. This can result in an underestimated or overestimated carbonate scale threat for the oilfield operational facilities. Oilfield scale threat management strategy relies heavily on scale threat predictions.1-3, 20 An erroneous scale threat prediction can lead to inappropriate selection of scale management options. It is noteworthy to mention that due to the reduction of solution pH from Brine #8 to #10, pipeline corrosion threat is predicted to increase considerably. Especially, top of line corrosion threat can be exacerbated owning to the increase of acetate concentration.4 In other words, the results from conventional alkalinity measurement method can lead to an incorrect corrosion threat prediction. This might lead to incorrect selection of corrosion threat management options.


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Brine #8

Brine #9

Brine #10

Figure 2. Calculated solution pH and carbonate scale saturation index for a Norwegian oilfield brine and its modified compositions (Brine #8 to #10) at a reservoir condition of 170C and 480 atm

Adopting a similar approach, scale threats with respect to CaCO3 and FeCO3 and solution pH were predicted for the aforementioned four field brines (Brine #4 to #7 in the ESI) collected from a Texas shale basin reservoir. A comparison of the predicted scale threats was made between the brine compositions from the automated analytical method and the conventional method (Table 2). As discussed above, the conventional method generally underestimates the total alkalinity due to a lack of appreciation of the presence of organic acids. Note that these brine samples collected from reservoir should be in equilibrium with CaCO3 solid, i.e., SI(CaCO3)reservoir = 0. This is because the brine solutions have been in contact with CaCO3 solid present in the reservoir over a geological time duration and an equilibrium has been established.2 Table 2 shows that the four SI(CaCO3) values from the automated method were much closer to zero than the ones from the conventional method. This indicates that the total alkalinity values obtained from the automated method are more representative of the true alkalinity levels of these reservoir brines. In addition, comparing the difference of the calculated SI(CaCO3) values between these two methods for Brine #4 to #7, it shows that the difference for Brine #4 is smallest (-0.02 vs. -0.07) and the difference 17 ACS Paragon Plus Environment


for Brine #6 is the largest (0 vs. 0.26). This is because the bicarbonate concentration obtained from the automated analytical method for Brine #4 (619-305 = 314 mg L-1) is close to the value reported by the conventional method for Brine #4 (340 mg L-1); while the bicarbonate concentration from the automated method for Brine #6 (1,459 - 918 = 541 mg L-1) is significantly different from the value reported by the conventional method for Brine #6 (1,179 mg L-1). A similar conclusion can be made by examining the calculation results for FeCO3 scale where the difference in SI(FeCO3) for Brine #4 is smallest (-1.39 vs. -1.44) and the difference for Brine #6 is the largest (0.33 vs. 0.61).


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Table 2. Comparison of the calculated scale threats and solution pH values between the automated analytical method and conventional method for the four brines collected from a Texas shale basin (Brine #4 to #7 in the ESI) at a reservoir condition of 170C and 480 atm. Brine #4 Conventional Method

This Method

Total Alkalinity (mg L-1) Organic acids (mg L-1) SI (CaCO3) SI (FeCO3) pH

Brine #5 Conventional Method

This Method


This Method


This Method

619

340

395

283

1459

1179

699

648

305

N.A.*

236

N.A.

918

N.A.

196

N.A.

-0.02 -1.39 5.30

-0.07 -1.44 5.25

0.01 -1.73 5.59

0.13 -1.61 5.51

0.00 0.33 5.75

0.26 0.61 5.69

0.02 -2.36 5.42

0.06 -2.28 5.40

* N.A. stands for not available in the conventional method



4. Conclusions In this study, an analytical method was presented to simultaneously measure solution alkalinity and organic acid concentration of oilfield brine via an automated titration approach. This method eliminates the impact of sulfide species by sparging the brine sample with CO2 gas and also considers solution alkalinity originated from particulate solids. This method considers a number of common anionic species encountered in oilfield produced water, such as carbonate, organic acids, as well as borate, silica, phosphate, ammonia. The obtained solution pH and standard acid addition amount were utilized to calculate the solution alkalinity and organic acid concentration following a Newton-Raphson procedure. It shows that the automated analytical method is superior to the conventional method in terms of accurately measuring solution alkalinity and organic acid concentration with one titration effort. Moreover, introducing random error into the titration data has insignificant influence on the calculation results, indicating that this method is considerably robust. In addition, the significance of this method on mineral scale threat prediction was illustrated by calculating the mineral scale threats of field brine samples. It shows that the automated analytical method exceeds the conventional method in determining solution alkalinity with an enhanced accuracy for scale threat predictions. This is the first study to report such an accurate and convenient analytical method to measure solution alkalinity and organic acid concentrations for oilfield produced brine to facilitate oilfield corrosion and scale control. Given the accuracy and convenience of this method, this method can find wider applications in natural water resources management, industrial water management and environmental pollution control.


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5. Supporting Information Titration curves of two oilfield brines (S1); Expression of alkalinity calculation (S2); Compositions of three synthetic brines for alkalinity titration (S3); Compositions of four produced brines collected from a Texas shale basin at reservoir condition (S4); Schematic representation of the automated analytical apparatus (S5); Detailed derivation of the curve fitting equation for simultaneous alkalinity and organic acids titration method (S6); Titration curves of four Texas shale basin brines (S7); Original and modified compositions of brines from a Norwegian oilfield (S8).

6. Acknowledgements The authors appreciate the financial support of Science and Technology Development Fund, Macao S.A.R (FDCT) (0063/2018/A2). This work was also financially supported by Brine Chemistry Consortium companies of Rice University, including Aegis, Apache, BHGE, BWA, Chevron, ConocoPhillips, Coastal Chemical, EOG Resources, ExxonMobil, Flotek Industries, Halliburton, Hess, Italmatch, JACAM, Kemira, Kinder Morgan, Nalco, Oasis, Occidental Oil and Gas, Range Resources, RSI, Saudi Aramco, Schlumberger, Shell, SNF, Statoil, Suez, Total and the NSF Nanosystems Engineering Research Center for Nanotechnology-Enabled Water Treatment (ERC-1449500).




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An automated analytical method to determine solution alkalinity of

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