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IX. INHIBITOR EFFECTIVENESS ON CO2 CORROSION WITH SAND

Introduction

Erosion, corrosion, and erosion-corrosion are common problems in offshore pipelines, tubing and pipe fittings. Corrosion has an important impact on the total cost of oil and gas production. Considering the diversity of corrosion related problems, CO2 corrosion (sweet corrosion) is probably the material degradation mechanism most extensively assessed in this industry over the last 30 years. In the last decade, predictive models have experienced a major improvement in accuracy as well as in the development of mechanistic models of the chemistry involved in the CO2 corrosion process. Several empirical laboratory models, empirical field models and mechanistic models have been developed in this area and many parameters have been taken into account, including the effects of CO2 pressure, temperature, pH, chloride content, hydrodynamics and others. However, applicability of these models when sand is produced is still not clear.

Chemical inhibition is one of the most common methods for controlling corrosion and erosion-corrosion of mild steels. Inhibitor performance is affected by different parameters including temperature, inhibitor concentration, flow velocity, sand erosion, water cut, metal cations, chlorides, type of metal, electrolytes, pH, flow geometry and other factors [1-10]. Considerable research in the oil and gas industry has been devoted to the development of inhibitor systems that can reduce corrosion rates in production equipment to acceptable levels. As a result, methodologies have been developed for predicting inhibitor efficiency as a function of environmental conditions and inhibitor concentration. However, prior to field testing, very little is known about how the efficiency of an inhibitor is affected by oil and the erosive action of sand particles entrained in the flow stream. The importance of oil and sand particle erosion on corrosion and inhibitor performance are discussed in the following paragraphs.

Hydrocarbons such as crude oil, natural gas, and natural gas condensates are very poor electrolytes because they have very high resistivity. Oilfield corrosion is usually caused by chemicals in the water phase that lower the natural resistivity of water [11]. The effects of crude oil on the CO2 corrosion rate is a wet ability effect and relates to a hydrodynamic condition where crude oil entrains the water and prevents it from wetting the steel surface

(continuously or intermittently) [12]. The presence of oil was also found to decrease the effectiveness of the inhibitor in reducing the corrosion of AISI 1018 carbon steel compared to water without oil. [13]. Corrosion inhibitor can accumulate in the oil-water interface of emulsion droplets and significantly reduce the effective inhibitor concentration in the water phase. Theoretical estimates indicate that inhibitor can be depleted from the water phase if the total oil droplet surface area exceeds 1 m2/liter (order of magnitude). Emulsification can be critical for inhibition, causing increased corrosion risk and excessive inhibitor consumption. The sensitivity of the inhibitor to oil-in-water emulsions was found to be dependent on the inhibitor formulation [14]. Under certain conditions oil-in-water emulsions may promote oil wetting and thus contribute to improved corrosion protection [14].

Sand erosion decreases inhibitor efficiency [15-17] and raises the inhibitor concentration required for optimum inhibitor effectiveness [4]. McMahon et al. [18] showed that large amounts of corrosion inhibitor can be lost from the bulk solution by adsorption of inhibitor onto the surfaces of produced sand particles. This effect only becomes significant for high concentrations of sand and small particle sizes, especially for oil-wetted particles. On the other hand, Ramachandran et al. [19], showed that the effect of inhibitor loss due to sand adsorption is small for industrial corrosion inhibitors used under field conditions. Tandon et al. [15] showed that for non-scale-forming conditions with sand, inhibitor protection provided at concentrations of 100 ppm and above appeared not to be affected much by the addition of small amounts of sand [15]. Tummala et al. showed that inhibitors that are effective in a CO2-saturated static brine are not necessarily effective under erosion-corrosion conditions [20]. Therefore, interactions of sand particles with chemical inhibitors in oil and gas wells depend on many parameters including inhibitor characteristics, water cut, erosivity, and corrosivity of the system.

One of the existing empirical models for prediction of the likelihood of erosion-corrosion inhibition success in the oil and gas industry was suggested by Crossland et al. [21]. They defined four different regions for inhibitor performance which can be used for estimating the amount of the inhibitor needed to achieve corrosion rates lower than 0.1 mm/y as a function of temperature, shear stress, and total dissolved solids.

The need to be able to predict inhibitor performance under sand production conditions is particularly acute when the wells are deep or off-shore because of the difficulty in running coupon tests to evaluate inhibitor efficiency at critical points throughout a system which might involve a number of wells flowing into a single header. Further, it would be highly desirable to be able to make decisions on the design of the well given advanced knowledge of the inhibition options and their predicted effectiveness.

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In the current study, a new approach has been developed for predicting corrosion part of inhibited erosion-corrosion rate based on inhibitor adsorption isotherms, mechanistic models for predicting CO2 corrosion rates, mechanistic models for predicting sand particle erosion rates, and an empirical correlation for including the effects of oil, and iron-carbide accumulation. The effect of oil on CO2 corrosion behavior was also studied for different sets of pH and temperature. Synergistic effects of sand particle erosion with corrosion of carbon steel under scale and non scale-forming conditions, in a CO2-saturated system, and in the presence of oil and an inhibitor were also examined. Metal loss rates are measured by long-term weight loss, and linear polarization resistance (LPR) techniques. Potentiodynamic polarization and Electrochemical Impedance Spectroscopy (EIS) are also used to examine the electrochemical mechanisms of corrosion and inhibition.

Experimental Procedure

Corrosion, erosion, and erosion-corrosion experiments were carried out in single-phase water and two-phase water/oil flow loops, referred to as Miniloop #1 and Miniloop #2 respectively. The flow geometry used for these experiments was direct impingement. The liquid circulated in the loop was CO2-saturated brine and impinges the carbon steel target at different flow velocities. More details about Miniloop #1 can be found in reference [22]. A schematic of the Miniloop #2 is shown in Figure IX-1. The piping of the loop is constructed of 316L stainless steel material due to its high resistance to corrosion and pitting. The loop is operable at pressures up to 1.13 MPa and at temperatures up to 93°C. The major components of the loop are the test section, sand/inhibitor injector, cyclone separator, tank and circulation pump. A test solution of 19 liters (5 gallons) was introduced into the tank with a maximum capacity of 37.85 liters (10 gallons) and de-aerated using a vacuum pump in order to remove dissolved oxygen present in the test solution. The oxygen content in the solution was maintained at a concentration less than 10 ppb. The test solution was then pressurized with CO2 for 24 hours.

The test solution was circulated in the system at flow velocities in the range of 9-60 m/s. Direct measurement of the solution flow velocity through the jet nozzle impinging orthogonal to the test specimen could not be achieved due to the compact size of the test section which prevents the use of the ultrasonic flow meter. Therefore, velocities were estimated from the exit pressure using Bernoulli’s equation. The pressure difference between the total and static pressures was measured using a Pitot-tube and a digital

manometer. The pH of the test solution was monitored before and after the tests in the by-pass section between the tank and the pump using a temperature-compensated pH probe. The pH probe was calibrated prior to each test and corrected for high chloride content [23]. In order to maintain the desired pH of the test solution, HCl or NaOH was injected into the system as needed by means of a dosing pump.

Figure IX-1: Schematic of the Two-Phase Water/Oil Flow Loop (Miniloop #2)

Electrochemical measurements were carried out within the test cell using the test specimen (X65) as the working electrode, a 316 stainless steel rod as a reference electrode, and 316 stainless steel as the counter electrode.

Corrosion, erosion, and erosion-corrosion measurements were made using different methods such as weight loss (WL), linear polarization resistance (LPR), Electrochemical Impedance Spectroscopy (EIS), Potentiodynamic Polarization (PDYN), and 3D profilometer methods. For weight loss and 3D profilometer measurements, initial and final weights and surface topography of the test specimen were measured. Before and after each test, the specimen was cleaned with acetone and dried prior to measurements. LPR, EIS, and PDYN measurements utilized a potentiostat operating in a three-electrode arrangement. The Tafel slope for each LPR test conditions was measured by running a potentiodynamic polarization test.

The test solution consisted of 18 wt % NaCl, 1000 ppm NaHCO3, and 50 ppm CaCl2 dissolved in distilled water. The other major test parameters were two temperatures of 57°C,

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and 93°C, and a CO2 pressure of 2.4 bars. Test parameters are summarized in Table IX-1. More details about the experimental set up and procedure can be found in References [23, 24].

A probe designed by Erosion/Corrosion Research Center (E/CRC) investigators was also used to estimate penetration rates with the LPR and EIS technique. This reference electrode is surrounded by a ceramic coating which is then surrounded by X65 carbon steel which acts as the working electrode.

Table IX-1: Summary of Important Test Parameters PARAMTERS Flow Loop ConditionsWater Cut 40 and 100% (Mineral Oil containing no inhibitor) Temperature 57 and 93 °C pH 3.5, 4.8, 5, and 6 Test solution composition 18 % NaCl, 1000 ppm NaHCO3, 50 ppm CaCl2 Flow velocity 9.4 m/s Gas, Partial pressure CO2, 2.4 bars Material tested API X65 Geometry Direct Impingement Average Sand size 150 μm Measurement techniques Weight loss, LPR, 3D Profilometer, EIS, and PDYNDissolved Oxygen Less than 10 ppb Inhibitor Concentration 0, 10, 25, 50, 100, 150, and 250 ppm

Results

Inhibitor Performance Characterization

Adsorption is the basic mechanism for corrosion protection by imidazoline-based inhibitors. Adsorption depends on the molecule’s chemical composition, the temperature, and the electrochemical potential at the metal/solution interface. Different inhibitor adsorption isotherms have the general form of Equation (1),

where Ka/d is an adsorption/desorption constant; Cinh is the inhibitor concentration; H(θ,n) is

the configurational factor, which depends upon the physical mode and the assumptions underlying the derivation of the isotherm; “θ” is the surface coverage by inhibitor; “n” is the ratio of the inhibitor molecule coverage to that of the water molecule coverage; and “f” is an adjustable parameter accounting for the interaction between adsorbed inhibitor molecules..

An inhibitor adsorption isotherm is governed by the interaction of inhibitor molecules with the metal surface and by their mutual interactions. Inhibitor adsorption isotherms can be developed by corrosion rate measurements for different inhibitor concentrations. The Frumkin isotherm can be used when both the interaction of inhibitor molecules with the metal surface and mutual interactions of inhibitor molecules are important [25]. For this work, the Frumkin isotherm in Equation (2) shows the best fit to the experimental data.

.Surface coverage by the inhibitor can be calculated based on corrosion rate data at different inhibitor concentrations using Equation (3) or charge transfer resistance (Rct) data from EIS test results using Equation (4).

where θ is surface coverage by inhibitor and ranges from 0 to 1, (CR)θ is the corrosion rate when the fraction of metal surface protected by inhibitor is θ, (CR)θ=0 is the corrosion rate when there is no inhibitor in the system, (Rct)θ is the charge transfer resistance when the metal is protected by inhibitor, and (Rct)θ=0 is the Rct when there is no inhibitor in the system.

Figure IX-2 shows potentiodynamic polarization curves for different inhibitor concentrations at T=57oC, pH=4.8, and 40% water cut. Adding inhibitor to the system shifts both cathodic and anodic polarization branch curves to the lower current densities (Figure 2). Therefore, the imidazoline-based inhibitor used in this study decreased both cathodic and anodic corrosion reactions by blocking the active sites of cathodic and anodic reaction on the metal surface and, consequently, decreased the corrosion rate.

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Figure IX-2: Potentiodynamic Polarization Curves for Different Inhibitor Concentrations at T=57oc, pH=4.8, And 40% Water Cut

EIS was also used in this research to study the inhibition mechanism in more details. Figure IX-3 shows EIS Nyquist plots for CO2 corrosion of carbon steel for different inhibitor concentrations at T=57oC, pH=4.8, and 40% water cut. According to Figure 3, increasing the inhibitor concentration up to 150 ppm increases impedance which means that increasing the inhibitor concentration increases the Rct and decreases the corrosion rate. The impedance diagrams shown in Figure IX-3 are not ideal semicircles which may due to by surface heterogeneity due to surface roughness, impurities, and dislocations [26]. The depressed semicircular shape in the complex impedance plane, with the center under the real axis, is a typical behavior for solid metal electrodes and shows frequency depression of the impedance data. Therefore, a Constant Phase Element (CPE) is used to fit the experimental data rather than an ideal capacitor to account for the non-ideal frequency response.

The equivalent circuit used in this study for interpretation of EIS data is shown in Figure IX-4. An excellent fit with the model was obtained for all experimental data. The equivalent circuit fit follows the same pattern as the experimental results. By analysis of impedance spectra, values of the main parameters, including Rct, Yo, and “a” at different inhibitor concentrations, were obtained and are listed in Table 2. Solution resistance (Rs) values for different inhibitor concentrations in 40% water cut (Table 2) were more than three times higher in comparison with previous data at 100% water cut [22] which indicates that how adding oil to the system and creating an emulsion changes the conductivity of the solution and affects the corrosion behavior. In Table IX-2, the double layer capacitance (Cdl)

was calculated by Equation (5):

where Yo and “a” are CPE parameters. The parameter “a” of the CPE is an indicator of electrode surface roughness or heterogeneity, and the parameter “Yo” is considered to be the CPE admittance. Experimental data at different inhibitor concentrations show that the CPE admittance value decreases by increasing the inhibitor concentration (Table IX-2) which means that adding inhibitor to the system decreases the Cdl since there is a direct relation between CPE admittance and Cdl, Equation (5). Lower Cdl causes smaller driving force for electron tunneling, charge transfer, and subsequently slower corrosion reactions. Therefore, adsorption of inhibitor molecules on the metal surface decreases the corrosion rate by decreasing the Cdl and also increasing the Rct.

Inhibition efficiency in Table IX-2 was calculated according to Equation (6). According to Table 2, inhibition efficiency increases as inhibitor concentration increases.

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Figure IX-3: EIS Nyquist Graphs of Erosion-Corrosion Test Results for Different Inhibitor Concentrations

Figure IX-4: Equivalent Circuit for Analysis EIS Data

Table IX-2: Circuit Parameters for Different Inhibitor Concentrations

Inhibitor Concentration

(ppm)

Rs (Ω cm2)

Rct (Ω

cm2)

Yo (Ω-1 cm-2 sn ×

104) a

0 0.661 11.06 34.54 0.955

10 1.132 13.09 108.1 0.887

25 1.038 61.3 20.67 0.938

50 1.078 101.06 26.29 0.868

100 1.0285 107.8 7.58 0.746

250 1.337 138.3 1.62 0.891

Effect of Oil on CO2 Corrosion Behavior

Table IX-3 shows an average of four corrosion tests with dispersion of ±5% at two

different water cuts using different electrochemical and non-electrochemical techniques. These flow loop experiments shows that adding oil to the system (60% Oil Cut) slightly reduces the corrosion rate by decreasing the water wetted surface area of the specimen at T=57oC and pH=4.8. Oil can either be dissolved in the aqueous phase and then be adsorbed onto the metal surface, or form a stable emulsion with less conductivity than the pure brine solution, which reduces the corrosion rate and also modifies the morphology of corrosion products [27]. Oil also decreases the anodic dissolution of steel due to the formation of a layer of oily phase on the steel surface, increasing the reaction activation energy [28]. Agreement between electrochemical techniques and non-electrochemical techniques also shows that electrochemical measurement techniques in 40% water cut with a mineral oil containing no inhibitor can be used reliably.

Table IX-3: Average Corrosion Test Results at Two Different Water Cuts at T=57oC and pH=4.8

Water Cut (%) C.R. (mm/y)LPR W.L. 3D profile

100 12.63±5% 11.4±5% 11.45±5%

40 10.55±5% 10.57±5% 10.83±5%

Different behavior was observed in the presence of oil at T=93oC and pH=5.0. LPR and EIS measurements (Figure IX-5 and Figure IX-6, respectively) after several tests showed that adding oil to the system considerably reduces the corrosion rate. Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), and Energy Dispersive Spectroscopy (EDS) analysis of the surface of the specimen after the corrosion test at 40% water cut showed that a continuous iron-carbonate scale had formed on the surface of the specimen (see Figures IX-7, IX-8).

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Figure IX-5: LPR and Weight Loss Corrosion Test Results at T=93oc and pH=5.0 for 40 and 100% Water Cut

Figure IX-6: EIS Corrosion Test Results at T=93oC and pH=5.0 for 40 and 100% Water Cut

Figure IX-7: SEM Image of the Surface after the Corrosion Test at 40% Water Cut and at T=93oC and pH=5.0

Figure IX-8: XRD Analysis of the Surface after the Corrosion Test at 40% Water Cut and at T=93oC and pH=5.0

Effect of Oil on Inhibitor Performance in CO2 Systems

Several techniques (LPR, EIS, PDYN, WL, and 3D profilometer) were used to study

the effect of oil on CO2 corrosion inhibition. Corrosion rate measurements showed that adding inhibitor to the system decreases the corrosion rate for T=57oC and pH=4.8. Figure IX-9 shows weight loss corrosion test results for different inhibitor concentration at T=57oC and pH=4.8 at two different water cuts. When there is no inhibitor in the system, adding oil decreases the CO2 corrosion rate by decreasing the conductivity of the solution and blocking

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some of the corrosion active areas. However, when there is some inhibitor in the system, adding oil to the system increases the corrosion rate slightly by reducing the inhibition efficiency (Figure IX-9). Inhibitor residual concentration measurements using a standard method for imidazoline based inhibitor concentration measurement showed that approximately 10% of the inhibitor added to the system dissolves in the oil phase for the test conditions of this research. Therefore, the presence of oil decreases the inhibition efficiency by reducing the concentration of the inhibitor in the water phase. Some of the inhibitor also stays in the water/oil interface in the emulsion which also decreases the inhibitor concentration in the water phase and consequently the inhibition efficiency. The Frumkin isotherm also was fitted to the experimental data (Figure IX-10) to show the effect of oil on inhibition efficiency.

0

3

6

9

12

15

0 10 25 50 100 150 250

Corrosion Rate (mm/y)

100 % water cut40% water cut

Inhibitor Concentration (ppm)

Figure IX-9: Weight Loss Corrosion Test Results at T=57oC and pH=4.8 at Two Different Water Cuts and Seven Different Inhibitor Concentrations

Figure IX-10: Frumkin Isotherm Fitted to Experimental Data at T=57oC and pH=4.8 at Two Different Water Cuts and Seven Different Inhibitor Concentrations

Prediction of Inhibited Corrosion

The Frumkin isotherms for different sets of pH and temperature with and without sand were used in order to predict the inhibited CO2 corrosion rate as a function of inhibitor concentration. These isotherms were used to calculate the surface coverage by the inhibitor or percent of area exposed to corrosion that is protected by the inhibitor. Then, a mechanistic model for prediction of CO2 corrosion rate (i.e. SPPS1:CO2 [29]) was used to calculate the electrochemical parameters such as electrochemical reaction rate constants, mass transfer constants, corrosion potential and etc. Percent area that is protected by the inhibitor (the inhibitor coverage) was integrated into the mechanistic model to reduce the active surface area. The mechanistic model then predicts the inhibited corrosion rate based on the remaining unprotected area. The Frumkin isotherm was not applied to the mass transfer reaction because potentiodynamic polarization test results showed that the corrosion reaction is not diffusion controlled. Therefore, charge transfer controls the corrosion reaction and there is no need to modify the mass transfer equations in the mechanistic model for prediction of CO2 corrosion rate. The effects of oil, temperature and pH are also included in corrosion rate prediction using the mechanistic model for prediction of CO2 corrosion rate. Prediction of CO2 corrosion rate shows good agreement with experimental data at four different sets of pH and

1 Sweet Production Pipe Saver:CO2 (SPPS:CO2), Erosion/Corrosion Research Center, The University of Tulsa, OK, USA

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temperature, with and without oil, for the range of inhibitor concentration between 0 and 250 ppm. Figure IX-11 shows predicted CO2 corrosion rates versus measured corrosion rates over a range of inhibitor concentrations for two different water cuts at T=57oC and pH=4.8. Figure IX-12 shows the predicted CO2 corrosion rates versus measured corrosion rates for four different sets of pH and temperature.

0.1

1

10

100

0.1 1 10 100

Corrosion Rate Prediction (mm/y)

Corrosion Rate by Experiment (mm/y)

100% Water Cut40% Water cut

0

1510

25

150

100

250

0

1025

50

50

100 ppm

Perfect Match

Figure IX-11: Comparison Between Experimental Corrosion Data and Prediction Of CO2 Corrosion Rate Using a Mechanistic Model after Integrating the Frumkin Isotherm for Different Inhibitor Concentrations (With and Without oil at T=57oC and pH=4.8)

0.1

1

10

100

0.1 1 10 100

Corrosion Rate Prediction (mm/y)

Corrosion Rate by Experiment (mm/y)

T=57C, pH=3.5T=57C, pH=4.8T=57C, pH=6.0T=93C, pH=5

0

1

25

150

100

250

0

5

10

25

50 ppm

50

100Perfect Match

Figure IX-12: Comparison Between Experimental Corrosion Data and Prediction of CO2 Corrosion Rate Using a Mechanistic Model after Integrating the Frumkin Isotherm for Different Inhibitor Concentrations (at 100% Water Cut, Without Sand at Four Different Sets of Temperature and pH) Effect of Sand Erosion on Inhibitor Performance

An increase in surface roughness by erosion can intensify the corrosion processes by

increasing the surface area of the specimen subjected to corrosion. Surface roughness also increases the corrosion rate because electron density in the indentations of the surface is higher; the higher density of electrons increases the corrosion rate. Corrosion may also accelerate the erosion rate by creating a favorable surface roughness for erosive action.

The erosion part of erosion-corrosion can be thought of as having two components: 1) pure erosion, and, 2) erosion affected by corrosion. Likewise, the corrosion part of erosion-corrosion also can be thought of as having two components: 1) pure corrosion, and, 2) corrosion affected by erosion.

The effects of sand erosion on the surface morphology of a low carbon steel under three different conditions: pure erosion, erosion-corrosion without iron-carbonate scale, and erosion-corrosion with iron carbonate scale are shown in Figure IX-13. Comparison between Figure IX-13 (a) and (b) shows how sand particle erosion changes the surface morphology by deforming the base metal and creating craters. The pure erosion of a mild-steel by sand particles provides a good example of the pure erosion mechanism for ductile

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materials. However, the synergistic effect of sand erosion and CO2 corrosion proved to have a stronger effect on surface morphology of the carbon steel, Figure IX-13 (c). Surface degradation by corrosion makes the metal surface more susceptible to sand erosion and increased deformation can be seen in the SEM image of the surface. More craters were observed on the surface because corrosion increased the surface roughness. Corrosion increases the surface roughness by accelereated corrosion rates at grain boundaries and impurities on the surface. Sand erosion in the presence of iron-carbonate scale showed a different mechanism to some extent Figure IX-13 (d). Fewer craters and surface deformations were observed in comparison with non-scale-forming conditions. This can be explained by considering the non-metallic characteristics of iron-carbonate scale layer. Iron-carbonate scale as a ceramic material tends to have a more brittle mechanical behavior which affects the erosion mechanism.

Figure IX-13: SEM Images of Surface Morphology (a) before Experiment, (b) after Pure Erosion, (c) after Erosion-Corrosion under Non-Scale Forming Condition, and (d) after Erosion-Corrosion under Scale Forming Condition.

Prediction of Inhibited Erosion-Corrosion

Many factors affect erosion-corrosion mechanisms and the synergistic effects that

occur between erosion and corrosion of mild steels. Addition of inhibitors brings another order of complexity to the phenomenon. However, in order to make engineering predictions of erosion-corrosion with inhibitors, some simplifying assumptions can be made. As more information becomes available, accuracy of the models can be improved. In order to estimate an inhibited erosion-corrosion rate, erosion-corrosion can be considered to consist of two parts: the erosion part of erosion-corrosion; and, the corrosion part of erosion-corrosion. The erosion part of erosion-corrosion has two components: pure erosion; and erosion affected by corrosion. Pure erosion can be predicted using an available mechanistic model for prediction of erosion rate [30] (e.g., SPPS2 model). In this research, the erosion affected by corrosion term was found to be small in comparison with the other erosion-corrosion terms [31]. Therefore, as a practical approximation, if the erosion affected by corrosion component is neglected for these test conditions, the erosion part of inhibited erosion-corrosion can be considered to be approximately equal to the pure erosion rate as indicated in Equation (7).

The corrosion part of erosion-corrosion is a function of inhibitor concentration and can be predicted based on the available Frumkin inhibitor adsorption isotherms. However, for application to erosion-corrosion situations, the Frumkin adsorption isotherm must be modified to include erosivity as a factor.

As mentioned earlier, the Frumkin isotherm (Equation (2)) has two constants: adsorption/desorption constant, “Ka/d”; and mutual interaction of inhibitor molecules constant, “f”. In the derivation of Ka/d [32], Ka/d is an exponential function of the entropy change occurring over the adsorption process (Equation (8)).

(2) Sand Production Pipe Saver (SPPS), Erosion/Corrosion Research Center, The University of Tulsa, OK, USA

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where, Ka/d is the adsorption/desorption constant, ΔSads is the adsorption entropy change, and R is the universal gas constant. Entropy is an expression of disorder, or randomness, in the system. Sand erosion and increases in temperature also cause changes in the adsorption entropy and affect the adsorption/desorption process of the inhibitor on the surface and, in turn, affect the value of Ka/d. It is assumed, for the prediction method used in this manuscript, sand erosion and temperature affect the adsorption /desorption constant; although, they do not have a significant effect on the constant f representing the mutual interaction of inhibitor molecules. Therefore, an empirical equation for the adsorption/desorption coefficient Ka/d has been developed as a function of the pure erosion rate and temperature based on experimental data for two values of temperature and three values of erosivity from data presented in this paper and from the work described by Dave et al. [17]. Therefore, the modified Frumkin isotherm is written as:

Parameters were defined in order to include the effects on inhibited erosion-corrosion due to an oil phase and/or iron-carbonate scale formation, and inhibitor effectiveness (Coverage). The Effective Active Area (EAA), representing the metallic surface area fraction not protected is shown in Equation (10) where AAF (Active Area Fraction) represents the surface area left uncovered by oil or iron carbonate scale, and θ represents the inhibitor coverage as determined by the modified Frumkin isotherm.

EAA = AAF × (1-θ) (10)

The modified Frumkin isotherm developed in this study can be used to estimate the inhibited erosion-corrosion rate in the temperature range 57 to 93°C and different erosion rates. Experimental data and the calculated corrosion part of inhibited erosion-corrosion at an erosion rate of 4.06 mm/y and for two different temperatures, 57 and 93oC, are shown in Figure IX-14 and Figure IX-15, respectively.

The Prediction of the corrosion part of inhibited erosion-corrosion using the modified Frumkin isotherm (Equation 9) and empirical equation for including the effect of oil, iron-carbonate scale, and iron carbide accumulation (Equation 10), shows good agreement with the experimental data in this research for different inhibitor concentrations and two different temperatures of 57 and 93oC. Total inhibited erosion-corrosion rate can be also predicted using Equation (9).

0

2

4

6

8

10

0 50 100 150 200 250Inhibitor concentration (ppm)

Measured

Predicted

Figure IX-14: Prediction of Corrosion Part of Inhibited Erosion-Corrosion at T=57oC, pH of 4.8, 40% Water Cut, And Erosivity of 4 mm/yr

0

3

6

9

12

15

0 50 100 150 200 250Inhibitor concentration (ppm)

Measured

Predicted

Figure IX-15: Prediction of Corrosion Part of Inhibited Erosion-Corrosion at T=93oC, pH of 5.0, 40% Water Cut, and Erosivity of 4 mm/yr

Corrosion part of Erosion-Corrosion (mm/yr)

Corrosion part of Erosion-Corrosion (mm/yr)

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A computer program was developed based on this research which is able to predict the inhibited erosion corrosion rate (pure erosion rate plus corrosion part of inhibited erosion-corrosion) as a function of erosivity of the system (particle concentration, superficial liquid velocity, superficial gas velocity, particle size, geometry, pipe diameter, pipe roughness, particle density, particle sharpness, and etc.) and corrosivity of the system (pH, temperature, water cut, CO2 pressure, NaCl concentration, NaHCO3 concentration, Fe2+ concentration, superficial liquid velocity, superficial gas velocity, and etc.). Figure IX-16 shows the prediction of inhibited erosion-corrosion rates in an elbow as a function of inhibitor concentration and erosivity of the system at 4.8 pH, 57oC, 40% water cut, 18% NaCl concentration, Vsl=0.6 m/s, and Vsg=24.4 m/s. Prediction of inhibited erosion-corrosion rates at a range of inhibitor concentrations and erosivities shows that increasing inhibitor concentration reduces the inhibited erosion-corrosion rate, and lower erosivities result in lower inhibited erosion-corrosion rates.

Figure IX-16: Prediction of Inhibited Erosion-Corrosion Rate as A Function of Inhibitor Concentration and Erosivity of the System at pH=4.8, T=57oC, 40% Water Cut, 18% NaCl, Vsl=0.6 m/s, and Vsg=24.4 m/s.

Conclusions

Imidazoline based inhibitor used in this research with API X65 carbon steel appeared to be very effective in reducing the corrosion part of erosion-corrosion, in erosion-corrosion conditions with 0.25 wt% sand concentration under the 9.4 m/s direct impingement of a CO2-saturated 18% NaCl solution and 40% water cut, although not quite as effective as for similar tests without sand. Sand erosion reduces the inhibitor efficiency by partially removing the inhibitor protective layer from the surface and also, to a lesser extent, by the adsorption of inhibitor on sand. Oil wetted sand adsorbed more inhibitor in comparison with water wetted sand particles. Flow loop experimental results showed that the imidazoline-based inhibitor used in this research physically adsorbs on the metal surface. Adsorption of inhibitor molecules on a water wetted surface of API X65 carbon steel was stronger than on the oil wetted surface.

The Frumkin adsorption isotherm at 40% water cut and different sets of pH and temperatures were integrated into a mechanistic model for prediction of CO2 corrosion which showed good agreement with experimental inhibited corrosion data.

A new approach was described for prediction of the corrosion part of inhibited erosion-corrosion and total inhibited erosion-corrosion rates as a function of inhibitor concentration, temperature, water cut, and erosivity of the system. Two main assumptions of this approach are neglecting the erosion affected by corrosion component, and any effect the erosivity might have on the mutual interaction of inhibitor molecules. The Frumkin inhibitor adsorption isotherm was modified to include the effects of erosivity and temperature using experimental data and basic concepts in developing the Frumkin isotherm. An empirical correlation was also developed to include the effect of oil, iron-carbonate scale formation, and accumulation of iron-carbide on the surface for a range of temperature, pH, water cut, and erosivity conditions. Predicted values of the corrosion part of inhibited erosion-corrosion rates for a range of inhibitor concentrations showed good agreement with flow loop experimental data.

Erosion-Corrosion Inhibition JIP

A new JIP has been initiated to follow-up on the work that was done for Petrobras.

The new JIP is called the Erosion-Corrosion Inhibition JIP. The JIP research will be aimed at the specific needs of the sponsoring companies, while at the same time addressing the science and technology needs that are common to all members. Petrobras is the first company to join the JIP, and we are actively seeking additional members.

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The objectives of the JIP are to experimentally characterize inhibitor effectiveness for the erosion-corrosion conditions that interest your company, and to improve and expand the computer program that we developed for Petrobras to include broader ranges of erosion-corrosion conditions and possibly new inhibitors. Central to all the research in this JIP are CO2 corrosion, solid particle erosion, chemical inhibition, chloride concentration, oil phase, and multiphase flow. We intend to build on our experience with the project for Petrobras, develop some new tools for our experimental investigations and for predicting inhibited erosion-corrosion, and explore the new directions in which the needs of our member companies lead us.

One advancement that shows good promise for the experimental work is the development of the three test cell flow loop, Figure IX-17.

Figure IX-17. Flow loop with three in-line test cells The loop handles oil, water and sand. Downstream of the pump are the three in-line

test cells. The idea of the three cells is to be able to measure the erosion component of

erosion-corrosion, the corrosion component of erosion-corrosion, and the total erosion-corrosion in the same test. The arrangement of the three test cells is shown in Figure IX-18.

From Tank

Erosion-Corrosion Test Output:

1- Total Erosion-Corrosion rate using X65 ER probe and also X65 weight loss probe

2- Pure Erosion using Inconel 625 ER probe

3- Corrosion part of Erosion-Corrosion using X65 electrochemical probe

• Erosion-corrosion can be monitored even at low water cuts

Pump

From Tank

Erosion-Corrosion Test Output:

1- Total Erosion-Corrosion rate using X65 ER probe and also X65 weight loss probe

2- Pure Erosion using Inconel 625 ER probe

3- Corrosion part of Erosion-Corrosion using X65 electrochemical probe

• Erosion-corrosion can be monitored even at low water cuts

Pump

Figure IX-18 Three In-line Test Cells

One ER probe cell monitors the erosion of a CRA. Another ER probe cell monitors the total erosion-corrosion of the carbon steel material under study. A third cell has an electrochemical probe and monitors the corrosion component of erosion-corrosion.

Figure IX-19 shows the output for a test involving ER probes in two of the cells: Cell 1 has an X65 probe; Cell 2 has an Inconel probe. The test is an erosion test using de-aerated distilled water under a blanket of nitrogen and sand as the eroding particle. The results indicate that under similar conditions, the erosion rate for the Inconel was a little less than the erosion rate for the X65 carbon steel material, which is not an unexpected result.

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Figure IX-19. Results from an erosion test with sand and nitrogen over distilled water.

Results from another test to calibrate and validate the three, in-line test cell design is shown in Figure IX-20. This is another erosion test involving sand, distilled and de-aerated water, and oil under a nitrogen blanket. Cell 1 and cell 3 each hold an X65 probe. Results after about 180 minutes indicate that the erosion rates for the two X65 probes were essentially identical. This result provides further confidence in the three, in-line test cell concept.

Figure IX-20. Erosion test with sand, distilled water, and oil under a nitrogen blanket.

In addition to providing experimental data for environmental conditions interesting to member companies, the JIP intends to improve and expand the computer program developed for Petrobras for predicting inhibited erosion-corrosion and for selecting inhibitor concentrations appropriate for controlling erosion-corrosion. This program presently handles many variables over a range of environmental conditions. But, one of the main objectives of the JIP is to expand and improve the computer program through incorporation of new data from the new JIP – cover a wider range of water cuts, for example (the existing program handles only 100% and 40% water cut), handle FeCO3 scale formation and erosion of same (the existing program assumes that the scale is completely removed if there is sand), handle low sand concentrations.

Deliverables for the Erosion-Corrosion Inhibition JIP include the following: • Report

o Methodology used Number of tests needed to characterize the modified inhibitor

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adsorption isotherm Inhibitor adsorption isotherm development process Integration of developed isotherms into the computer program

o Results of testing (company specific cases) Conditions tested Test results Isotherms developed Inhibited erosion-corrosion rates

• Computer program o Each company will receive a computer program that will predict the

erosion-corrosion rate for your company’s conditions o The computer program will also be improved and expanded to

include additional conditions through the use of data from the other member companies that allow us to use it.

If your company is interested in joining this new JIP, or you are interested in

learning more about it, please contact Dr. Siamack Shirazi: siamack-shirazi@utulsa.edu, (918) 631-3001

Acknowledgments

The authors would like to acknowledge the financial support of this research by the PETROBRAS Company, the technical support of E/CRC Senior Technician Ed Bowers, and Mr. Faisal Al-Mutahar PhD candidate at the University of Tulsa.

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