Quantitative Evaluation of the Efficiency of Water-in-Crude-Oil

Article pubs.acs.org/IECR

Quantitative Evaluation of the Efficiency of Water-in-Crude-Oil Emulsion Dehydration by Electrocoalescence in Pilot-Plant and FullScale Units Patrícia Suemar,† Elizabeth F. Fonseca,† Raquel C. Coutinho,§ Fabricio Machado,‡ Rafael Fontes,‡ Luís Carlos Ferreira,‡ Enrique L. Lima,§ Príamo A. Melo,§ José Carlos Pinto,§ and Márcio Nele*,‡,§ †

Petrobras/CENPES, Cidade Universitária Q.7, CEP 21949-900 Rio de Janeiro, RJ, Brasil Escola de Química and §Programa de Engenharia Química da COPPE, Universidade Federal do Rio de Janeiro, Cidade Universitária, CP 68502, Rio de Janeiro 21945-970, Brasil

‡

ABSTRACT: The electrostatic dehydration of crude-oil emulsions were investigated using pilot-plant and industrial data. The experimental data obtained with seven different crudes over a wide range of viscosities in a pilot plant showed that the electric field and the residence time were the most important operating variables. Various crude-oil properties influenced the emulsion stability, including the total acid number and the resin, asphaltene, and metal contents, but their effects were statistically correlated with the crude-oil viscosity and density. Using pilot-plant data, a power-law model relating the water content in the treated oil to the dehydration operating conditions and the crude-oil viscosity and density was developed to aid in the design and evaluation of industrial units. The model was tested against industrial data and found to be able to predict very well the performance of the industrial units.

■

INTRODUCTION

while the electrophoretic force promotes droplet movement in the region between the electrodes. Modeling of the forces acting on the water droplets coupled with the separator hydrodynamics and interdroplet interactions is very difficult. To the best of our knowledge, the design of electrocoalescence equipment is carried out using pilot-plant data and empirical correlations. Empirical modeling of electrocoalescence is an important tool for improving crude-oil production and refining processes. Abdul-Wahab et al.13 showed that the temperature, settling time, mixing time, dilution water, and other parameters influence the performance of the desalting process. They pointed out that the electrocoalescence dehydration process can be described only by a highly nonlinear model, such as an artificial neural network, that is able to model the nonlinear relationships of the parameters involved in the dehydration process.14 Modeling of volumetric droplet distribution under an electrical field was done by Chiesa,15 whose work showed good agreement between the calculated and measured waterdroplet volumetric distributions in a stagnant emulsion with a water volume fraction of 2%, below the range used in processing equipment. The influence of turbulent flow on electrocoalescence was modeled by Melheima and Chiesa,16 and their work showed that turbulence can control the droplet collision frequency. Empirical and semiempirical models are typically developed to overcome the challenge of creating phenomenological

Water-in-oil emulsions are readily formed in the production of crude oil, causing problems in different steps of oil production and refining. Corrosion of pipelines, pumps, and other pieces of equipment and catalyst deactivation are consequences of the presence of salty water. In addition, the cost of transporting water in pipelines and the extra processing equipment required to remove water from crude oil add to the production costs. Therefore, removing this unwanted emulsified water from crude oil is essential to reduce the costs of production and refining.1,2 Several methods for removing emulsified water from oil are available, such as chemical demulsification, gravity or centrifugal settling, pH adjustment, filtration, heat treatment, membrane separation, and electrostatic demulsification (electrocoalescence). It is also possible to combine electrostatic demulsification with other separation technologies, such as centrifugal, heating, chemical, and filtration techniques.1−7 Emulsified water droplets are distributed in the continuous phase by hydrodynamical or gravitational fields. However, when a high electric field is applied to a water-in-oil emulsion, the droplets move and align themselves parallel to the field, polarizing themselves and leading to a linear flocculation of water droplets that attains a chainlike configuration between the electrodes.7−11 These phenomena lead to water droplet coalescence, followed by sedimentation. A water droplet between two charged electrodes suspended in an insulating medium, such as crude oil, is under the influence of three electromagnetic forces, in addition to gravitational and viscous drag: dipolar attraction, electrophoresis, and dieletrectrophoresis.3,12 For very close drops, the dipolar attraction enhances the droplet coalescence rate, © 2012 American Chemical Society

Received: Revised: Accepted: Published: 13423

November 18, 2011 June 28, 2012 September 18, 2012 September 18, 2012 dx.doi.org/10.1021/ie202489g | Ind. Eng. Chem. Res. 2012, 51, 13423−13437

Industrial & Engineering Chemistry Research

Article

ρa = 0.99965 + 2.0438 × 10−4T − 6.1744 × 10−5T1.5

models that are useful for process design in difficult-to-model systems. Empirical models are based on the operating and design variables used to infer the efficiency of crude-oil dehydration. The main hypotheses used are that the oil and water phases are homogenized with the same efficiency, all salt are dissolved in the aqueous phase,13,14,17 and the selected process variables are meaningful for describing the process. Lucas4 developed a polynomial model to predict crude oil and water contents after dehydration as functions of the treatment temperature and crude-oil-emulsion feed flow rate based on field data. It was concluded that the initial water cut and the droplet size distribution had limited effects on the crude-oil-emulsion dehydration efficiency. Empirical models based on the voltage gradient, electrode spacing, crude-oil volumetric flow rate, transverse sectional area of the separation tank, and oil viscosity and density have been developed.18−21 These models were able to reproduce the electrostatic desalination efficiency using a crude-oil-emulsion dehydration pilot plant processing light oils, with densities of 15.7−28.7°API.18−20 Coutinho20 proposed a modification of the model developed by Oliveira and co-workers5,18 by introducing the value of the API density and estimated the parameters for five different oils. This modification improved the ability of the model to predict the crude-oil-emulsion dehydration efficiency.19,20 Despite the industrial importance of electrocoalescence, the literature lacks detailed studies at industrially relevant temperatures of water in crude-oil-emulsion dehydration processes. Therefore, the objective of this work was to investigate the effects of operating variables and crude-oil physicochemical properties on electrocoalescence efficiency. This work culminated in the development of an empirical model based on pilotplant data and its validation with industrial data.

(3)

where ρc (g/cm ) is the density of crude oil at temperature T (°C), ρ20 (g/cm3) is the density of crude oil at a temperature of 20 °C, and ρa (g/cm3) is the density of the aqueous phase at temperature T (°C). Experimental Data Obtained in the Pilot Plant. Crudeoil emulsions from seven different oils were tested in a pilot plant. The pilot-plant operating variables were the initial water content in the emulsion (H2Oin), the electric field between the electrodes (GT), the treatment temperature (T), and the residence time between the electrodes (TRP). The experiments for these four experimental variables were organized in a fractional factorial plan with three replicas at the central point (Table 1). The values were normalized between −1 and +1 to 3

Table 1. Experimental Plan for Experiments Performed in an Electrostatic Dehydration Treatment Pilot Planta GT

T

TRP

1 2 3 4 5 6 7 8 9 (C) 10 (C) 11 (C)

−1 −1 −1 −1 1 1 1 1 0 0 0

−1 −1 1 1 −1 −1 1 1 0 0 0

−1 1 −1 1 −1 1 −1 1 0 0 0

−1 1 1 −1 1 −1 −1 1 0 0 0

Normalized variables: H2Oin, water content in the synthetic emulsion; GT, voltage gradient between the electrodes; T, operating temperature; TRP, residence time between the electrodes.

EXPERIMENTAL SECTION This study presents experimental data obtained from an electrostatic dehydration pilot plant (PP) and two refineries denoted 1 and 2. The following crude-oil physicochemical characteristics were used as input variables in this study: crude-oil water content; crude-oil API density; weight fractions of saturated compounds, resins, and asphaltenes in the crude oil; total sulfur, nitrogen, nickel, vanadium, and iron contents in the crude oil; crude-oil acidity index; crude oil/water interfacial tension; crude-oil dynamic viscosity (under operating conditions); crude oil conductivity; and the difference between the densities of the aqueous and crude-oil phases under operating conditions. The droplet size distribution was not used as an independent variable, because it was not measured for all experiments. To determine the viscosity of crude oil at different temperatures, we used the equation22

allow for the calculation of the effects of the variables without any influence of their magnitudes and to maintain the orthogonality of the experimental plan.24 The water content in the crude-oil emulsion feed (H2Oin) ranged from 4% to 10%, the electric field between electrodes ranged from 5.49 to 9.14 kV/in (from 2.16 to 3.60 kV/cm), and the residence time between electrodes ranged from 0.7 to 4.4 min. The dehydration temperature ranged from 80 to 120 °C for oils A and B, from 80 to 160 °C for oils C−F, and from 120 to 133 °C for oil G to account for large viscosity differences in the crude-oil samples. Table 2 shows the experimental region used in the experiments performed in the pilot-plant unit using normalized variables for the sake of generality.24 For instance, the value of −1 for the normalized variable water content in the feed emulsion (H2Oin) indicates that the feed emulsion was prepared with the lowest water content value, 4% (w/w); the value of +1 for the normalized variable temperature (T) indicates that the electrostatic treater temperature was set to the highest temperature for a given oil, for example, 120 °C for oil A. An experimental plan such as that shown in Table 2 was set to run for each oil, but because of plant instability, the plan was not fully executed for heavy oils F and G. For oil F, the center points were not executed, and for oil G, only three experimental points were obtained. The response variable was the water content in the treated crude oil measured by Karl Fisher titration.25 The current

(1)

where νp (mm2/s) is the crude-oil kinematic viscosity at temperature T (K). The constants A and B were estimated from kinematic viscosity data measured at at least three different temperatures. The crude-oil and aqueous-phase densities were estimated as functions of temperature using the equations23 ρc = [(ρ20 )2 − 0.0012(T − 20)]0.5

H2Oin

a

■

log log(νp + 0.7) = A + B log(T )

experiment

(2) 13424

dx.doi.org/10.1021/ie202489g | Ind. Eng. Chem. Res. 2012, 51, 13423−13437


Article

Table 2. Experimental Region for the Data Obtained in the Pilot Plant and Refineries 1 and 2 pilot plant

a

symbol

variable

units

maximum

API AROM ASPH Ca Fe GT H2Oin N Ni P Q RES S SAT T TAN TRP Va ΔP γ μp σ ρa ρa − ρc ρc

petroleum API density aromatic content in the oil asphaltene content in the oila calcium content in the oil iron content in the oil voltage gradient between electrodes water content in the feed emulsion total nitrogen content in the oil nickel content in the oil phosphorus content in the oil oil volumetric flow rateb resins content in the oil total sulfur content in the oil saturated content in the oil operating temperature total acidy number in the oil residence time between electrodes vanadium content in the oil head loss at the mixing valve oil/water interfacial tensionc oil dynamic viscosityb oil conductivityd aqueous-phase densityb density difference between the aqueous and oil phasesb oil densityb

°API % w/w % w/w ppm ppm kV/cm % w/w ppm ppm ppm L/h or m3/day % w/w % w/w % w/w °C (mg of KOH)/g S % w/w kgf/cm2 mN/m g/(cm s) nS/m g/cm3 g/cm3 g/cm3

27.8 32.8 7.67 17 13 2.0 10.6 0.50 43 44 7.1 28.3 0.78 54.3 161.1 3.26 299 28 − 21.1 0.409 38 0.973 0.131 0.912

refinery 1

minimum maximum 13.0 24.1 0.59 5 1 1.2 3.7 0.31 4 15 0.9 19.6 0.35 40.2 78.4 0.30 37 6 − 15.9 0.017 0.75), meaning that only one of them can be included in a model to properly describe their effects. The chosen variable for modeling purposes was (ρa − ρc), which can take into account temperature variations. The final water content in the treated crude oil depends on the crude-oil dynamic viscosity, as expected, because an increase in oil viscosity leads to a decrease in droplet terminal 13431



Article

account through only the crude-oil viscosity. Therefore, the effect of crude-oil viscosity takes into account (indirectly) chemical and even electrical effects for this set of crude oils. The effects of water pH and shear rate used to prepare the emulsion feed and the amount of demulsifier were evaluated in additional experiments at the central point for crude oils A−E. Table 7 compares the mean water content in the treated crude oil for central-point replicas with the water content in the

Table 8. Experimental Region of the Data Run in the Pilot Plant Using Oil and Water from Refinery 2 values

Table 7. Effects of Water pH, Demulsifier Content, and Droplet Size on the Final Water Content of the Treated Oil [H2Oout (% w/w)] Effect of Increasing Dilution Water Alkalinity crude oil A D E

neutral pH

pH 8.0

0.602 ± 0.042 0.889 ± 0.084 0.742 ± 0.031 Effect of Demulsifier Addition with demulsifier

E

without demulsifier

0.742 ± 0.031

1.113 ± 0.063

minimum maximum

oil dynamic viscositya oil specific massa aqueous-phase specific massa specific mass diference (aqueous phase − petroleum)a water content in the aqueous phase operating temperature oil volumetric flow ratea residence time between the electrodes voltage gradient between the electrodes

g/(cm s) g/cm3 g/cm3 g/cm3

0.012 0.794 0.911 0.115

0.018 0.811 0.927 0.126

% w/w °C L/h S kV/cm

5.7 138.3 0.9 31 1.2

8.8 155.8 8.4 295 1.4

Obtained at the operating temperature.

Table 9. Correlation Coefficients between the Operating Variables and the Water Content in the Treated Oil (H2Oout) at Refinery 1

C 0.445 ± 0.007 0.569 ± 0.063 Effect of Increasing Shear Rate Used to Prepare the Feed Emulsion 16000 rpm

units

a

0.773 ± 0.063 1.150 ± 0.063 0.919 ± 0.063

11000 rpm

variable

crude oil from experiments with alkaline water (pH 9). The confidence interval for the measured water content for the treated oil from emulsions with alkaline water was based on the experimental error estimated from replicas for only one crude oil. It was observed that the alkaline water led to an increase in the water content in the treated crude oil as described in the literature.29,30 The effect of adding a demulsifier was evaluated by removing the demulsifier from the crude-oil-C emulsion treated under the central-point conditions. Table 7 shows a statistically significant increase in water content in crude oil C for the experiment without demulsifier, confirming the expected demulsifier effect. More interestingly, it was also observed that the removal of the demulsifier led to large current oscillations during emulsion dehydration. The effect of the droplet size distribution was investigated by increasing the shear rate in the preparation of the water emulsion feed for oil E. As the stirring speed was increased from 13000 to 16000 rpm, the mean volumetric droplet diameter D(4,3) decreased from 8 to 4 μm. Table 7 shows that the final water content in the treated oil increased as the droplet diameter in the feed decreased. The observed effects were very modest and could not be observed when the conditions were not very well controlled. The range of experimental variables investigated in the fullscale tests (industrial units) are listed in Table 8. The correlations between the operating variables and the water content in treated crude oil (H2Oout) after vessels A and B are reported in Table 9. The statistical significant variables are in bold. The performance of the dehydration process was not affected by the water content in the emulsion in any of the dehydration stages. The head loss in the mixing valve (ΔP) also did not affect the performance of the electrostatic dehydration process in any of the stages. This behavior showed that the head loss in the mixing valve did not exceed the critical value for which the water content in the treated crude oil increased rapidly.31 The

variable

R2

T GT TRP ΔP H2Oin

0.79 −0.66 −0.07 0.16 −0.08

residence time between the electrodes (TRP) also did not affect the performance of the electrostatic dehydration process in any of the stages. The voltage gradient between the electrodes affected the performance of the dehydration process in the first stage (Table 9 and Figure 7). The water content in the treated crude was found to be inversely proportional to the voltage gradient. The temperature (T) affected the performance of the electrostatic dehydration process in the first stage (see Table 9 and Figure 8). The water content was directly proportional to the electrostatic treater temperature, contrary to expectations, and could be related to the increased crude-oil conductivity and water solubility with treatment temperature. This effect was also observed for the crude oil C tested in the pilot plant. The lack of observed effects at the industrial site could be due to experimental error. To evaluate the experimental error, replicas from 11 sets of conditions for each desalted stage were selected, and the global variance (sp2, pooled variance) and global standard deviation (sp, pooled average) were calculated, as reported in Table 10. Considering the normal distribution probability, the experimental error for only one measure of the response variable (H 2 O out ) was 0.129% (w/w) (95% confidence), which is acceptable. The lack of effects observed in the industrial unit probably arises from the limited range over which one can disturb the plant without compromising the refinery operation and the impressive robustness of the electrostatic coalescence process. To compare the behaviors of the industrial site and pilot plant, crude oil, water, and brine collected from the refinery were tested in the pilot plant. The range of the collected experimental data is reported in Table 8. The experimental conditions in the pilot plant were similar for vessel B (refinery 2), but for vessel E (refinery 2), because of experimental problems, the oil residence time between electrodes tested at the pilot plant was twice that in the industrial unit. 13432



Article

Figure 7. Correlation of the water content in the treated oil with the electric field in desalter A in refinery 1.

Figure 8. Correlation of the water content in the treated oil with the treatment temperature in desalter A in refinery 1.

B of refinery 2 (Figure 9), the dehydration efficiency was slightly higher than the dehydration efficiency in the pilot plant; for the comparison performed with desalter E of refinery 2 (Figure 10), the dehydration efficiency of the industrial unit was higher than or equal to that of the pilot plant. This behavior indicates that the industrial units operate close to the limits of dehydration efficiency and that the electrical and hydrodynamic differences have a minor influence under these conditions. The agreement between the pilot-plant and industrial data further stimulated the development of a simple model able to

Table 10. Variance Analysis of the Replicas Obtained at Refinery 1a vessel

number of replicas

mean H2Oout (% w/w)

variance

A B

2 2

0.472 0.662

0.0011 0.0076

a 2 sp

= 0.0043, sp = 0.066.

The water contents in the crude oil treated in vessels B and E for the operating conditions of the industrial and pilot units are shown in Figures 9 and 10. For the tests performed in desalter 13433



Article

Table 11. Estimated Parameters for Eq 5a confidence A B C D E a

estimate

standard error

−95%

+95%

3.0781 0.1466 0.6517 0.4140 0.8548

1.3015 0.0499 0.0981 0.0433 0.1663

0.4772 0.0469 0.4558 0.3276 1.1871

5.6791 0.2464 0.8477 0.5004 0.5225

Number of experiments = 68, R2 = 0.83.

Figure 9. Water content (% w/w) in the crude oil treated in desalter B of refinery 2 for the conditions tested in the pilot plant (◆) and in the industrial unit (■).

Figure 10. Water content (% w/w) in the crude oil treated in desalter E/refinery 2 for the conditions tested in the pilot plant (▲) and in the industrial unit (■).

Figure 11. Prediction of the water content in the treated crude oil (% w/w) by the power-law model (◆) using the experimental data (■) from the pilot plant.

predict industrial behavior and aid in the design and evaluation of crude-oil desalting/dehydration equipment. Based on an analysis of the process variables, through the evaluation of the pilot-plant (PP) experimental data, it was concluded that the following operating variables should be used as model input: voltage gradient between the electrodes (GT) and residence time between the electrodes (TRP). The crude-oil properties used were the crude-oil dynamic viscosity (μp) and the density difference between the aqueous phase and the crude oil (Δρ) at the dehydration temperature. It was observed that the asphaltene content was highly correlated with the crude-oil viscosity, so this variable not used in the model. Various models, including neural networks and dimensional analysis, were tried; the power-law model (eq 5) gave the best results. It was built to predict the water content in treated crude oil based on the oil viscosity (μp), the density difference between water and oil (Δρ), the oil residence time between electrodes (TRP), and the electric field (GT); A, B, C, D, and E are adjustable parameters. The estimated parameters are reported in Table 11. H 2Oout = A

regarded as a very good result, although this deviation is significantly higher than the experimental error. The relative errors are more significant: The largest relative error is about 80% (maximum absolute percent deviation), and the average relative error is 20% (average absolute percent deviation). A residual analysis was executed by plotting the residuals against all of the operating variables and crude-oil properties. However, no trend was observed between the residuals and any experimental variable. The model was validated using both pilot-plant and industrial data. Figure 13 shows the predicted and experimental data for a set of validation data points from pilot-plant experiments not used in the regression. The prediction can be regarded as very good, with a maximum deviation from the experimental data of about 0.2% (w/w), but the model presented a systematic error probably due to an oil-dependent systematic error. As the model was developed to describe a wide range of oils, it is somewhat expected that, for a single oil, the model produces systematic errors, predicting a higher or lower dehydration efficiency than observed experimentally. Figure 14 shows the model predictions for the experiments run in the full-scale units. The model predictions for vessel A can be considered excellent. The predictions for the data produced in vessel B are also good, considering the differences in flow patterns between the industrial and pilot plants. Therefore, the proposed model is also able to evaluate different configurations (two- and three-electrode grids) in full-scale units.

μp B ΔρC TRP DGT E

(5)

Figure 11 shows the very good agreement of the power-law model to the experimental data. The frequency distribution of the residues between the observed and predicted values is shown in Figure 12; it can be observed that the residues are well distributed among negative and positive values centered at zero average (0.0038%). The average absolute residual is 0.18%. The largest residuals are about 0.8% (w/w), which can be 13434



Article

Figure 12. Residuals of the difference between the predicted and observed final water contents in the treated crude for the pilot-plant data.

Figure 13. Comparison between the predicted (●) and observed (■) water contents in the treated oil (% w/w) using a validation data set obtained in the pilot plant.

■

CONCLUSIONS

This work presented a study of the electrostatic dehydration process performed in pilot-plant and industrial units. Seven different crude oils were tested, and the investigated operating variables were the water content in the feed emulsion, the voltage gradient between electrodes, the dehydration temperature, and the residence time between electrodes. Concerning the operating variables, the electric field consistently reduced the final water content in the treated crude. The emulsion residence time between electrodes also decreased the final water content in all treated oils, except oil D. The emulsion dehydration temperature and water initial cut had both positive and negative influences on the treatment efficiency, depending on crude oil. The most important crude-oil variable in terms of emulsion stability was found to be the total acidity number; the asphaltene content had just a modest influence on the treatment efficiency. These results might be biased by demulsifier use, but they indicate that the role of naphthenic acids in emulsion stabilization cannot be neglected.

Figure 14. Comparison between the predicted (■) and observed water contents in the treated oil (% w/w) using experimental data (●) collected in the refineries. Runs 1−8, refinery 2, desalter A; runs 9−19, refinery 2, desalter E; runs 20−30, refinery 2, desalter B.

13435



Article

(7) Warren, K. W. New tools for heavy oil dehydration. Presented at the 2002 SPE International Thermal Operations and Heavy Oil Symposium and International Horizontal Well Technology Conference, Calgary, Alberta, Canada, Nov 4−7, 2002; SPE 78944. (8) Warren, K. W. The Dual Polarity® treaterprinciples and operation. NATCO GROUP. Presented at Petrobras S.A., Rio de Janeiro, Brasil, 2002, private communication. (9) Less, S.; Hannisdal, A.; Bjørklund, E.; Sjöblom, J. Electrostatic destabilization of water-in-crude oil emulsions: Application to a real case and evaluation of the Aibel. VIEC Technol. Fuel 2008, 8, 2572. (10) Kokal, S. Crude-oil emulsions: A state-of-the-art review. SPE Prod. Facil. 2005, 20, 5. (11) Schramm, L. L. Crude oil emulsions: Basic principles. In Emulsions: Fundamentals and Applications in the Crude Oil Industry; Scharamm, L. L., Ed.; Advances in Chemistry Series; American Chemical Society: Washington, DC, 1992; Vol. 231, Chapter 1, pp 1− 49. (12) Eow, J. S.; Ghadiri, M.; Sharif, A. O.; Williams, T. J. Electrocoalesce-separators for the separation of aqueous drops from a flowing dielectric viscous liquid. Sep. Purif. Technol. 2002, 29, 63−77. (13) Abdul-Wahab, S.; Elkamel, A.; Madhuranthakam, C. R.; AlOtaibi, M. B. Building inferential estimators for modeling product quality in a crude oil desalting and dehydration process. Chem. Eng. Process. 2006, 45, 568. (14) Al-Otaibi, M. B.; Elkamel, A.; Nassehi, V.; Abdul-Wahab, S. A. A Computational Intelligence Based Approach for the Analysis and Optimization of a Crude Oil Desalting and Dehydration Process. Energy Fuels 2005, 19, 2526. (15) Chiesa, M. Electrocoalescence modeling: An engineering approach. Presented at the 15th Australasian Fluid Mechanics Conference, Sydney, Australia, December 13−17, 2004. (16) Melheima, J. A.; Chiesa, M. Simulation of turbulent electrocoalescence. Chem. Eng. Sci. 2006, 61, 4540. (17) Attena, P.; Lundgaardb, L.; Bergb, G. A simplified model of electrocoalescence of two close water droplets in oil. J. Electrost. 2006, 64, 550. (18) Alves, R. P.; Oliveira, R. C. How to establish a mathematical model for the electrostatic desalting process based on pilot plant studies. Presented at the 2006 SPE Annual Technical Conference and Exhibition, San Antonio, TX, Sep 24−27, 2006; SPE 102790. (19) Coutinho, R. C. C.; Pinto, J. C.; Nele, M.; Hannisdal, A.; Sjoblom, J. Evaluation of Water-in-Crude-Oil Emulsion Stability Using Critical Electric Field: Effect of Emulsion Preparation Procedure and Crude Oil Properties. J. Dispersion Sci. Technol. 2011, 7, 923. (20) Coutinho, R. C. C. Estudo da estabilidade de emulsões de água ́ em petróleos. Dissertaçaõ de Mestrado em Engenharia Quimica, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil, 2005. (21) Mahdi, K.; Gheshlaghi, R.; Zahedi, G.; Lohi, A. Characterization and modeling of a crude oil desalting plant by a statistically designed approach. J. Pet. Sci. Eng. 2008, 61, 116. (22) Standard Test Method for Kinematic Viscosity of Transparent and Opaque Liquids (and Calculation of Dynamic Viscosity); ASTM D445; ASTM International: West Conshohocken, PA, 2010. (23) Standard Test Method for Density and Relative Density of Liquids by Digital Density Meter; ASTM D4052; ASTM International: West Conshohocken, PA, 2002. (24) Box, G. E. P.; Hunter, W. G. ; Hunter, J. S.; Hunter, W. G. Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building, John Wiley & Sons: New York, 1978. (25) Standard Test Method for Determination of Water in Petroleum Products, Lubricating Oils, and Additives by Coulometric Karl Fisher Titration; ASTM D6304a; ASTM International: West Conshohocken, PA, 2007. (26) Eow, J. S.; Ghadiri, M.; Sharif, A. Deformation and break-up of aqueous drops in dielectric liquids in high electric fields. J. Electrost. 2001, 51−52, 463. (27) Manning, F. S., Thompson, R. E. Oil Field Processing of Petroleum: Crude Oil; PennWell Publishing Company: Tulsa, OK, 1995.

The demulsifier presence improved the pilot-plant stability significantly but did not significantly reduce the final water content in the treated oil. Similarly, the use of alkaline water in the emulsion preparation had a small negative influence on the final water content of the treated oil. Correlation analysis of the oil-dependent variables showed that the most important variables for treatment efficiency were the total acidity number (TAN) and resin content (RES); however, these variables were correlated with density difference between crude oil and water at the treatment temperature (ρa − ρc), so that a model could be written using only the physical characteristics of the oil. As a result, an empirical power-lawtype model was built to relate the treatment conditions and the physical characteristics of the oil to the final water content in the treated oil. This model was able to describe the crude-oil emulsion dehydration data from pilot and industrial plants very well. It is somewhat surprisingly that a simple power-law model is able to predict such complex phenomena in pilot and industrial units, especially because of the significant flow and electric-field differences in the two situations. The most important conclusion is that the crude-oil properties that dominate electrostatic dehydration performance and therefore electrocoalescer design are the crude-oil viscosity and density, unless a problematic crude sample that forms a highly stable emulsion is to be treated. This corroborates the results of Coutinho et al.,19 who observed, on the bench scale, that the critical electrical field to start the coalescence of water droplets in crude-oil emulsions is dominated by the crude-oil viscosity.

■

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS

■

REFERENCES

The authors thank Petrobras SA, FAPERJ (Fundaçaõ Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro) and CNPq (Conselho Nacional de Pesquisa e Desenvolvimento) for supporting this project and CNPq for providing scholarships.

(1) Eow, J. S.; Ghadiri, M. Electrostatic enhancement of coalescence of water droplets in crude oil: A review of the technology. Chem. Eng. J. 2002, 85, 357. (2) Eow, J. S.; Ghadiri, M.; Sharif, A. O.; Williams, T. J. Electrostatic enhancement of coalescence of water droplets in oil: A review of the current understanding. Chem. Eng. J. 2001, 84, 173. (3) Noïk, C.; Chen, J.; Dalmazzone, C. Electrostatic demulsification on crude oil: A state-of-the-art review. Presented at the 2006 SPE International Oil & Gas Conference and Exhibition in China, Beijing, China, Dec 5−7, 2006; SPE 103808. (4) Lucas, R. N. Performance of heavy oil dehydrators. J. Crude Oil Technol. 1969, 21, 1285. (5) Oliveira, R. C. G.; Figueiredo, A. M. P. Estado da arte sobre o processo de tratamento eletrostático de emulsões de petróleos e derivados; Comunicaçaõ Técnica; CENPES/Petrobras S.A.: Rio de Janeiro, Brazil, 1989. (6) William, T. J.; Bailey, A. G. Changes in the size distribution of a water-in-oil emulsion due to electric field induced coalescence. IEEE Trans. Ind. Appl. 1986, 1A-22 (3), 536. 13436



Article

(28) Arla, D.; Sinquin, A.; Palermo, T.; Hurtevent, C.; Graciaa, A.; Dicharry, C. Influence of pH and water content on the type and stability of acidic crude oil emulsions. Energy Fuels 2007, 21, 1337. (29) Jones, T. J.; Neustadter, E. L; Whittinghan, K. P. Water-in-crude oil emulsion stability and emulsion destabilization by chemical demulsifiers. J. Can. Pet. Technol. 1978, 17, 100. (30) Kimbler, O. K.; Reed, R. L.; Silberberg, I. H. Physical characteristics of natural films formed at the crude oil-water interfaces. J. Pet. Technol. 1966, 6, 153. (31) Hemrajani, R. R. Fluid mixing technology in the petroleum industry. In Handbook of Industry Mixing: Science and Practice; John Wiley & Sons: New York, 2004; Chapter 19, pp 1171−1186.

13437


Quantitative Evaluation of the Efficiency of Water-in-Crude-Oil

Recommend Documents