Inorganic Solid Content Governs Water-in-Crude Oil Emulsion Stability

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Energy & Fuels 2009, 23, 1258–1268

Inorganic Solid Content Governs Water-in-Crude Oil Emulsion Stability Predictions† Michael K. Poindexter* and Samuel C. Marsh Energy SerVices DiVision, Nalco Company, 7705 Highway 90-A, Sugar Land, Texas 77478 ReceiVed August 11, 2008. ReVised Manuscript ReceiVed December 15, 2008

Solving oilfield emulsion problems is often addressed with the field bottle test. This widely used and informative method uses fresh samples and readily generates a number of emulsion stability parameters that aptly describe the diverse aspects of oil-water separation, namely, water drop, oil dryness, and interface quality. Bottle test data by itself is not predictive because all of the parameters are dependent. Demulsification depends upon the conditions used to resolve the emulsion and the crude oil components that inherently stabilize emulsions. By coupling field bottle test data with subsequent characterization of the same samples used in the field, it is possible to gain insight into the factors that describe and possibly determine emulsion stability. Past work using 12 different crude oils showed that inorganic solid content was the most informative parameter in describing many aspects of emulsion stability. Higher solid levels resulted in more stable emulsions. Further field studies and laboratory analyses have doubled the sample size of the original data set and nearly doubled the number of potential descriptive variables. The characterization data is multivariate (i.e., described by many variables) to account for the chemical diversity of crude oil emulsions. In this study, a broad spectrum of oils with American Petroleum Institute (API) gravities ranging from 10-31° and their associated water were characterized using 18 different parameters. Statistical analyses of the expanded data set yield results that agree with the conclusions set forth in the original study. Inorganic solid content remains the most descriptive variable in predicting emulsion stability.

Introduction During the production of crude oil, water will eventually comprise part of the production fluids. In the life of many oilfields, mixtures of oil and water can form stable emulsions and become an operational issue unless treated with appropriate measures. To anticipate and prevent production problems associated with stable water-in-oil emulsions, various process equipment and operational procedures are used. Some combination of large-diameter vessels to increase interface area and separate the production phases (e.g., oil, water, gas, and solids),1,2 heaters to reduce viscosity,3-5 electrical grids to disrupt interfacial films and aid water droplet coalescence,6,7 centrifuga† Presented at the 9th International Conference on Petroleum Phase Behavior and Fouling. * To whom correspondence should be addressed: Energy Services Division, Nalco Company, 7705 Highway 90-A, Sugar Land, Texas 77478. Telephone: 281-263-7505. Fax: 281-263-7221. E-mail: mkpoindexter@ nalco.com. (1) Manning, F. S.; Thompson, R. E. Phase separation of gas, oil, and water. In Oilfield Processing: Crude Oil; PennWell: Tulsa, OK, 1995; Vol. 2, Chapter 6, pp 79-112. (2) Simmons, M. J. H.; Komonibo, E.; Azzopardi, B. J.; Dick, D. R. Residence time distributions and flow behaviour within primary crude oilwater separators treating well-head fluids. Chem. Eng. Res. Des. 2004, 82, 1383–1390. (3) Manning, F. S.; Thompson, R. E. Dehydration of crude oil. In Oilfield Processing: Crude Oil; PennWell: Tulsa, OK, 1995; Vol. 2, Chapter 7, pp 113-143. (4) Benayoune, M.; Khezzar, L.; Al-Rumhy, M. Viscosity of water in oil emulsions. Pet. Sci. Technol. 1998, 16, 767–784. (5) Alboudwarej, H.; Muhammad, M.; Shahraki, A.; Dubey, S.; Vreenegoor, L.; Saleh, J. Rheology of heavy oil emulsions. SPE Prod. Oper. 2007, 22, 285–293. (6) 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, 173–192.

tiontospeedseparation,8,9 filtration,1,9 andchemicaldemulsifiers10-12 are employed. Resolving water-in-crude oil emulsions is generally accomplished in the field before transporting the oil to refineries. Residual water specifications for oil leaving production facilities are typically capped at 0.1-0.5% and sometimes as high as 3%.9 Unresolved water carries species (chlorides and inorganic solids) that contribute to corrosion and fouling issues during transportation and in refining operations.13 A number of different crude oil components and processing conditions are known to stabilize crude oil emulsions. Some of the more studied and acknowledged factors known to contribute to emulsion stability include high viscosity, which is linked partly to crude oil composition, water droplet size, and water (7) Chen, T. Y.; Mohammed, R. A.; Bailey, A., I.; Luckham, P. F.; Taylor, S. E. Dewatering of crude oil emulsions 4. Emulsion resolution by the application of an electric field. Colloids Surf., A 1994, 83, 273–284. (8) Leopold, G. Breaking produced-fluid and process-stream emulsions. In EmulsionssFundamentals and Applications in the Petroleum Industry; Schramm, L. L., Ed.; American Chemical Society: Washington, D.C., 1992; Chapter 10, pp 341-383. (9) Lissant, K. J. Demulsification of petroleum emulsions. In Demulsification Industrial Applications; Marcel Dekker: New York, 1983; Chapter 5, pp 105-134. (10) Staiss, F.; Bo¨hm, R.; Kupfer, R. Improved demulsifier chemistry: A novel approach in the dehydration of crude oil. SPE Prod. Eng. 1991, 6, 334–338. (11) Jones, T. J.; Neustadter, E. L.; Whittingham, K. P. Water-in crude oil emulsion stability and emulsion destabilization by chemical demulsifiers. J. Can. Pet. Technol. 1978, 17, 100–108. (12) Mikula, R. J.; Munoz, V. A. Characterization of demulsifiers. In Surfactants: Fundamentals and Applications in the Petroleum Industry; Schramm, L. L., Ed.; Cambridge University Press: Cambridge, U.K., 2000; Chapter 2, pp 51-77. (13) Batra, B.; Borchert, C. A.; Lewis, K. R.; Smith, A. R. Design process equipment for corrosion control. Chem. Eng. Prog. 1993, 68–76.

10.1021/ef800652n CCC: $40.75  2009 American Chemical Society Published on Web 02/04/2009

Water-in-Crude Oil Emulsion Stability Predictions

content,4,5,14-16 naturally occurring surface-active components (e.g., asphaltenes,17 resins,18,19 and naphthenic acids20), solids (both organic and inorganic),19,21-26 and aging.12 Unraveling the inherent complexity of crude oils and how the different components influence emulsion stability is challenging. To date, there is no industry-wide accepted and used method to fully describe the chemistry and properties of crude oil. Viscosity and American Petroleum Institute (API) gravity (i.e., specific gravity) probably come the closest to serving as industrial standards;27 however, they, similar to most any small group of descriptors, are insufficient to fully explain crude oil behavior. Assuming that such an agreed upon method or series of methods existed to describe crude oil, they would permit, for the first time, widespread comparisons of data generated from different laboratories to finally occur; however, the methods would not remove the innate complexity of crude oil. Besides viscosity and API gravity, crude oil complexity is often addressed by separation into groups of varying polarity and/or molecular-weight distributions (e.g., distillation).28 By essentially dissecting crude oils, a better understanding of how the oils are weighted toward one or more fractions is obtained. One of the most prevalent characterization practices involves the fractionation of crude oil into saturate, aromatic, resin, and asphaltene (SARA) components. Numerous experimental SARA methods exist,29,30 and advances and variations in the technique continue to provide new ways to examine and define crude oil behavior.31,32 Results from various characterization procedures, including but not limited to SARA fractionation, can serve as (14) Hemmingsen, P. V.; Silset, A.; Hannisdal, A.; Sjo¨blom, J. Emulsions of heavy crude oils. I: Influence of viscosity, temperature, and dilution. J. Dispersion Sci. Technol. 2005, 26, 615–627. (15) Schramm. L. L. Petroleum emulsions: Basic principles. In EmulsionssFundamentals and Applications in the Petroleum Industry; Schramm, L. L., Ed.; American Chemical Society: Washington, D.C., 1992; Chapter 1, pp 1-49. (16) Kokal, S. Crude oil emulsions: A state-of-the-art review. SPE Prod. Fac. 2005, 20, 5–13. (17) Kilpatrick, P. K.; Spiecker, P. M. Asphaltene emulsions. In Encyclopedic Handbook of Emulsion Technology; Sjo¨blom, J., Ed.; Marcel Dekker: New York, 2001; Chapter 30, pp 707-730. (18) Schorling, P.-C.; Kessel, D. G.; Rahimian, I. Influence of the crude oil resin/asphaltene ratio on the stability of oil/water emulsions. Colloids Surf., A 1999, 152, 95–102. (19) Gafonova, O. V.; Yarranton, H. W. The stabilization of water-inhydrocarbon emulsions by asphaltenes and resins. J. Colloid Interface Sci. 2001, 241, 469–478. (20) 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, 1337–1342. (21) Thompson, D. G.; Taylor, A. S.; Graham, D. E. Demulsification and demulsification related to crude oil production. Colloids Surf. 1985, 15, 175–189. (22) Zaki, N.; Schorling, P.-C.; Rahimian, I. Effect of asphaltene and resins on the stability of water-in-waxy oil emulsions. Pet. Sci. Technol. 2000, 18, 945–963. (23) Menon, V. B.; Wasan, D. T. Characterization of oil-water interfaces containing finely divided solids with applications to the coalescence of water-in-oil emulsions: A review. Colloids Surf. 1988, 29, 7–27. (24) Sztukowski, D. M.; Yarranton, H. W. Oilfield solids and waterin-oil emulsion stability. J. Colloid Interface Sci. 2005, 285, 821–833. (25) Sullivan, A. P.; Kilpatrick, P. K. The effects of inorganic solid particles on water and crude oil emulsion stability. Ind. Eng. Chem. Res. 2002, 41, 3389–3404. (26) Yan, N.; Gray, M. R.; Masliyah, J. H. On water-in-oil emulsions stabilized by fine solids. Colloids Surf., A 2001, 193, 97–107. (27) Speight, J. G. The Chemistry and Technology of Petroleum, 3rd ed.; Marcel Dekker: New York, 1998; pp 305-319. (28) Altgelt, K. H.; Boduszynski, M. M. Composition and Analysis of HeaVy Petroleum Fractions; Marcel Dekker: New York, 1994; Chapter 3, pp 41-73. (29) Speight, J. G. The Chemistry and Technology of Petroleum, 3rd ed.; Marcel Dekker: New York, 1998; pp 269-283. (30) Andersen, S. I.; Speight, J. G. Petroleum resins: Separation, character, and role in petroleum. Pet. Sci. Technol. 2001, 19, 1–34.

Energy & Fuels, Vol. 23, 2009 1259 Scheme 1

the independent variables that might describe the measures of emulsion stability (i.e., the dependent variables). The methodology of this study started with gathering the dependent variables. Numerous field bottle test studies, where crude oil emulsions were taken at or near the wellhead and before any chemical treatment, were conducted. Each field test was performed using an established method and involved the same group of chemical demulsifiers at the same concentration.33 Thus, fluids from numerous fields were subjected to chemicals that are known to destabilize oilfield emulsions. In this approach, the exact chemicals used are almost immaterial compared to treating each emulsion under investigation with the same group and same concentration of chemicals. In effect, the chemicals serve as probes of emulsion stability because they each have a propensity of resolving some aspect of the factors used to gauge emulsion stability. To couple the field bottle test studies with the crude oil predictors (i.e., the independent variables), top oil from each bottle of a given study was collected, combined, and laboratory-characterized to determine the various crude oil components that were at play (see the Field Approach in Scheme 1). This field approach differs from the more common and traditional laboratory approaches, where dry and often treated crude oils are sent to the laboratory for characterization followed by studies designed to focus on a particular emulsion stability issue (see the Lab Approach in Scheme 1). The role of asphaltenes or asphaltenes combined with resins is a frequent approach, where the crude oil fraction or fractions are added to mixtures of aliphatic and aromatic solvents and emulsified with water. The emulsion is then monitored to determine the role that selected independent variables (i.e., the crude oil components) have on emulsion stability, which is generally gauged by the amount of water separated (i.e., water drop) in a given amount of time. Another recently introduced laboratory method for specifically isolating interfacial materials from Athabasca bitumen froth emulsion involves dilution with dibromomethane and heavy water (D2O).34 There are advantages and disadvantages to both field and laboratory approaches. The field approach allows all of the crude oil components to simultaneously interact with each other and leaves the crude oil in a state similar to that found in field processing. However, the field approach does not permit crude oil components to be varied in a systematic manner. The experimenter must accept what the field produces. Thus, a somewhat large data set is ultimately needed to elucidate the most predictive factors and their interactions if this multivariate (31) Kharrat, A. M. A new approach for characterizing heavy oils. Energy Fuels 2008, 22, 1402–1403. (32) Graham, B. F.; May, E. F.; Trengove, R. D. Emulsion inhibiting components in crude oils. Energy Fuels 2008, 22, 1093–1099. (33) Poindexter, M. K.; Chuai, S.; Marble, R. A.; Marsh, S. C. Solid content dominates emulsion stability predictions. Energy Fuels 2005, 19, 1346–1352. (34) Wu, X. A. Selective creaming: A novel technique to isolate interfacial organics and mineral solids from water-in-oil emulsions. Energy Fuels 2008, 22, 2346–2352.

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approach is to yield meaningful results. For the laboratory approach, experimental designs are readily possible to conduct. Emulsion stability trends are clear because the number of potential variables influencing emulsion stability has been greatly reduced. Conversely, fractionation or dilution of crude oil before experimentation and making subsequent comparisons can denature the isolated components and possibly alter or eliminate the rich interplay of the components at work in crude oil. While a number of crude oil components and properties have been identified as generating stable emulsions, the first intent of this study is to describe or rank emulsion strength and not just emulsion existence. The most common way to gauge emulsion stability is by recording water drop. As mentioned, this is particularly true for model studies and is sometimes the only parameter used. In field bottle testing, water drop and several other parameters (e.g., oil dryness and interface quality) are routinely recorded. The latter two parameters, oil dryness and interface quality, are not commonly reported in model studies. It is important to introduce both terms and their value in describing oil-water separation. Although crude oil producers generally record water separation rates in real time, crude oil transportation is ultimately dictated by oil dryness. This value is generally recorded as BS&W (where BS stands for bottom settlings or basic sediment35 and W stands for water). The BS parameter is particularly important and will be used throughout this report because it describes the residual untreated emulsion that exists in a sample. Another number of importance is the slug grindout number (see the Experimental Section for its determination). The slug grindout number captures the total water in the sample after the residual emulsion has been broken. It is not simply the sum of the BS and W values because very fine emulsion, often called secondary emulsion, can remain hidden from the BS&W evaluation. Furthermore, the percent oil and water in the BS layer is not readily defined until the slug grindout number is measured. In bottle testing, oil dryness measurements are typically determined for each bottle by removing via a syringe a small amount of oil. This is commonly called “thiefing” the oil.35 Using a procedure that involves dilution, centrifugation, and resolution of any residual emulsion, the basic sediment (BS) and total water content (slug value) are determined for the thiefed samples. Lower values indicate less residual emulsion and drier oil, respectively. Interface quality is equally important in describing another aspect of the overall oil-water separation process. The border defined by oil and water is extremely rich in complexity. Concentrations of certain surface-active species and metals are higher in this region as opposed to the bulk fluids.36 Field conditions that perform well in both water drop and oil dryness can still leave an unresolved and detrimental interface. Gradual accumulation and build-up of an unresolved interface will lead to off-specification oil. Similar to the oil dryness procedure, the interface quality is examined as well. To accomplish this, the resolved water in each bottle is removed via a syringe and the remaining contents are well-mixed. The BS and slug values of the wet oil sample (35) Hyne, N. J. Dictionary of Petroleum Exploration, Drilling, and Production; PennWell: Tulsa, OK, 1991. (36) McLean, J. D.; Kilpatrick, P. K. Effects of asphaltene aggregation in model heptane-toluene mixtures on stability of water-in-oil emulsions. J. Colloid Interface Sci. 1997, 196, 23–34, (see Table 2 for comparisons).

Poindexter and Marsh

are determined and compared to the oil dryness results. If the oil dryness and interface quality results are similar, then the water content throughout the oil phase is fairly uniform; however, if the interface quality values are substantially larger, then a water-in-oil gradient exists. All three basic parameters (water drop, oil dryness, and interface quality) are needed for solving field emulsions. Collectively, they round out much of the picture regarding oil-water separation. Just as no single crude oil property can adequately describe crude oil behavior, no single gauge of oil-water separation can fully describe emulsion stability. Oil-water separation is generally considered to be a stepwise process as opposed to a concerted process. The very nature and design of field treatment procedures and systems seems to have taken advantage of this stepwise process. A second intent of this study is to find interaction terms among the independent variables that seem to exacerbate emulsion stability. As is often the case, it is not just one factor but a collection of factors that describe complex processes. To address these interactions, a multivariate statistical technique known as partition or decision trees was used. The statistical method allowed each of the bottle test parameters to be crossexamined against all of the possible evidence at hand, namely, the crude oil characterization and physical property data. In agreement with a prior study using the same approach, inorganic solid content was found to be the most descriptive property to gauge overall emulsion stability.33 Solid content was the only variable that appeared in every measure of emulsion stability. Experimental Section Bottle Test Terminology. Some of the terms used in the Experimental Section as well as the Results and Discussion are jargon, having oilfield origin, and may not have gained widespread acceptance throughout the scientific community. Where appropriate, a brief description of each term will be provided when introduced. More in-depth explanations can be found in helpful reference guides for bottle testing and oilfield operations.3,8,9,37 Chemicals and Supplies. A total of 36 different demulsifiers served as the chemical probes. All are manufactured by Nalco Company. Demulsifier stock solutions consisted of 5 wt % active component in heavy aromatic naphtha, and all tests were conducted at 50 ppm (by vol). To determine the water content in crude oil and the various sampling steps of bottle testing, aliquots were diluted with Stoddard solvent or Varsol (Registry 8052-41-3), which is sometimes referred to as mineral spirits. Stoddard solvent is a nonvolatile, odorless diluent that reduces the viscosity of the emulsion and facilitates the quantification of unresolved emulsion and water. Prescription bottles (6 oz) were ordered from Berlin Packaging, Houston, TX. Field Emulsions. Water-in-oil emulsions collected in the field were free of demulsifier. Shortly after collection, samples were drained of any free water. Free water is defined as water that separates rapidly and is not truly emulsified. A total of 12 of the 24 emulsions in this report date back to a prior study.33 In some of the more recently studied emulsions, crude oil sampling for analytical characterizations was conducted in the field as opposed to the laboratory. Bottle testing for three of the oils was repeated, where the repeats were conducted a week after the first test. A summary of all of the emulsion properties along with their abbreviations is provided in Table 1. The duplicates are further designated with a suffix (a and b). To match production process fluids, two of the Canadian emulsions (AB-2 and AB-3) and both Venezuelan emulsions (EV and WV) were diluted with their respective field condensates before field bottle testing. (37) Petroleum Extension Service. Treating Oilfield Emulsions, 4th ed.; Petroleum Extension Service at The University of Texas at Austin: Austin, TX, 1990; Chapter 6, pp 35-51.

a

AB-1 AB-2 AB-3 MS-1 MS-2 MT-1 MT-2 EV GM-1 GM-2 WC-1 WC-2a WC-2b WC-3 WC-4a WC-4b WC-5 WC-6 WC-7 WC-8 WC-9a WC-9b WV WY

10.0 13.5 12.3 10.5 11.1 30.6 27.8 13.6 28.7 18.3 19.7 24.2 24.4 19.4 23.6 23.3 22.8 19.5 21.5 22.8 21.0 20.9 11.2 19.5

53300 6200 7200 166500 65400 17 76 8100 17 220 258 40 48 165 48 49 60 112 79 60 84 88 59000 165

18.8 18.6 15.9 10.7 14.6 38.6 34.5 13.8 65.2 20.8 14.8 21.8 28.6 17.4 27.6 22.6 27.8 14.5 25.8 25.0 18.4 21.2 12.1 24.2

51.9 48.9 54.7 57.4 53.1 28.6 30.8 49.0 26.7 54.0 43.9 65.6 59.7 66.4 48.7 56.9 51.3 63.2 52.2 54.6 61.4 59.2 49.4 49.3

14.6 13.7 13.6 24.1 25.0 4.3 4.2 14.1 2.6 11.7 16.7 5.8 6.6 8.9 7.3 7.1 7.7 9.0 6.4 7.2 7.8 7.8 17.1 9.9

14.3 13.1 12.3 7.9 8.3 8.1 11.6 14.5 0 3.4 11.4 1.2 1.4 2.5 3.1 3.3 2.7 2.9 5.7 2.6 4.4 4.9 16.8 7.6

0.9 1.0 1.8 3.3 5.3 1.1 0.3 4.0 1.1 1.5 1.1 0.4 0.1 0.5 0.3 0.4 0.2 0.6 0.1 0.6 0.3 0.2 1.6 0.3

0.4 1.0 0.6 1.8 2.6 0.2 0.1 1.7 0.3 1.2 0.5 1.0 0 0.6 0.2 0.4 0.15 0.3 0 0 0 0 0.5 0.2

401 661 985 156 634 664 1090 96 176 205 257 156 112 83 486 494 254 189 168 67 170 179 297 157

6.8 3.6 14 32 19 5.0 13 6.8 13 50 120 2.5 1.9 8.5 3.3 4.5 2.8 10 2.1 5.2 4.1 3.9 11.5 2.7

64 66 62 67 53 2.9 4.6 76 0.9 17 69 6.9 3.6 13 9.4 11 8.5 14 16 10 15 15 95 34

160 150 150 75 62 2.7 1.0 335 0.7 51 175 13 5.8 24 26 26 16 29 39 18 34 35 1067 130 3.49 1.46 4.88 4.80 3.60 2.35 2.13 2.80 3.06 1.12 2.78 1.77 1.62 1.02 1.31

1.02 1.05 1.11 3.07 3.01 0.53 0.36 0.97

1.54 1.52 1.52 1.51 1.56 1.46 1.46 1.55 1.54 1.52 1.71 1.67 1.60 1.55 1.58 1.60 1.54 1.60 1.60 1.58 1.57 1.60 1.56 1.54

28 50 50 60 54 46 55 15 33 21 44 74 76 50 54 56 56 30 46 53 40 40 30 58

e

e

8.2 8.0 8.2 8.3 7.9 8.6 8.7 8.0 7.7

e

1.0145 1.0149 1.0081 1.0086 1.0149 1.0081 1.0079 0.9995 1.0017

0.1082 0.1051 0.0786 0.0915 0.1055 0.0877 0.0869 0.0195 0.0719

0.0294 0.0308 0.0216 0.0064 0.0126 0.1645 0.1391 0.0377 0.1809 0.1680 0.0904 0.1133 0.1146 0.0912

8.2 8.9 7.5 7.4 7.7 7.6 7.6 7.9 6.8 6.7 5.5 7.6 7.6 9.0

1.0019 0.9994 0.9978 0.9994 0.9987 1.0295 1.0203 1.0047 1.0568 1.1022 1.0170 1.0148 1.0148 1.0213

Reported as mg of KOH/g of crude. b Reported as pounds/1000 barrels of crude (PTB). c Atomic ratio for aromatic fraction. d Water density - oil density. e The water sample was not collected.

Alberta Alberta Alberta California Midway-Sunset California Midway-Sunset Eastern Montana Eastern Montana Eastern Venezuela Gulf of Mexico (shelf) Gulf of Mexico (deepwater) West Coast West Coast West Coast West Coast West Coast West Coast West Coast West Coast West Coast West Coast West Coast West Coast Western Venezuela Western Wyoming

crude oil

Table 1. Summary of Crude Oil and Water Properties

API viscosity % % % % acid naphthenic Fe Ni V aromatic water water density designation gravity (cP) saturates aromatics resins asphaltenes numbera acidsa solidsb (ppm) (ppm) (ppm) R/A H/Cc content (%) density pH differenced

Water-in-Crude Oil Emulsion Stability Predictions Energy & Fuels, Vol. 23, 2009 1261

1262 Energy & Fuels, Vol. 23, 2009 Slug Grindout Number (Water Content). Before bottle testing and after removal of free water, all field emulsions were shaken and subjected to a “grindout”, a procedure that measures the water content in the emulsion. Using a graduated API centrifuge tube (12.5 mL), one part by volume Varsol as a diluent was added followed by one part emulsion. The diluted emulsion was handshaken to ensure thorough mixing and then centrifuged (5 min at ca. 680 rpm). The percent water (abbreviated W) and remaining emulsion (abbreviated BS for bottom settlings or basic sediment) were both recorded. It is customary to double all centrifuge tube readings to account for the diluent. The term BS is used to quantify the remaining emulsion (“rag”) layer residing at the oil-water interface. After recording the BS and W values, a chemical known to resolve the remaining emulsion was added to the centrifuge tube. Such chemicals are called “slugging or knockout chemicals” and are typically low-molecular-weight sulfonate-based materials. Typically, a few drops are needed to completely resolve the emulsion. After slugging, the tube was again shaken and centrifuged as previously described. If enough slugging chemical was added, the BS will be completely eliminated and only water remains in the bottom part of the tube. The amount of slug needed is determined in the initial grindout work. The final reading, called the slug grindout number, is reported as a percentage. This measurement is critical to determine before conducting any bottle testing. The value represents the amount of water in each bottle in the study assuming that the field sample is well-mixed before distributing emulsion to the bottles. Samples taken to determine water-in-oil levels in later steps of the bottle test employ an identical procedure to that just described. Water Drop Measurements. All tests were conducted in graduated 6 oz prescription bottles to allow for rapid water drop readings. All bottles used 100 mL of emulsion. After pouring the emulsion followed by chemical addition, the bottles were allowed to reach the separator temperature via a water bath. Upon reaching the desired temperature, the samples were shaken via a mechanical shaker and then returned to the water bath. Water drop readings were recorded in milliliters and generally involved longer time frames for heavier crude oils and shorter times for lighter oils. Final water drop values, reported as a percentage of the total water content (as determined by the slug grindout number), will act as one of five bottle test parameters to gauge emulsion stability. Oil Dryness (Thief, t) Measurements. After the water drop readings, the resolved or partially resolved oil from each bottle was analyzed for water content. Using a syringe with a wide bore needle, a small portion of the oil (commonly called a “thief”, ca. 6 mL) was withdrawn. The tip of the syringe was set to 15-20 mL above the theoretical oil-water interface as determined by the slug grindout value. The aliquot of oil was added to a graduated API centrifuge tube containing an equal volume of Varsol, and then the contents were shaken thoroughly by hand. After centrifugation, the percent residual emulsion, abbreviated BS(t), was noted for each bottle in the study. Slugging chemical, as determined in the slug grindout number, was added to each tube to resolve any remaining emulsion, and once again, the contents were hand-shaken and centrifuged as described in the prior step. The water amount was recorded as the thief slug value, abbreviated Slug(t). Both measurements, BS(t) and Slug(t), express the volume percentage of residual emulsion and total water contained in the siphoned oil sample, respectively. These two measurements describe different aspects of oil dehydration. Smaller values indicate drier oil. Interface Quality (Composite, c) Measurements. The last two bottle test measurements describe the dryness of the oil-water interface and are often referred to as composites. From each bottle, the resolved water layer was carefully removed by a syringe. The remaining contents were shaken by hand. As in the thief procedure, a portion of the shaken composite was added to a centrifuge tube containing Varsol (equal parts of each), shaken, and centrifuged. Basic sediment and slug measurements for the composites were conducted in the same manner described in the oil dryness thief section and labeled as BS(c) and Slug(c), respectively. Composite

Poindexter and Marsh values complement thief measurements. For instance, the closer composite and thief values are to one another, the more uniformly distributed is the water content throughout the oil phase. Conversely, if the thief values are noticeably smaller than their composite counterparts, then a gradient exists and the water content increases as the interface is approached. Crude Oil Fractionation and Characterization. To collect crude oil for the various fractionation and bulk oil analyses, the top layer of resolved crude oil (i.e., ca. 15% of the total oil phase) from each bottle was removed via a syringe and combined. Fractionation of the crude oils into their SARA components was followed using a known procedure.38 Crude oil viscosities were measured at 25 °C using a Brookfield viscometer model LVT. API gravities (15.56 °C) and oil and water densities (g/mL, 25.0 °C) were determined using a Paar density meter DMA 48. Total acid numbers (TANs) were determined according to ASTM D-66439 and are reported in milligrams of KOH/gram of crude. Naphthenic acid numbers were accomplished by solid-phase extraction of the maltenes (i.e., crude oil minus the n-heptane-insoluble asphaltenes) to isolate the naphthenic acids. The naphthenic acids were then titrated in an isopropyl alcohol/toluene solution using potassium hydroxide. Similar to TANs, naphthenic acid numbers are reported in milligrams of KOH/gram of crude. Inorganic solid content was conducted according to ASTM D-480740 and is reported in pounds per thousand barrels (PTB). The procedure involves a hot toluene wash (90 °C) through a 0.45 µm pore size nylon membrane filter paper that removes most organic material. Metal contents (iron, nickel, and vanadium) were determined using a Jarrell-Ash 61E inductively coupled argon plasma emission spectrometer. Oilfield water pH measurements were performed with a Metrohm 809 Titrando from Brinkmann. Elemental analyses were performed by Galbraith Laboratories, Knoxville, TN. Statistical Analysis. All statistical analyses were conducted using JMP Statistical Discovery Software version 6.0.0 from the SAS Institute, Inc., Cary, NC. Linear regression analyses were conducted to measure the relationship of each crude oil and water characteristic with each mean- and median-based bottle test emulsion stability parameter. Multivariate models were generated using the partition tree technique, where the minimum split size was set to 1. Partition tree splits were not specified a priori, but rather, the algorithm of the software was allowed to determine the best split to explain the variance in the dependent variable.

Results and Discussion Dependent Variables Defined by Field Bottle Testing. Bottle test design is critical to ensure field studies mimic process behavior and cover the basic aspects of oil dehydration. Demulsification is complex and not readily defined by a single measurement of oil-water separation. For this reason, the bottle test can be a somewhat lengthy process as depicted in the Experimental Section. Bottle testing allows several aspects of the oil-water separation process to be quantified, namely, by water drop, oil dryness, and interface quality. Quality of the separated water phase is another parameter commonly recorded in the bottle test but will not be considered in this work because it is frequently described with qualitative terms (e.g., clear, slightly hazy, dirty, etc.) and thus more difficult to quantify and compare. In the bottle test, water drop serves to describe the efficiency of oil-water separation through the entire process. This can (38) Poindexter, M. K.; Zaki, N. N.; Kilpatrick, P. K.; Marsh, S. C.; Emmons, D. H. Factors contributing to petroleum foaming. 1. Crude oil systems. Energy Fuels 2002, 16, 700–710. (39) American Society for Testing and Materials (ASTM). ASTM D664: Standard test method for acid number of petroleum products by potentiometric titration. (40) American Society for Testing and Materials (ASTM). ASTM D-4807: Standard test method for sediment in crude oil by membrane filtration.


Energy & Fuels, Vol. 23, 2009 1263

Table 2. Types of Chemical Demulsifier number of demulsifiers

chemical family

8 5 8 5 4 6

resins with nonyl phenol resins with butyl phenol propylene-ethylene glycol backbone triol backbone hexol backbone cross-linked resins

occur over a relatively short time frame (e.g., for offshore platforms, it can be minutes or tens of minutes) or, conversely, over a long time (e.g., for extensive and massive oilfields, it might involve hours). Measuring oil dryness in the bottle test, as described in the Experimental Section, is accomplished via thiefing35 the oil phase and serves to represent what pipelines and tankers will transport and refineries will receive. Interface quality provides a gauge for how well the process separation vessels will manage the buildup of an unwanted and unresolved interface (sometimes called a “rag” layer). Designing conditions that create good water drop and dry oil are not guarantees that the field will operate within specification for long. Interfaces can build over time, creating off-specification oil as well as oily water. In this extended investigation, the results from 24 crude oil emulsion studies will be examined using five bottle test parameters. The parameters are final water drop, oil dryness represented by BS(thief) and Slug(thief), and interface quality denoted as BS(composite) and Slug(composite). To test and ultimately rank field emulsion stability, it is necessary to break the emulsions under consideration. In the field, this is accomplished via a combination of methods, with heat, electrical, and chemical being the most common. For the fluids used in this study, heat alone was insufficient to resolve any of the emulsions because all were stable to this parameter. Using a critical electrical field approach to gauge emulsion strength is another possibility; however, the viscosity of many of the field emulsions would prevent their use in the most current apparatus.41 Chemical treatment also provides a comparative way to examine emulsion stability and was the method chosen for this approach. In designing the study, it was considered necessary to use a wide variety of demulsifiers (see Table 2) because this would ensure that each emulsion encountered would be resolved at least partly. The same ensemble of demulsifiers was used in each study, and each chemical was dosed at 50 ppm by volume. After all 24 bottle tests, the arithmetic mean value for each of the five emulsion stability parameters was calculated. While the mean is the most common way to represent the center of the data (i.e., the most representative value of a data set), it is not always the most appropriate way to summarize the central tendency of data sets.42 For data that is not normally distributed, the central tendency is often more aptly described using the median value (i.e., the midpoint of the data) because it is less sensitive to outliers. For this reason, the median values were also calculated for each emulsion stability parameter. In the sum total of this work, 5 bottle test parameters were collected over 24 field studies. This results in 120 distributions, where each distribution records the results of 36 demulsifier results. As expected, all 120 distributions were not normally distributed. In many instances, the distributions were skewed to the left (i.e., outliers tailing off toward small values) or to the right (i.e., outliers tailing off toward large values). Examples (41) Sullivan, A. P.; Zaki, N.; Sjo¨blom, J.; Kilpatrick, P. K. The stability of water-in-crude and model oil emulsions. Can. J. Chem. Eng. 2007, 85, 793–807. (42) Harnett, D. L. Introduction to Statistical Methods; Addison-Wesley: Reading, MA, 1972; pp 11-16.

Figure 1. (A and B) Water drop frequency distributions for emulsions WV (normal) and WC-9b (skewed to the left).

of a normal and left-skewed distribution are shown in Figure 1. To account for the uniqueness of each of the distributions, both the mean and median values (Table 3) will be used as the dependent variables to describe emulsion stability. If the correlations using both mean and median results provide similar results, then the conclusions will be reinforced. Independent Variables Defined by Oil and Water Properties. To describe the aspects of emulsion stability, descriptors are needed. These generally come in the form of crude oil properties and composition. A prior study using the field bottle test approach used 12 crude oils and 10 independent variables related to crude oil properties.33 This expanded study uses a total of 18 variables, and 14 of the variables are associated with the oil phase (Table 1). These include API gravity, viscosity, the four SARA components, TAN, naphthenic acid number, inorganic solid content, three fingerprint metals (iron, nickel, and vanadium),43,44 the resin/asphaltene ratio (R/A),18,19,45 and aromaticity of the aromatic fraction.45,46 Over the years, each of these parameters and some of their combinations have been used to classify crude oils or gauge their behavior regarding emulsion stability. In addition to the crude oil properties, properties representing the water separated from the emulsions were included in the list of potentially descriptive independent variables. Model studies have shown that water chemistry and content can play a role in emulsion stability. Thus, water content,4,5 water density,47 the density difference between water and oil,47 and (43) Barwise, A. J. G. Role of nickel and vanadium in petroleum classification. Energy Fuels 1990, 4, 647–652. (44) Nalwaya, V.; Tangtayakom, V.; Piumsomboon, P.; Fogler, S. Studies on asphaltenes through analysis of polar fractions. Ind. Eng. Chem. Res. 1999, 38, 964–972. High iron levels can influence asphaltene polarity and promote asphaltene aggregation. . (45) Al-Sahhaf, T.; Elsharkawy, A.; Fahim, M. Stability of water-in-oil emulsions: Effect of oil aromaticity, resins to asphaltene ratio, and pH of water. Pet. Sci. Technol. 2008, 26, 2009–2022. (46) Aske, N.; Orr, R.; Sjo¨blom, J. Dilatational elasticity moduli of watercrude oil interfaces using the oscillating pendant drop. J. Dispersion Sci. Technol. 2002, 23, 809–825. (47) Grace, R. Commercial emulsion breaking. In EmulsionssFundamentals and Applications in the Petroleum Industry; Schramm, L. L., Ed.; American Chemical Society: Washington, D.C., 1992; Chapter 9, pp 313-339.


Poindexter and Marsh Table 4. R2 Summary for Linear Regressions

Table 3. Bottle Test Parameters crude oil

water drop (final)


59 36 23 54 52 54 44 50 70 56 55 96 92 83 56 63 78 66 56 88 81 76 68 86


70 24 20 57 53 58 34 53 70 61 69 96 92 86 66 68 84 67 61 91 88 88 67 86

oil dryness BS(t)

oil dryness Slug(t)

composite BS(c)

composite Slug(c)

water drop (final)

Mean Values 7.7 9.2 17.6 21.7 27.8 36.5 2.8 3.6 10.2 10.8 30.9 28.0 40.9 32.8 2.1 5.6 1.4 4.3 0.2 5.5 10.3 11.5 2.2 2.1 2.1 2.7 2.3 8.4 9.5 13.3 18.2 13.2 6.3 7.4 0.4 8.7 18.3 15.6 0.1 0.6 0.4 1.9 0.5 2.8 1.3 7.0 0.9 3.7

6.4 29.9 31.1 3.5 11.7 28.5 37.2 2.5 1.6 1.3 11.7 2.2 2.7 3.1 12.0 15.5 7.5 0.6 18.0 0.5 0.4 1.1 0.7 1.4

13.6 37.1 45.6 15.0 27.3 27.8 31.6 6.7 7.7 9.3 17.8 4.5 4.7 11.7 18.8 18.1 13.1 9.6 18.2 3.6 3.4 6.1 7.5 5.8

Median Values 7.4 8.9 14.6 18.0 28.0 40.5 2.6 3.1 3.6 3.2 33.7 30.0 50.0 41.0 0 3.6 1.3 3.6 0.1 5.4 9.4 12.0 0.2 1.2 0.4 2.4 2.1 7.3 7.6 10.5 12.3 13.8 5.7 5.6 0 8.5 12.0 14.5 0 0.4 0 1.1 0 1.2 0.7 6.6 0.2 2.5

6.0 24.4 32.0 3.9 5.0 30.4 44.7 0 1.3 0 10.0 0.3 0.9 2.3 9.8 8.4 5.0 0 14.1 0.2 0 0 0 0.4

12.0 38.0 47.0 15.0 26.0 27.0 37.0 5.8 6.0 8.0 15.0 3.4 4.0 10.0 14.0 15.5 12.3 9.4 16.0 3.0 2.4 3.1 7.6 5.1

oil dryness BS(t)

oil dryness Slug(t)

composite BS(c)

composite Slug(c)

solids, 0.53 asphaltenes, 0.38

Using Mean Results solids, 0.78 solids, 0.82 R/A, 0.31 R/A, 0.31

solids, 0.80 R/A, 0.29

solids, 0.79 R/A, 0.20

solids, 0.60 asphaltenes, 0.37

Using Median Results solids, 0.75 solids, 0.77 solids, 0.79 aromatics, 0.33 R/A, 0.31 R/A, 0.31

solids, 0.83 R/A, 0.22

This was performed using both the mean and median values of the field results. A summary of the linear regression results is provided in Table 4, where the two most influential variables for each bottle test parameter are listed along with their R2 value. Examination of Table 4 shows that only four variables make an appearance. In all 10 relationships, solid content is by far the single most descriptive variable, having R2 values ranging from 0.53 to 0.83. These values are remarkably high considering that solid content is competing against all other 17 parameters in the bottle test.52 For the five mean-based relationships, examples of the highest and lowest R2 values using solid content as the descriptor are presented in Figure 2. There is a noticeable drop in the R2 value between the highly descriptive solid content and the next most descriptive variable in Table 4. These secondary descriptors include the resin/ asphaltene (R/A) ratio (six appearances), asphaltene content (three appearances), and aromatic content (one appearance). It was necessary to exclude GM-1 from the R/A calculations because this oil contained no asphaltenes. For the four descriptors noted in Table 4, more stable emulsions had higher solid contents, lower R/A values, higher asphaltene content, and less aromatic content. All of these field-derived results agree with model studies, where more solids and asphaltenes are known

water pH45,48 were included. Because pH was measured in the laboratory and not immediately in the field, it is likely that degassing over time may have altered the values to some extent. Still, with this proviso, the laboratory measured values were included in the modeling work. Linear Regressions. The most common method to examine the relationship of one variable to another is via simple linear regression (i.e., the sum of the squares of the residuals).49,50 Linearity is typically defined by the R2 statistic, also called the coefficient of determination, where R2 values range from 0 (no relationship) to 1 (absolute linearity).51 As an initial assessment of the data, each of the five bottle test dependent variables in Table 3 were regressed against the 18 descriptors in Table 1. (48) Strassner, J. E. Effect of pH on interfacial films and stability of crude oil-water emulsions. J. Pet. Technol. 1968, 20, 303–321. (49) Alfassi, Z. B.; Boger, Z.; Ronen, Y. Statistical Treatment of Analytical Data; Blackwell Science: Oxford, U.K., 2005; p 80. (50) Harnett, D. L. Introduction to Statistical Methods; Addison-Wesley: Reading, MA, 1972; pp 287-298.

Figure 2. (A and B) Plots of solid content versus two different emulsion stability parameters: (A) mean water drop and (B) mean Slug(t). Each point represents a crude oil emulsion study. The least-squares regression line is included for reference in both plots.


Energy & Fuels, Vol. 23, 2009 1265

Figure 3. Partition tree analysis of the mean water drop values found in Table 3.

to be detrimental, while higher resin and aromatic levels are known to increase solvency and help counter the aggregation of asphaltenes. It is important to stress that the ability of the variance of an independent variable to account for the variance of a dependent variable does not prove causality. However, from numerous model studies, increasing the level of finely divided inorganic solids was shown to substantially increase emulsion stability.19,23-26 Partition Tree Analyses. In most regression methods, such as the simple linear regression method just presented or multiple linear regression, where more than one input is used in model building, the full range of the independent variable is regressed against the full extent of the dependent variable. For analysis of multivariate data sets, this approach may not provide the most suitable methodology. Other techniques, such as partition tree analysis, which is also known as recursive partitioning, can identify the most appropriate independent data range to describe the variance of the dependent variable. Partition tree analysis has its roots in the earlier developed techniques of automatic interaction detection (AID) and classification and regression trees (CART).53 Analysis by partition trees falls under the realm of data mining. This method allows for construction of highly informative multivariate models54,55 that can readily identify the most informative ranges of the independent variables and capture nonlinearity relationships. From a group of independent variables, partition tree analysis identifies the most appropriate independent variables and their data ranges for describing the variance or data spread of a given dependent variable. This is performed through a series of (51) For linear regression, R2 equals the square of the Pearson productmoment correlation coefficient, r, which is another common way of describing the relationship between variables. R2 is easier to interpret because its value specifies what fraction of the variation in the dependent variable is explained by an independent variable. (52) Sheskin, D. J. Handbook of Parametric and Nonparametric Statistical Procedures, 3rd ed.; Chapman and Hall/CRC: Boca Raton, FL, 2004; p 956. (53) Breiman, L.; Friedman, J. H.; Olshen, R. A.; Stone, C. J. Classification and Regression Trees; Chapman and Hall/CRC: Boca Raton, FL, 1998. (54) Izenman,A.J.ModernMultiVariateStatisticalTechniquessRegression, Classification, and Manifold Learning; Springer: New York, 2008; Chapter 9, pp 281-314. (55) For an informative account of partition tree or decision tree analysis in the medical field, see Gladwell, M. BlinksThe Power of Thinking without Thinking; Little, Brown and Company: New York, 2005; pp 125-136.

successive partitions or data splits, where each split group can be divided again. While various types of splits are possible in recursive partitioning, only binary splits were used in the analyses that follow. Recursive partitioning uses the sum of squares criterion, which effectively maximizes the difference between the means of the split groups. Once all possible splits have been calculated for the independent variables, the split with the largest difference between the two group means of the dependent variable is chosen as the best split. Once a split is found, the process can start again with each new partition. The same criterion is used again, namely, find the binary split for the independent variable that yields the greatest separation of the two resulting group means of the dependent variable under consideration. Care must be taken in the number of splits performed. Knowledge of the system is critical to determine if the splits are meaningful or just splitting noise. For this study, the technique starts by finding the order or importance of the independent variables (i.e., oil and water properties) that optimally explain the differences observed in the bottle test parameters. The steps taken in a partition tree analysis are best explained with an example. Figure 3 is a three split partition tree, where mean values of the water drop parameter serve as the dependent variable. Each data point on the graph represents the mean water drop for one crude oil. The grand mean of the water drop values is 64% and is represented by a horizontal line labeled “All Rows”. In this case, asphaltene content with a value of 7.9% (by weight) was found to yield the largest difference in mean water drop values for the split groups. Because all other independent variables could not as effectively account for the variance seen in the water drop values, asphaltene content was selected as the first split value. Those crude oils having an asphaltene content greater than or equal to 7.9% reside as a group on the left side of the plot and collectively have a mean value of 49%, while those oils with less than 7.9% asphaltenes reside on the right and have a mean value of 75%. As a whole and as expected, those oils with less asphaltenes drop water more readily. The right group is split again, but this time, inorganic solid content was found to be the optimal variable, with a split at 168 PTB. Thus, oils with solid levels less than 168 PTB and asphaltene contents less than 7.9% drop water more readily. In


Poindexter and Marsh

Figure 4. Partition tree analysis of the median BS(t) values found in Table 3.

effect, asphaltenes and solids have an interaction for the oils comprising the right side of the plot. When asphaltene and solid contents are lower, then water drop is more complete. However, when solid content is increased, then water drop is reduced. A second split was also performed on those oils containing greater than 7.9% asphaltenes. This second left side split used water density as the splitting variable. One oil, AB-3, had by far the lowest mean water drop. The water associated with this heavy Canadian oil had a very low density of 0.9978 g/mL, which happens to be the lowest value in Table 1. This result indicates that oils with high asphaltene content (i.e., heavy oils) and relatively fresh water are resistant to water drop. This conclusion once again agrees with experience.16 As seen in Figure 3, water drop is more facile for oils on the right side of the plot, as opposed to those on the left side. The parameters selected and their directionality provide an effective account for describing water drop behavior. In the above example, both secondary splits used a different variable than the first split variable. However, when successive splits use the same variable, then that variable is extremely useful in describing a complex system. Such was the case for many of the thief and composite results. Figure 4 provides an example of this occurrence. When analyzing the median values of the BS(thief) parameter, the first split involved solid content. Three oils (MT-1, MT-2, and AB-3) had solid contents greater than 664 PTB and exceptionally high median BS(t) values. For the remaining 21 oils on the left side of the plot, solid content was once again found to be the best splitting variable. Producing dry oil was more difficult when the solid content was greater than or equal to 254 PTB than when the solid content was lower. Even though WC-7 in the left most group (

Inorganic Solid Content Governs Water-in-Crude Oil Emulsion Stability

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