Copyright 2003, Society of Petroleum Engineers Inc. This paper was prepared for presentation at the SPE International Symposium on Oilfield Chemistry held in Houston, Texas, U.S.A., 5–7 February 2003. This paper was selected for presentation by an SPE Program Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Papers presented at SPE meetings are subject to publication review by Editorial Committees of the Society of Petroleum Engineers. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of where and by whom the paper was presented. Write Librarian, SPE, P.O. Box 833836, Richardson, TX 75083-3836, U.S.A., fax 01-972-952-9435.

Abstract Paraffin-waxes present in crude oils, at some thermodynamic states, exhibit the phenomenon of crystallization. The onset of wax crystallization temperature of stock tank oil at atmospheric pressure is known as the cloud point. In this paper, cloud point data are presented for several synthetic mixtures and crude oils. The cloud point data have been obtained via three different techniques: Near-Infra-Red (NIR) light attenuation, Dynamic Filtration Cloud Point (DFCP), and ASTM-D2500. For the transparent mixtures, the ASTM-D2500 method is being used as the standard against which the other two techniques are compared to. The data show that all three techniques are consistent with each other, although their precision is different. Because of its simplicity, higher precision, and wide applicability to all kinds of fluids and thermodynamic conditions, the NIR light attenuation technique is recommended. Furthermore, cloud point and wax deposition data from a variation of the DFCP technique are presented from various crude oils from around the world. Some of these oils contain natural asphaltene dispersants and wax crystal modifiers and as a result, although these oils contain substantial amounts of asphaltene and wax molecules, they remain stable at most thermodynamic conditions encountered during their production. Two cases of these “special” oils are presented here.

Introduction Naturally occurring hydrocarbons in the earth’s crust contain varying amounts of certain molecules generally called asphaltenes and waxes. Asphaltenes exhibit a behavior at some thermodynamic states called flocculation. That is, asphaltene particles or micelles present in crude oils aggregate or flocculate into larger aggregates or flocks. The locus of all

thermodynamic points in a P-T-x phase diagram at which flocculation occurs is called the Asphaltene Deposition Envelope (ADE). Asphaltene deposition can occur only at thermodynamic conditions within the ADE, hence, the word “deposition” in the name. Paraffin waxes present in crude oils, on the other hand, at some thermodynamic states, exhibit the phenomenon of crystallization. The locus of all thermodynamic points in a P-T-x phase diagram at which wax crystallization occurs is called the Wax Deposition Envelope (WDE). As with asphaltenes, wax deposition can occur only at thermodynamic conditions within the WDE, hence, the word “deposition” in the name. The onset of wax crystallization temperature of stock tank oil at atmospheric pressure is known as the cloud point. Paraffin waxes are rather a-polar molecules and their interactions are expected to be van der Waals or London dispersion type, whereas asphaltene molecules are polar in nature and, as a result, are expected to have polar, hydrogen bond type, or associative type molecular interactions. Asphaltene flocculation and wax crystallization are two mechanisms via which organic deposition takes place from crude oils. In crude oils, the probable shapes of the thermodynamic envelopes that are manifestations of these two mechanisms of organic deposition from the various reservoir fluids have been defined recently.1 Wax deposition is a serious field problem encountered during crude oil production that causes plugging of pipelines, well tubings, and surface and process equipment.2-3 Wax crystals change the flow behavior of crude oil from Newtonian to non-Newtonian.4-6 The wax crystals lead to higher viscosity, with increased energy consumption for pumping and a decreased pumping capacity. Wax deposition increases the pipeline roughness, which results in an increase in pressure drop. The other effect is to reduce the effective cross sectional area of the pipe. The deposits also cause subsurface and surface equipment plugging and malfunction, especially when oil mixtures are transported across Arctic regions or cold oceans.6-7 Wax deposition leads to more frequent pigging requirements. If the deposits get too thick, they reduce the capacity of the pipeline and cause the pigs to get stuck. Wax deposition in well tubings and process equipment may lead to more frequent shutdowns and operational problems. Also, some investigators report that wax deposition can result in severe formation damage.8-10 If the temperature of the fluid in the formation falls below the cloud point, wax precipitates and may deposit in the formation pores, partially blocking or plugging the fluid flow channels and thus restricting the flow.

SPE 80267

Cloud Point and Wax Deposition Measurement Techniques Kosta J. Leontaritis*, SPE, AsphWax Inc. and John D. Leontaritis Kosta Oil Field Technologies Inc.

*Corresponding author

2 SPE 80267

The lighter components of crude oil help to keep the heavier components in solution. These higher molecular weight solids precipitate whenever anything occurs that decreases the carrying capacity of the fluid solvent. Crude oil is a mixture of a wide range of hydrocarbons. The carbon number distribution of the paraffins varies from one crude oil to another. The solubility of a specific n-paraffin in a crude oil is a strong function of its carbon number and system temperature. Temperature is a major driving force for the paraffin solid-liquid phase equilibria and the subsequent separation of the two phases. The two major parameters that affect the solubility of wax in oil are the temperature and composition of the oil.9 Pressure has a lesser effect. The precipitation of wax is sometimes irreversible in that the wax, once removed from solution, is very difficult to re-dissolve, even after original formation temperatures are restored.8 Precipitation of wax from petroleum fluids is considered to be a thermodynamic molecular saturation phenomenon.1, 11 Wax molecules are initially dissolved in a chaotic molecular state in the fluid. At some thermodynamic state the fluid becomes saturated with wax molecules, which then begin to precipitate. This thermodynamic state is called the onset of wax crystallization or solidification. It is analogous to the usual dew point or condensation phenomenon, except that in wax precipitation a solid is precipitating from a liquid, whereas in condensation a liquid is precipitating from a vapor. In wax precipitation, resin and asphaltene micelles behave like heavy molecules. When their kinetic energy is sufficiently reduced due to cooling, they precipitate out of solution but they are not destroyed. If kinetic energy in the form of heat is supplied to the system, these micelles will desegregate and go back into stable suspension and Brownian motion. Big savings can be obtained from the accurate advance prediction of the onset of wax crystallization. Knowledge of the magnitude of wax deposition can also lead to reduction of insulation requirements for production and transportation systems. Furthermore, wax problems can be dealt with in an early stage of a project, so that sufficient thermal insulation is planned for, instead of expensive chemical injection and loss of system capacity.12 Improved heat transfer efficiency can result in reduced process heat loads. Capacity reduction in heat exchangers due to blockage or vibration problems due to high velocity or flashing can be overcome. The size of export pumps and flowlines can be reduced from an accurate knowledge of the effect of wax formation on crude viscosity. The minimum pigging frequency can be determined if the amount of wax deposition can be estimated. Also, problems related to start-up and shutdown can be solved cost-effectively. Laboratory Wax Measurement Techniques A description of the Cloud Point and Wax Deposition Measurement techniques covered in this paper are discussed next. Cloud Point. Three Cloud Point Measurement techniques are presented and compared in this paper.

ASTM-D250013 is being used as the standard against which the other two techniques are compared to. The ASTM-D2500 technique is shown in Figure 1.

Figure 1: ASTM-D2500 Cloud Point Test Apparatus The sample is cooled at a specified rate and examined periodically. The temperature at which a cloud is first observed at the bottom of the test jar is recorded as the cloud point. The ASTM-D2500 test method covers only petroleum products which are transparent in 40 mm layers of thickness, and with a cloud point below 49 °C. Hence, all ASTM-D2500 cloud points presented in this study are of petroleum products or solvents fortified with paraffin wax. The Dynamic Filtration Cloud Point System14 (DFCP) is shown in Figure 2.

Figure 2: Dynamic Filtration Cloud Point Test Apparatus The dynamic or filtration technique takes advantage of the following three phenomena to determine the cloud point:

• All asphaltene micelles remain in stable suspension before the onset of wax crystallization.

• All paraffin-wax molecules remain in molecular state before the onset of wax crystallization.

BPR

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0.1 µ Filter

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0.1 µ Filter

SPE 80267 3

• After the onset of wax crystallization the first 0.1-micron or larger wax crystals are formed.

The hydrocarbon mixture to be tested for onset is at some pressure and temperature above wax onset conditions (say reservoir conditions) in a piston transfer cylinder. The entire system is maintained at the desired testing temperature and pressure. Flow is pumped (usually at around 0.2 to 0.5 cc/min) through the 0.1-micron filter and the BPR. The BPR maintains the required operating pressure of the flowing fluid. The water bath is programmed to decrease the testing temperature at some predetermined rate, say 0.2 °F/min. The computer monitors the differential pressure (∆P) across the filter, the pressure at the BPR, the temperature of the oil, and other operating parameters. The ∆P across the filter vs. the oil temperature is plotted as shown in Figure 3.

Dynamic or Filtration Wax OnsetLive Oil at 3000 psig

0.0000

0.2000

0.4000

0.6000

0.8000

1.0000

30.0 50.0 70.0 90.0 110.0

Temperature, °F

Pre

ssur

e D

rop,

psi

Hagen-Poiseuille Fit Data Curve Fit Experiment

Wax Onset at 64 °F

Figure 3: DFCP Example Live Oil Cloud Point Test The temperature at which the ∆P across the filter begins to rise signals the onset of wax crystallization, which is 64 °F. The actual data analysis and interpretation is actually somewhat more involved and is explained next. The Hagen-Poiseuille equation describes incompressible fluid flow for Newtonian fluids under laminar flow conditions.

2

410*68.6d

LP υµ−

=∆ 1

Where: ∆P = pressure drop, psi µ = viscocity, centipoise L = length of tubing, feet υ = Q/A = fluid mean velocity, feet/second d = internal tubing diameter L, υ, d remain constant during the experiment. µ, however, varies with temperature. Beal's correlation15 for estimating viscosities of hydrocarbon liquids is:

+−

+

+=

APIAnti

TAPI

33.843.0log

53.4

7

20036010*8.132.0µ 2

A modified functional form of Beal's correlation is used here to represent the variation of viscosity with temperature and pressure.

cb

PT

a

+

=200

360µ 3

Where: T = temperature, °F P = pressure, psig a, b, c = constants Combining equations 1 and 3 one gets:

cb

PT

aP

+

=∆200

360 4

Equation 4 is used to fit the ∆P vs Temperature data at the pressure P of the experiment in the Newtonian range, i.e., at temperatures above the onset of wax crystallization. The remaining data, i.e., the data at temperatures below the onset of wax crystallization, are fitted to a suitable equation that makes the best fit to the data. The onset of wax crystallization is the temperature at which the two curves intersect each other. Figure 3 demonstrates the application of above procedure, which yields the onset temperature at 64 °F.

Figure 4: NIR Cloud Point Test Apparatus The Near-Infra-Red (NIR) Light Attenuation14 apparatus is shown in Figure 4. The NIR wax onset method is based on the observation that there is a sharp increase in light absorption or attenuation in the near-infrared region at the onset of wax crystallization. The mechanism of wax crystallization and why NIR light spectra provide the information necessary for determining the onset of wax crystallization has not been completely understood yet. However, considerable knowledge has been already accumulated regarding the relationship of NIR and wax phenomena that is described next.

Oil

Pressure Control Module

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Spectrophotometer

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�������������������

4 SPE 80267

From spectroscopic theory and experiments, we know that the absorption of light by a component in solution follows Beer's Law: 13 I(λ) = Io(λ) exp(-E(λ) l m) 5 Where: λ = wavelength of light Io(λ) = intensity of light entering sample I(λ) = intensity of light leaving sample E(λ) = molar absorptivity at wavelength λ, liter/

(mole-cm) l = light path length through sample, cm m = molarity of absorbing species, moles/liter The absorbance, A(λ), at wavelength λ, is given by the following relation:

( ) ( )( )

=

λλ

λIIA o

10log 6

Combining Equations 5 and 6, one gets the linear relationship: A(λ) = 0.4343 E(λ) l m 7 Transmittance, T(λ), of NIR light through a sample of waxy/asphaltenic oil has also been used to detect the onset of wax crystallization. There is a sharp decrease in the transmittance of NIR light through a sample of waxy/asphaltenic oil (rather than increase as in the case of absorbance) at the onset of wax crystallization. The transmittance at wavelength λ is defined as follows: T(λ) = I(λ)/Io(λ) = exp(-E(λ) l m) 8 Hence, combining equations 6 and 8 one gets:

( ) ( )

=

λλ

TA 1log10 9

Equation 9 shows that the absorbance and transmittance are logarithmically related. This is illustrated numerically in the following examples: Absorbance = 0 ⇒ Transmittance = 100 % Absorbance = 1 ⇒ Transmittance = 10 % Absorbance = 2 ⇒ Transmittance = 1 % A typical absorption/attenuation plot when cooling a special wax-Hexane mixture, at atmospheric pressure, is shown in Figure 5. In this case, the cloud point is indicated at 59 °F.

NIR Cloud Point Test ofSpecial Wax-Hexane Mixture

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

40 45 50 55 60 65 70 75 80 85 90

Temperature, °F

Abs

orba

nce

Uni

ts Onset at 59 °F

Figure 5: NIR Cloud Point Test Example In Figure 5, as the fluid is cooled down, the trend of the data curves upwards thus indicating that the absorbing/attenuating molecules are undergoing a change that permits less of the light to travel through the oil sample. It is not clear how much of the light is absorbed or scattered. However, it is known that during wax crystallization larger and new wax crystals are formed. Hence, there is a strong possibility that light scattering (by striking the newly formed crystals) does take place as the wax crystallization process progresses and more and larger particles are formed. The point at which the "absorbance-scattering" begins to rise rather exponentially is called the onset of wax crystallization. Based on the fact that new and larger crystal particles are formed, light scattering is a more pronounced physical phenomenon than light absorbance during crystallization. Hence, the actual NIR curve, in addition to yielding the onset, it also provides dynamic wax crystal/particle size information. This information is useful to models that simulate particle size distribution during wax crystallization. Because of its simplicity, higher precision, and wide applicability to all kinds of fluids and thermodynamic conditions, the NIR light attenuation wax onset technique is preferred over the other methods. Wax Deposition. Two wax deposition measurement techniques are discussed and compared in this paper. A dynamic technique, that is with the oil flowing and simulating the real system, and a static technique where the oil is static thus maing the technique more qualitative than quantitative. The Dynamic Wax Deposition Apparatus14 is an adaptation of the dynamic filtration wax onset apparatus. A schematic is shown here in Figure 6.

SPE 80267 5

Figure 6: Dynamic Wax Deposition Apparatus Wax deposition is dependent on the thermal and mechanical history of the oil. This is because the wax crystals once they form need substantial heating and mixing above the cloud point temperature to be dissolved. Wax deposition is different when the oil is heated without dissolving all the wax crystals than when the oil is heated in a way that dissolves all wax crystals.

Dynamic Wax Deposition Test

50

51

52

53

54

55

40 50 60 70 80 90 100 110 120 130

Temperature, °F

Pres

sure

, psi

g

Wax Onset

Figure 7: Dynamic Wax Deposition Example

An example wax deposition test-run is shown in Figure 7. Eventhough this apparatus does not have filter, the cloud point is still evident at about 84 °F. The primary wax deposition data, however, are obtained in this case at about 52 °F. At that temperature, cooling is stopped and flow continues. The build-up of ∆P is noted in say psi/hr or day. This is related to the wax deposition rate in the experimental system. It is emphasized that the dynamic wax deposition system is a flow-through system. It is not a “flow-loop.” Flow loops do not simulate as closely as flow-through systems field wax deposition conditions. The closed loop is a “batch” system; hence, the nature of depositing wax changes continuously with time. That is not the case in either real operating systems or in flow-through lab set-ups.

Once the wax deposition psi/day rate data is obtained, it may to be converted to an inch/day wax deposition rate for the lab set-up by assuming that wax deposition is occurring evenly in the entire lab pipe length. It is known that in reality this is not the case. The wax deposit profile in the pipe is not “flat.” However, this rate gives an approximate idea of what to expect in the field. One can relate this wax deposition rate to other similar rates from oils with known field wax deposition behavior. Also, wax deposition simulators may use it as a tuning target. An example data conversion is shown in Figure 8.

Figure 8: Dynamic Wax Deposition Example The Static Wax Deposition Apparatus14 is shown in Figure 9. This is an adaptation of the conventional cold plate (or cold finger) semi-quantitative wax deposition measurement technique.

Figure 9: Static Wax Deposition Apparatus The Static Wax Deposition Test or Cold Plate Test (CPT) determines the amount of waxes that deposit on a metal plate (i.e., cold plate), whose weight is known, dipped inside an oil sample that is maintained at some temperature above its cloud point. Cold fluid, usually but not always at 40 °F, circulates inside the cold plate. Inside the occlusions of the depositing wax crystal structure resides a substantial amount (usually more than 80 Vol.%) of liquid stock tank oil. Laboratory Wax Results Cloud point and wax deposition data from several oils are presented next.

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Use coil in vertical position to study deposition in conduits with vertical orientation.

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Directly Measured Data Wax Build-upµ, cp d, inch L, ft Constant Q, cc/min Q, ft3/hr v, ft/hr Reynold's Shear, sec-1 ∆P, psi Rate, psi/day

1.7 0.04805 4.833 1.856E-07 0.5 0.0010593 84.16374 4.278119 46.70897789 0.0555915 0.04805 4.833 1.856E-07 0.5 0.0010593 84.16374 0.484854 46.70897789 0.4904815 0.04418 4.833 1.856E-07 0.5 0.0010593 99.554383 0.527325 60.09016621 0.68627 21.68713239

Lab Data InterpretationsLab Pipe Area, ft2 = 0.0608Oil Density, lb/ft3= 52.2787Wax Density, g/cc= 0.8500Wax Volume, ft3/day= 0.0000Wax Volume, cc/day= 0.2663Wax Mass, g/day= 0.2264Wax Dep Rate, g/day/ft2 = 3.7254Wax Dep Rate, ft3/day/ft2 = 0.0002Field System Data Average Field Shear Rate

Per Day Per Day Per Day Per Month Total Deposit Vol % Liq = 0.35Length, ft. = 150004.8 Wax Vol Wax Dia Wax Vol Wax Vol Per MonthOD, inch ID, inch Surf Area, ft2/ft ft3/ft Inch Bbls/ft Bbls/ft Barrels Wax Q, ft3/hr v, ft/hr Shear, sec-1

8.625 6.893 1.803668333 0.00027913 6.889284846 4.971E-05 0.0014914 223.7152323 1980 62403 241.4158798Wax Dep Rate Linearly Extrapolated Wax Deposit Thickness Field Reynold'sinch/day Deposit Inch Deposit Inch Deposit Inch Critical Deposit Thickness 51571.02789

0.003715154 90-day Rate 180-day Rate 360-day Rate (20% of ID)/20.33436387 0.668727748 1.3374555 0.6893

6 SPE 80267

Cloud Point. The repeatability, reproducibility, and accuracy of the Dynamic Filtration Cloud Point Test data for the wax-Hexane mixture of Figure 5, are now checked against the ASTM-D2500 standard method. It is noted that ASTM-D2500 has a repeatability and reproducibility of about ±5 °F. Table-1 shows the repeatability of the DFCP method and its accuracy as it compares to the ASTM-D2500 method.

Table 1: Dynamic Filtration Cloud Point Method An example run, Run 1 in Table-1, is shown in Figure 10.

Special Wax-Hexane Mixture Cloud Point

0.00.20.40.60.81.01.21.41.61.82.0

40.0 60.0 80.0 100.0

DeltaP, psi

Tem

pera

ture

, °F ASTM D-2500

Cloud Point = 62 °F±5

Cloud Point @61 °F

Figure 10: Wax-Hexane Mixture DFCP Run 1 Figure 1 shows the NIR Cloud Point run for the same sample shown in the above Figure 10. It is evident that either method detects the wax crystals immediately after they form. The repeatability, reproducibility, and accuracy of the NIR and DFCP methods for the wax-Hexane mixture of Figures 5 and 10 are now checked against the ASTM-D2500 standard method. Table-2 shows the repeatability of the NIR and DFCP methods and their accuracy as they compare to that of the ASTM-D2500 method.

Table 2: Near-Infra-Red and DFCP Comparison Because of its simplicity, higher precision, and wide applicability to all kinds of fluids and thermodynamic conditions, the NIR light attenuation technique is recommended and adapted in this paper. In the following six figures NIR cloud point versus composition data are presented for 10 black oils and 7 gas condensates from around the world.

Cloud Point Relation to Oil C50+

0

20

40

60

80

100

120

140

160

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

Weight. %

Clo

ud P

oint

, °F

Figure 11: Oil Cloud Point and C50+ Correlation

Cloud Point Relation to Oil Normal Paraffins

0

20

40

60

80

100

120

140

160

0 1 2 3 4 5 6

Weight. %

Clo

ud P

oint

, °F

nc30-nc49 % C50+ %

Figure 12: Oil Cloud Point and nC30+ Correlation

Test Run Start Temp., °F Cloud Point, °FRun 1 93 61Run 2 96 62Run3 97 61

Repeatability and Accuracy = ±0.5 °F

Dynamic Filtration Cloud Point MethodSpecial Wax-Hexane Mixture

ASTM-D2500 Cloud Point is 62 °F

Test Run NIR CP, °F DFCP CP, °FRun 1 59 61Run 2 60 62Run3 60 61

Repeatability = ±0.5 °F ±0.5 °F

Accuracy = ±1 °F ±0.5 °F

DFCP and NIR Cloud Point MethodsSpecial Wax-Hexane Mixture

ASTM-D2500 Cloud Point is 62 °F

SPE 80267 7

Cloud Point Relation to Oil Composition

0

20

40

60

80

100

120

140

160

0 5 10 15 20 25

Weight. %

Clo

ud P

oint

, °F

Wax % AR % ARW % nc30-nc49 % C50+ %

AR = Asphaltenes + ResinsARW = Asphaltenes + Resins + Waxes

Figure 13: Oil Cloud Point-Composition Correlation

Cloud Point Relation to Gas C50+

0

20

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60

80

100

120

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Weight. %

Clo

ud P

oint

, °F

Figure 14: Gas Cloud Point and C50+ Correlation

Cloud Point Relation to Gas Normal Paraffins

0

20

40

60

80

100

120

0 0.2 0.4 0.6 0.8 1 1.2 1.4

Weight. %

Clo

ud P

oint

, °F

nc30-nc49 % C50+ %

Figure 15: Gas Cloud Point and nC30+ Correlation

Cloud Point Relation to Gas Composition

0

20

40

60

80

100

120

0 0.5 1 1.5 2 2.5 3 3.5

Weight. %

Clo

ud P

oint

, °F

Wax % AR % ARW % nc30-nc49 % C50+ %

AR = Asphaltenes + ResinsARW = Asphaltenes + Resins + Waxes

Figure 16: Gas Cloud Point-Composition Correlation Although the data in Figures 11 to 16 indicate some correlation of the oil and gas condensate cloud point with the composition data, especially but not only with the C50+ paraffins, this correlation is not due to fundamental or mechanistic reasons. This will become apparent later in the section “Special Case: Oils Containing Natural Wax Crystal Modifiers,” where it will be shown that the cloud point is not at all influenced by the oil SARA (Saturate-Aromatic-Resin-Asphaltene) and HTGC (High Temperature Gas Chromatography) compositions.

Wax Deposition. Wax deposition data are presented next for the dynamic wax deposition and static wax deposition apparatuses. First, some of the raw data obtained for the dynamic wax deposition example shown in Figure 8 is shown below in Table-3.

Table 3: Dynamic Wax Deposition Data for Example of Figure 8 It is evident from the data that wax deposition in the lab apparatus starts high and after a while it begins to decline as waxes deposit and the shear rate increases. The average initial wax deposition rate is about 21.6 psi/day for data points collected every 5 minutes in Table 3. The raw data for the

DP, psi Rate, psi/min Rate, psi/hr Rate, psi/day Avg Rate0.475 0.0021 0.129 3.086 psi/day0.505 0.0046 0.277 6.646 21.6410.525 0.0067 0.400 9.6000.550 0.0095 0.573 13.7450.575 0.0130 0.780 18.7200.570 0.0139 0.833 20.0000.575 0.0163 0.975 23.4000.560 0.0164 0.986 23.6570.550 0.0175 1.050 25.2000.530 0.0170 1.020 24.4800.525 0.0200 1.200 28.8000.515 0.0233 1.400 33.6000.475 0.0150 0.900 21.6000.465 0.0200 1.200 28.800

Raw Wax Deposition Data for Example in Figure 8

8 SPE 80267

static wax deposition example shown in Figure 9 are shown below in Table 4.

Table 4: Static Wax Deposition Data for Example of Figure 9 In Table 4, 6 cases of the same oil were run with different chemicals to determine the effect of 5 chemicals on wax deposition. However, one could have placed six different oils in the cells and compared the wax deposition from them. Although such data would appear to have only qualitative usefulness, if the true field wax deposition rate of one or two of the oils is known, the wax deposition rate of the other oils could be estimated by extrapolation or interpolation (preferred). Special Case: Oils Containing Natural Wax Crystal Modifiers It was mentioned earlier that some oils contain natural asphaltene dispersants and wax crystal modifiers and as a result, although these oils contain substantial amounts of asphaltene and wax molecules, they remain stable at most thermodynamic conditions encountered during their production. The following two examples demonstrate this point. Special Case 1: The complete composition and fluid characterization of the Oil A is shown in Table 5.

Table 5: Oil A PARA EOS Fluid Characterization The above method of characterizing reservoir fluids, called PARA (Paraffin-Aromatic-Resin-Asphaltene) EOS Fluid

Characterization, has been previously described. 14, 16 This oil contains 0.15 wt% C50+ and 2.13 wt% C30-C49. However, the oil did not precipitate any waxes in the following two tests whose data are shown in Figures 17-18 and Table-6.

Oil A Near-Infra-Red Cloud Point Test

0.000.050.100.150.200.250.300.350.40

20 40 60 80 100 120 140 160

Temperature, °F

N-I

-R L

ight

Att

enua

tion,

AU

No wax onset indicated from 158 to 38 °F.

Figure 17: Oil A NIR Cloud Point Test

Figure 18: Oil Static Wax Deposition Test

Table 6: Static Wax Deposition Data for Example of Figure 18

Special Case 2: The complete composition and fluid characterization of the Oil B is shown in Table 7.

Component MW Tc, °K Pc, bar Omega Mole Fr. Weight Weight Fr.N2-CO2 44.010 304.206 72.948 0.225 0.000984 0.043296 0.000481METHANE 16.043 190.550 45.990 0.011 0.559697 8.979217 0.099731ETHANE 30.070 305.330 48.710 0.099 0.063172 1.899592 0.021098PROPANE 44.097 369.850 42.470 0.152 0.037729 1.663736 0.018479I-BUTANE 58.124 408.322 36.018 0.185 0.008034 0.466957 0.005186N-BUTANE 58.124 425.250 37.920 0.199 0.017356 1.008773 0.011204C5-C9 102.725 540.855 27.313 0.355 0.099486 10.219652 0.113508C10-C15 168.735 677.669 21.759 0.631 0.081986 13.833971 0.153652C16-C29 274.966 806.437 15.705 0.890 0.049726 13.673064 0.151864AROMATIC 425.000 867.799 12.376 1.155 0.060792 25.836635 0.286963C30-C49 462.557 843.814 8.699 1.262 0.004145 1.917469 0.021297C50+ 678.381 923.658 6.505 1.697 0.000204 0.138710 0.001541RESINS 600.000 942.131 5.204 1.710 0.014418 8.651074 0.096086ASPHALTE 750.000 960.604 5.053 1.812 0.002270 1.702571 0.018910

1.000000 90.034716 1.000000

AsphWax Reservoir Oil PARA Fluid Characterization

Date: 18-Feb-02Fluid: AsphWax Well #1 STO

Initial Oil Temperature, °F: 140.0Chemical Treatment Temperature, °F: 140.0Hot Water Bath/Oil Temperature, °F: 140.0Cold Plate Temperature, °F: 40.0

Beaker # Chemical PPM Deposit, g % Effectiveness1 None 0 0 NA

Cold Plate Test Report

Date: 17-Aug-02Fluid: AsphWax Well #1 STOInitial Oil Temperature, °F: 140.0Chemical Treatment Temperature, °F: 140.0Hot Water Bath/Oil Temperature, °F: 120.0Cold Plate Temperature, °F: 40.0Beaker # Chemical PPM Deposit, g % Effectiveness

1 None 0 0.9101 NA2 WPPD* 1000 0.7588 16.63 WCM* 1000 1.647 -81.04 WCM* 1000 1.8344 -101.65 MUAW° 1000 0.3962 56.56 MAW° 1000 0.4921 45.9

* Wax Crystal Modifier° Wax Dispersant

Cold Plate Test Report

SPE 80267 9

Table 7: Oil B PARA EOS Fluid Characterization The above oil contains 0.19 wt% C50+ and 2.27 wt% C30-C49. However, the oil did not precipitate any waxes in the following cloud point test down to 30 °F shown in Figure 19.

Oil B Near-Infra-Red Cloud Point Test

0.000.020.040.060.080.100.120.140.160.180.20

20 40 60 80 100 120 140 160

Temperature, °F

N-I

-R L

ight

Att

enua

tion,

AU

No Wax Onset indicated down to 30°F

Figure 19: Oil B NIR Cloud Point Test Conclusions Cloud point and wax deposition data were presented for several synthetic mixtures and crude oils. The cloud point data have been obtained via three different techniques: Near-Infra-Red (NIR) light attenuation, Dynamic Filtration Cloud Point (DFCP), and ASTM-D2500. Also, two wax-deposition techniques were presented; the dynamic and static wax deposition techniques. The following conclusions can be made:

• For the transparent mixtures, the ASTM-D2500 method was the standard cloud point method against which the other two techniques are compared to. The data showed that all three techniques are consistent with each other, although their precision is different. Because of its simplicity, higher precision, and wide applicability to all kinds of fluids and thermodynamic conditions, the NIR light attenuation technique is recommended.

• Wax deposition data from two dynamic and static techniques were presented from various crude oils from around the world. Some of these oils contain natural asphaltene dispersants and wax crystal

modifiers and as a result, although these oils contain substantial amounts of asphaltene and wax molecules, they remain stable at most thermodynamic conditions encountered during their production.

• Cloud point data were correlated with compositional data of crude oils and gases from around the world. The compositional data were obtained via the PARA analysis method. This EOS Fluid Characterization method of characterizing reservoir fluids has been previously described. 14, 16

• It is evident from the results of this study that the behavior of heavy wax molecules from reservoir hydrocarbons is largely dependent on compounds or molecules that are not readily identified by conventional analytical techniques such as Gas Chromatography Compositional analysis.

Acknowledgements The authors wish to thank the partners of AsphWax, Inc. for allowing publication of the material in this paper. References 1. Leontaritis, K.J., "The Asphaltene and Wax Deposition

Envelopes," The Symposium on Thermodynamics of Heavy Oils and Asphaltenes, Area 16C of Fuels and Petrochemical Division, AIChE Spring National Meeting and Petroleum Exposition, Houston, Texas, March 19-23, 1995.

2. Bern, P.A., V. R. Withers, and R. J. R. Cairns, “Wax Deposition in Crude Oil Pipelines,” Proc. Eur. Offshore Pet. Conf., London. Oct. 21-24 (1980).

3. Burger, E. D., T. K. Perkins, and J. H. Striegler, “Studies of Wax Deposition in the Trans Alaska Pipeline,” J. Petr. Tech., June, 1075 (1981).

4. Ferris, S. W., and H. C. Cowles, “Crystal Behavior of Paraffin Wax,” Ind. Eng. Chem., 37, 1054-1062 (1945).

5. Edwards, R. T., “Crystal Habit of Paraffin Wax,” Ind. Eng. Chem., 49, 750-757 (1957).

6. Economides, M. J., and G. T. Chaney, “The Rheological Properties of Prudhoe Bay Oil and The Effects of a Prolonged Flow Interruption on Its Flow Behavior,” Soc. Pet. Eng. J., June, 408 (1983).

7. Perkins, T. K., and J. B. Turner, “Starting Behavior of Gathering Lines and Pipelines Filled with Gelled Prudhoe Bay Oil,” J. Pet. Technol., March, 301 (1971).

8. Sutton, G. D., and L. D. Roberts, “Paraffin Precipitation During Fracture Stimulation,” J. Pet. Technol., Sep., 997 (1974).

9. Nenniger, J. and G. Nenniger, “Optimizing Hot Oiling/Watering Jobs to Minimize Formation Damage,” SPE Paper # CIM/SPE 90-57, presented at the International Technical Meeting in Calgary, June 10-13, (1990).

10. Leontaritis, K.J., "Wellbore Damage by Wax Deposition in Gas-Condensate Reservoirs," World Oil, October 1999.

11. Narayanan, L., Leontaritis, K.J., and Darby, R., "A Thermodynamic Model for Predicting Wax Precipitation from Crude Oils," The Symposium of Solids Deposition, Area 16C of Fuels and Petrochemical Division, AIChE Spring National Meeting and Petroleum Exposition, Houston, Texas, March 28-April 1, 1993.

12. Leontaritis, K.J., "Hydrate and Wax Flow Assurance Issues in Subsea Satelite Wells and Flowlines, "2002 International Conference on Heavy Organics Depositions,” Puerto Vallarta, Jalisco, Mexico, November 17-21, 2002.

Component MW Tc, °K Pc, bar Omega Mole Fr. Weight Weight Fr.N2-CO2 43.428 297.733 71.514 0.218 0.003279 0.142411 0.001376METHANE 16.043 190.550 45.990 0.011 0.477216 7.655982 0.073984ETHANE 30.070 305.330 48.710 0.099 0.039828 1.197617 0.011573PROPANE 44.097 369.850 42.470 0.152 0.036108 1.592242 0.015387I-BUTANE 58.124 408.322 36.018 0.185 0.008362 0.486048 0.004697N-BUTANE 58.124 425.250 37.920 0.199 0.018864 1.096440 0.010595C5-C9 103.729 543.344 27.105 0.359 0.149335 15.490365 0.149691C10-C15 167.591 675.627 21.808 0.628 0.108498 18.183200 0.175714C16-C29 276.526 807.724 15.602 0.893 0.080481 22.254994 0.215061AROMATIC 425.000 867.799 12.376 1.155 0.062165 26.419920 0.255309C30-C49 463.385 843.723 8.704 1.263 0.005069 2.348852 0.022698C50+ 679.080 923.658 6.505 1.692 0.000284 0.192570 0.001861RESINS 600.000 942.131 5.204 1.710 0.009756 5.853640 0.056567ASPHALTE 750.000 960.604 5.053 1.812 0.000757 0.567770 0.005487

1.000000 103.482049 1.000000

AsphWax Reservoir Oil PARA Fluid Characterization

10 SPE 80267

13. The American Society of Testing and Materials.: “Standard Test Method for Cloud point of Petroleum Products,” ASTM Standard Designation: D 2500-91, December 1991.

14. Fluid Characterization for Flow Assurance.: Chapter-7 of AsphWax Professional Course Manual.

15. Standing, M., B.: "Volumetric and Phase Behavior of Oil Field Hydrocarbon Systems," Society of Petroleum Engineers of AIME, Dallas, Texas, 1977.

16. Leontaritis, K.J.: "PARA-Based (Paraffin-Aromatic-Resin-Asphaltene) Reservoir Oil Characterization," SPE Paper No. 37252, SPE International Symposium on Oilfield Chemistry, February 18-21, 1997, Houston, Texas.