Modeling of Asphaltene Precipitation Due to Changes inComposition Using the Perturbed Chain Statistical Associating Fluid

Theory Equation of State†

Doris L. Gonzalez,‡ George J. Hirasaki,‡ Jeff Creek,§ and Walter G. Chapman*,‡

Department of Chemical Engineering, Rice UniVersity, Houston, Texas, and CheVronTexaco EnergyTechnology Co., Houston, Texas

ReceiVed September 6, 2006. ReVised Manuscript ReceiVed March 26, 2007

Asphaltene precipitation and deposition adversely affect production assurance and are key risk factors inassessing difficult environments such as deepwater. Deposition in the near well bore regions and productiontubulars implies high intervention and remediation costs. Prediction of asphaltene precipitation onset representsa challenge for the flow assurance area. The applicability of the PC-SAFT equation of state model to predictasphaltene onset of the precipitation in live oils is demonstrated by studying representative examples fromfield experiences with asphaltene problems during production. These examples not only validate the proposedmodel but also confirm the theory that asphaltene phase behavior can be explained based only on molecularsize and van der Waals interactions. The PC-SAFT equation of state estimates also properties such as densitiesand bubble points of live oil systems using a minimum number of real components and “realistic”pseudocomponents. The amount and composition of the asphaltene precipitated phase is also determined aspart of the equilibrium calculations. This paper presents experimental observations and simulation results atreservoir conditions using the PC-SAFT equation of state on the effect of compositional changes in live oilscaused by two common processes in the oil industry: oil-based-mud (OBM) contamination and reinjection ofassociated gas. In the first case, the downhole oil samples can be contaminated with OBM, causing laboratorymeasurements of the bubble point and asphaltene precipitation to be different from the reservoir fluid. In thesecond case, the reinjection of gas into the field increases the gas-oil-ratio (GOR) of the oil. The addition ofgas into the oil can cause asphaltene precipitation and deposition due to the increase of light components thatreduces asphaltene solubility. Asphaltenes in this example are treated as both monodisperse and polydispersepseudocomponents. From the obtained results, it can be concluded that the live oil modeled using the PC-SAFT equation of state properly predicts the asphaltene phase behavior under these compositional changes.The PC-SAFT equation of state model is a commercially available, proven tool.

Introduction

Asphaltene stability depends on a number of factors includingpressure, temperature, and composition of the fluid. The effectof composition and pressure on asphaltene precipitation isgenerally stronger than the effect of temperature. Changes incomposition arise in the presence of oil-based muds (OBMs).Significant overbalance pressure during the drilling process canresult in the mud filtrate invasion into the formation and mixwith the reservoir fluid. Mud filtrate can significantly modifythe composition of the near wellbore crude. Phase behaviormeasurements performed on reservoir fluid samples are affectedby OBM contamination resulting in wrong data interpretation.Both the bubble point and the asphaltene precipitation onsetcan be affected by contamination of the oil with drilling fluids.Changes in composition also occur during gas injection pro-cesses employed for both enhanced oil recovery (EOR) in theinjection wells and for gas lift in the wellbore. The gas can

dissolve into the crude oil and decrease asphaltene solubility.1

The miscible gas also decreases the density and viscosity sothat the crude oil will flow more readily. The effect ofconsidering asphaltenes as monodisperse or polydispersepseudocomponent will be analyzed in this example.

The objective of this paper is to present experimentalobservations and simulation results at reservoir conditions onthe effect of compositional changes in live oils that may resultin either asphaltene precipitation or solubilization using the PC-SAFT equation of state (EOS) as implemented in Multiflashsoftware from Infochem.

THE PC-SAFT EQUATION OF STATE

Thermodynamic phase behavior of fluid mixtures can bedescribed by perturbation theory. In this approach, the propertiesof a fluid are obtained by expanding about the same propertiesof a reference fluid. The statistical associating fluid theory(SAFT) equation of state was developed by Chapman et al.2,3

† Presented at the 7th International Conference on Petroleum PhaseBehavior and Fouling.

* Corresponding author. Mailing address: Department of ChemicalEngineering, Rice University, MS #362, PO Box 1892, Houston, Texas77251, USA. Tel.: +1-713-348-4900. Fax:+1-713-348-5478. E-mail:wgchap@rice.edu.

‡ Rice University.§ ChevronTexaco Energy Technology Co.

(1) Gonzalez, D. L.; Ting, P. D.; Hirasaki, G.; Chapman, W. G. Predictionof Asphaltene Instability under Gas Injection with the PC-SAFT Equationof State.Energy Fuels2005, 19, 1230-1234.

(2) Chapman, W. G.; Jackson, G.; Gubbins, K. E.Mol. Phys.1988, 65,1057-1079.

(3) Chapman, W. G.; Gubbins, K. E.; Jackson, G.; Radosz, M.Ind. Eng.Chem. Res.1990, 29, 1709-1721.

1231Energy & Fuels2007,21, 1231-1242

10.1021/ef060453a CCC: $37.00 © 2007 American Chemical SocietyPublished on Web 05/02/2007

by applying and extending Wertheim’s first-order perturbationtheory4,5 to chain molecules. In this theory, molecules aremodeled as chains of bonded spherical segments and theproperties of a fluid are obtained by expanding about the sameproperties of a reference fluid. Gross and Sadowski6 proposedthe perturbed chain modification (PC-SAFT) to account for theeffects of chain length on the segment dispersion energy, byextending the perturbation theory of Barker and Henderson7,8

to a hard chain reference. PC-SAFT employs a hard spherereference fluid described by the Mansoori-Carnahan-Starling-Leland equation of state.9 This version of SAFT properlypredicts the phase behavior of mixtures containing high mo-lecular weight fluids similar to the large asphaltene molecules.

PC-SAFT describes the residual Helmholtz free energy (Ares)of a mixture of associating fluid as

whereAseg, Achain, A0hs, A0

disp, Aassocare the segment, chain, hard-sphere, dispersion, and association contributions to the mixtureHelmholtz free energy. In eq 1,R is the gas constant andT istemperature.

The main assumption in this approach is that asphalteneassociates to form preaggregates and further association is notconsidered during precipitation. Therefore, asphaltene phasebehavior can be qualitatively explained in terms of Londondispersion interactions (contribution to the van der Waals forces)and polar interactions are assumed to have an insignificantcontribution. Aromatic ring compounds like asphaltenes arehighly polarizable; therefore, the polarizability determines theability of hydrocarbons to serve as a precipitant or as a solventfor asphaltenes. Because of this assumption, the association termin SAFT is not used in this asphaltene modeling work

The PC-SAFT EOS requires three parameters for eachnonassociating component. These parameters are the tempera-ture-independent diameter of each molecular segment (σ), thenumber of segments per molecule (m), and the segment-segment dispersion energy (ε/k).

The temperature-independent binary interaction parametersbetween components are estimated by adjusting binary vapor-liquid equilibria at the corresponding temperature for thecombination of pure components. For pseudocomponents, arepresentative component is selected. Generally, binary interac-tion parameters for asphaltenes and other components areassumed equal to those for aromatics and the same components.

PC-SAFT Thermodynamic Modeling.The asphaltene phasebehavior simulation procedure for a live oil starts with thedefinition of four pseudocomponents that represent the gasphase: nitrogen (N2), carbon dioxide (CO2), methane (CH4),and light pseudocomponents (hydrocarbons C2 and heavier). Thecharacterization is based on the compositional information forthe gas phase. The PC-SAFT EOS parameters for the purecomponents, N2, CO2, and methane, are available in theliterature.6 The average molecular weight of the light pseudocom-

ponent is used to estimate the corresponding PC-SAFT EOSparameters through correlations ofn-alkanes series. Gross andSadowski6 identified the three pure-component parametersrequired for nonassociating molecules for 20n-alkanes bycorrelating vapor pressures and liquid volumes. Equations 2 to4 present correlations generated from these parameters.

Three pseudocomponents represent the liquid phase: satu-rates, aromatics plus resins, and asphaltenes. The characteriza-tion of this phase is based on the liquid fluid compositionalinformation (for example, C30+) and SARA (saturates, aromatics,resins, and asphaltene) analysis. Above the C10 cut, theproportion of saturates, from SARA analysis, are consideredthe saturates pseudocomponent. The remaining fraction fromC10 to C29 corresponds to aromatics/resins. All asphaltenes arefound in the heaviest subfraction(s).

The PC-SAFT parameters for saturates and for aromatics/resins pseudocomponents are calculated from their averagemolecular weight. Saturates are treated asn-alkanes; therefore,PC-SAFT parameters are calculated using eqs 2-4. Thearomatics/resins pseudocomponent is linearly weighted by thearomaticity parameter between poly-nuclear-aromatic (PNA) andbenzene-derivative components, characterized by the correlationspresented in eqs 5-7 for PNA and 8-10 for benzene deriva-tives. These correlations are generated from parameters listedin the works of Gross and Sadowski6 and Ting10), and presentedin equations 5 to 7 for PNA and 8 to 10 for benzene derivatives.

The aromaticity parameter (γ) determines the aromatics/resinstendency to behave as PNA or benzene derivatives. To quantifythe degree of aromaticity,γ will take a value between one, forPNA, and zero, for benzene derivatives. The aromaticityparameter is tuned for the fluid to meet the experimental valuesof stock-tank-oil (STO) density, STO refractive index, andbubble point for live oils.

Monodisperse Asphaltene.In a first approach, asphaltene istreated as a monodisperse pseudocomponent. The PC-SAFTEOS parameters for a monodisperse asphaltene are fitted toprecipitation onset measurements based on ambient titrationsand/or depressurization measurements. In this work, the averagemolecular weight of 1700 g/mol is used to represent the averagemolecular weight for a preaggregate asphaltene. This value issimilar to values reported in the literature for asphaltenes. Forexample, Alboudwarej et al.11 reported an asphaltene monomer

(4) Wertheim, M. S.J. Stat. Phys.1986, 42, 459.(5) Wertheim, M. S.J. Stat. Phys.1986, 42, 477.(6) Gross, J.; Sadowski, G. Perturbed-Chain SAFT: An Equation of State

Based on a Perturbation Theory for Chain Molecules.Ind. Eng. Chem. Res.2001, 40, 1244-1260.

(7) Barker, J. A.; Henderson, D. J.J. Chem. Phys.1967, 47, 2856-2861.

(8) Barker, J. A.; Henderson, D. J.J. Chem. Phys.1967, 47, 4714-4721.

(9) Mansoori, G. A.; Carnahan, N. F.; Starling, K. E.; Leland, T. W.J.Chem. Phys.1971, 54, 1523.

(10) Ting, P. D. Thermodynamic Stability and Phase Behavior ofAsphaltenes in Oil and of Other Highly Asymmetric Mixtures. DoctoralThesis, Rice University, Houston, TX, 2003.

Ares

RT) Aseg

RT+ Achain

RT) m(A0

hs

RT+

A0disp

RT) + Achain

RT+ Aassoc

RT(1)

m ) 0.0253MW+ 0.9263 (2)

σ ) (0.1037MW+ 2.7985)1× 10-10/m (3)

ε/k ) 32.8 ln(MW)+ 80.398 (4)

m ) 0.0139MW+ 1.2988 (5)

σ ) (0.0597MW+ 4.2015)1× 10-10/m (6)

ε/k ) 119.4 ln(MW)-230.21 (7)

m ) 0.0208MW+ 0.9136 (8)

σ ) (0.0901MW+ 3.1847)1× 10-10/m (9)

ε/k ) 40.059 ln(MW)+ 101.18 (10)

1232 Energy & Fuels, Vol. 21, No. 3, 2007 Gonzalez et al.

molar mass of 1800 g/mol based on the vapor-pressureosmometry (VPO) technique.11

Polydisperse Asphaltene.Asphaltenes are a polydisperse classof compounds with resins as their lower molecular weightsubfraction. They are a continuum of aggregates (self-associatedasphaltenes) of increasing effective molar mass.11 Typical MWvalues using VPO are in the range of 800-3000 g/mol in goodsolvents (e.g., toluene, benzene).12

Comparisons between considering asphaltene as monodisperseor polydisperse are presented in Case 2.

Case 1: Effect of Oil-Based Mud Contamination onAsphaltene Stability

OBM used to increase borehole stability during the drillingprocess can contaminate near wellbore reservoir fluids. Drillingfluid can mix with crude oil either during drilling or during theflow back for sampling. The effect of these OBM filtrates inthe reservoir fluid on asphaltene stability is shown by the tracerof the solid deposition system (SDS) technique in Figure 1.

Fluids Properties.The development of the asphaltene modelis based on thePVT fluid information and the asphaltenecharacterization provided by Chevron-Texaco of two deepwaterreservoir fluids with different characteristics, fluids A and B.

Reservoir fluid A of 30.6°API gravity and a characteristicGOR of 1180 scf/sbl has a bubble point of 4085 psi at 188°F.The onset pressure measured using SDS technique was deter-mined to be 9900 psi at 188°F. The SARA content for thisfluid was measured as 64.9 wt % saturates, 16.3 wt % aromatics,16.3 wt % resins, and 12.6 wt %n-C5 insoluble or 3.7 wt %n-C7 insoluble of asphaltenes. These values indicate that thereservoir fluid sample is saturate in nature (saturates> 50%),but its asphaltene content is high enough that according to thede Boer criteria13 severe asphaltene problems would not be

expected. SARA values alone do not indicate the stability ofthe fluid. Gas composition also affects the asphaltene instabilityof a live oil. The reservoir fluid A chromatographic (GC) com-position of the gas and liquid phases is presented in Table 1.

Reservoir fluid B of 33.0°API gravity and a characteristicGOR of 1601 scf/sbl has a bubble point of 5850 psi at 178°F.The onset pressure measured using SDS technique was deter-mined to be 7650 psi at 178°F. Reservoir fluid B is originallycontaminated with OBM at a 2.6 wt % live oil basis which

(11) Alboudwarej, H.; Akbarzedeh, K.; Beck. J.; Svrcek, W. Y.;Yarranton, H. W. Regular Solution Model of Asphaltene Precipitation fromBitumen,AIChE J.2003, 49 (11), 2948-2956.

(12) Spiecker, P. M.; Gawrys, K. L.; Kilpatrick, P. K. Aggregation andSolubility Behavior of Asphaltenes and their sub-fractions.J. ColloidalInterface Sci.2003, 267, 178-193.

(13) de Boer, R. B.; Leerlooyer, K.; Eigner, M. R. P.; van Bergen, A.R. D. Screening of Crude Oils for Asphalt Precipitation: Theory, Practiceand the Selection of Inhibitors; SPE Production & Facilities, 1995.

(14) Ashcroft, S. J.; Clayton, A. D.; Shearn, R. B.J. Chem. Eng. Data1979, 24, 195.

(15) Richon, D.; Laugier S.; Renon, H.J. Chem. Eng. Data1991, 36,104.

(16) Brown, T. S.; Niesen, V. G.; Sloan, E. D.; Kidnay, A. J.Fluid PhaseEquilib. 1989, 53, 7.

(17) Stryjek, R.; Chappelear P. S.; Kobayashi, R.J. Chem. Eng. Data1974, 19, 334.

(18) Grauso, L.; Fredenslund, A.; Mollerup, J.Fluid Phase Equilib.1977,1, 13-26

(19) Azarnoosh, A.; McKetta, J. J.J. Chem. Eng. Data1963, 8, 494.(20) Richon, D.; Laugler, S.; Renon, H. J.Chem. Eng. Data1992, 37,

264-268.(21) Miller, P.; Dodge, B. F.Ind. Eng. Chem.1940,32, 434-438.(22) Bian, B.; Wang, Y.; Shi, J.; Zhao, E.; Lu, B. C.-Y.Fluid Phase

Equilib. 1993, 90, 177.(23) Morris, W. O.; Donohue, M. D.J. Chem. Eng. Data1985, 30, 259.(24) Robinson, D. B.; Ng, Heng-Joo.J. Chem. Eng. Data1978, 23, 325.(25) Katayam, T.; Ohgaki, K. J.Chem. Eng. Data1976, 21 (1).(26) Wichterle, I.; Kobayashi, R.J. Chem. Eng. Data1972, 17, 4.(27) Akers, W. W.; Burns, J. F.; Fairchild, W. R. Ind. Eng. Chem.1954,

46, 2531.(28) Reamer, H. H.; Sage B. H.; Lacey, W. N. Ind. Eng. Chem.1951,

43, 1436.(29) Lin, H. M; Sebastian, H. M.; Simnick, J. J.; Chao, K-C.J. Chem.

Eng. Data 1979, 24 (2).(30) Stryjek, R.; Chappelear, P. S.; Kobayashi, R.J. Chem. Eng. Data

1974, 19, 334.(31) Richon, D.; Laugier S.; Renon, H.J. Chem. Eng. Data1991, 36,

104.(32) Muhammad, M.; Joshi, N.; Creek, J.; McFadden, J. InEffect of Oil

Based Mud Contamination on LiVe Fluid Asphaltene Precipitation Pressure.Presented at the 5th International Conference on Petroleum Phase Behaviorand Fouling, Banff, Alberta, Canada, 2004; pp 13-17.

Figure 1. Experimental determination of OBM contamination effecton asphaltene precipitation onset using the SDS technique (Schlume-berger-Oilphase-DBR).

Table 1. Reservoir Fluid A Composition

Crude Oil and Gas Composition

overall

component liquid (wt %) gas (mol %) wt % mol %

N2 0.000 0.528 0.185 0.37CO2 0.000 0.510 0.122 0.383C1 0.000 71.325 9.435 51.731C2 0.000 10.436 2.588 7.569C3 0.000 7.44 2.705 5.396C4 0.330 4.754 2.540 3.844C5 0.848 2.696 2.276 2.775C6 1.699 1.282 2.259 2.305C7 2.424 0.434 2.282 2.003C8 3.263 0.157 2.736 2.107C9 3.426 0.036 2.756 1.89cyclics/aromatics 1.663 0.389 1.603 1.519C10 4.071 0.012 3.244 2.129C11 3.609 0.002 2.865 1.714C12 3.237 0.000 2.568 1.403C13 3.266 0.000 2.591 1.302C14 3.105 0.000 2.463 1.14C15 2.931 0.000 2.325 0.993C16 2.710 0.000 2.15 0.852C17 2.519 0.000 1.998 0.742C18 2.542 0.000 2.016 0.707C19 2.452 0.000 1.945 0.651C20 2.223 0.000 1.763 0.564C21 2.041 0.000 1.619 0.489C22 1.965 0.000 1.559 0.45C23 1.827 0.000 1.45 0.401C24 1.849 0.000 1.467 0.39C25 1.767 0.000 1.401 0.357C26 1.683 0.000 1.335 0.327C27 1.815 0.000 1.44 0.339C28 1.421 0.000 1.127 0.255C29 1.528 0.000 1.212 0.265C30+ 37.786 0.000 29.975 2.637MW 254 25.1

Asphaltene Instability with the SAFT EOS Energy & Fuels, Vol. 21, No. 3, 20071233

corresponds to a 3.6 wt % dead oil basis. The SARA contentfor this fluid was measured as 52.3 wt % saturates, 28.0 wt %aromatics, 11.82 wt % resins, and 8.3 wt %n-C7 insolubleasphaltenes. These values also indicate that the reservoir fluidsample is saturate in nature (saturates> 50%), but its asphaltenecontent is above the limit for a crude with asphaltene severeproblems (>1%).13 Again, SARA analysis is not a clearindication of the fluid stability. The composition of the reservoirfluid B is presented in Table 2.

An internal olefin was the base oil for the OBM fluid usedas drilling fluid in the field from which the crude oil samplewas obtained. The average molecular weight of this fluid was236 g/mol and its density was 0.782 g/cm3 at 74°F. The carbonnumber distribution of components in the filtrate sample usedas the contaminant in the depressurization experiments was deter-mined by gas chromatographic analysis as shown in Figure 2.

Fluid A Modeling. In the live oil simulation procedure, FluidA is treated as a mixture of eight components: four in the gasphase (N2, CO2, methane, and light pseudocomponent) and fourin the liquid phase (saturates, aromatics+ resins, asphaltenes,and olefins). The olefins pseudocomponent represents the OBMcontamination; therefore, its mole fraction value is zero for the

uncontaminated fluid. OBM can also be represented as anadditional saturates component; in this case, seven componentsrepresent the live fluid and the OBM is added to the saturatespseudocomponent proportionally to the amount of contaminationin the sample.

The amount and characteristic molecular weight of each ofthe components and pseudocomponents are defined usingSARA, GOR, and compositional information. The PC-SAFTparameters are calculated using the procedure described in thePC-SAFT thermodynamic modeling section presented above.The asphaltene PC-SAFT parameters were fitted to meet thetitration of the fluid A STO with a series ofn-alkanes (C7, C11,and C15) at 20°C and 1 atm measured by New Mexico Tech

Table 2. Reservoir Fluid B Composition

Crude Oil and Gas Composition

overall

component liquid (wt %) gas (mol %) wt % mol %

N2 0.000 0.045 0.123 0.31CO2 0.000 0.089 0.042 0.068C1 0.000 79.542 13.888 61.001C2 0.000 7.133 2.334 5.471C3 0.000 5.325 2.556 4.084C4 0.399 3.489 2.506 3.039C5 0.788 2.105 2.245 2.193C6 1.645 1.052 2.225 1.819C7 0.243 0.365 2.222 1.563C8 3.269 0.136 2.629 1.622C9 3.345 0.032 2.563 1.407C10 4.160 0.013 3.15 1.657C11 3.686 0.003 2.778 1.332C12 3.455 0.000 2.601 1.139C13 3.524 0.000 2.653 1.068C14 4.313 0.000 3.247 1.204C15 3.652 0.002 2.754 0.942C16 3.872 0.000 2.915 0.925C17 3.186 0.000 2.398 0.713C18 3.258 0.000 2.452 0.688C19 2.830 0.000 2.13 0.571C20 2.703 0.000 2.034 0.521C21 2.328 0.000 1.752 0.424C22+ 45.555 0.000 34.291 5.093MW 227.6 22.7

Figure 2. OBM filtrate carbon number distribution.

Table 3. PC-SAFT Characterization of Precipitants and STO ofReservoir Fluid A

precipitant MW m σ (Å) ε/k (K)

C7 100.20 3.4831 3.8049 238.40C11 156.00 4.9082 3.8893 248.82C15 212.42 6.2855 3.9531 254.14

STO STOXmole MW m σ (Å) ε/k (K)

saturates 0.70452 233.62 6.837 3.953 259.28aromatics+ resins 0.28623 256.33 6.660 3.786 290.76asphaltenes 0.00926 1700 29.500 4.334 395.00

Table 4. Binary Interaction Parameters (kij) for STO-Fluid A andPrecipitants

kij saturatesa A + Rb asphaltenes

C7 0.00 0.0065 0.00C11 0.00 0.0070 0.00C15 0.00 0.0000 0.00saturates 0.00 0.0070 0.00arom+ resins 0.0000 0.00asphaltenes 0.00

a Saturates are represented by decane or dodecane;ksaturates-n-alkanes)0.00. b Aromatic + resins are represented by toluene or benzene;kA+R-n-alkanes.14,15

Figure 3. Precipitant volumetric fraction (φppt) at the onset ofasphaltene precipitation for fluid A.

Table 5. PC-SAFT Characterization of Live Fluid A (GOR ) 1180scf/stb)

total gas Xmole MW m σ (Å) ε/k (K)

N2 0.00381 28.01 1.2053 3.3130 90.96CO2 0.00368 44.01 2.0729 2.7852 169.21methane 0.5149 16.04 1.0000 3.7039 150.03light 0.19959 47.91 2.1385 3.6320 207.31

total liquid

saturates 0.19589 233.62 6.837 3.953 259.28aromatics+ resins 0.07959 256.33 6.660 3.786 290.76asphaltenes 0.00257 1700 29.500 4.334 395.00OBM - olefinic 0.0000 238.00 6.967 3.956 259.99

1234 Energy & Fuels, Vol. 21, No. 3, 2007 Gonzalez et al.

(NMT). Table 3 presents STO fluid A characterization for thetitration experiments.

Titration measurements and simulation results are presentedin Figure 3 as the volumetric fraction of precipitant (φppt) atthe onset of asphaltene instability vs carbon number. Thetemperature-independent binary interaction parameters (kij) usedin these calculations are shown in Table 4.

Table 5 summarizes composition, molecular weight, andparameter values for each of the live fluid A components witha GOR value of 1180 scf/bbl. Thekij parameters are presentedin Table 6.

Comparison between the PC-SAFT model fluid propertiesand experimental results are presented in Table 7.

Calculations for fluid A consider the OBM contaminant asan independent pseudocomponent with either olefin character-istics (MW and PC-SAFT parameters correlations for olefins)or as a saturate pseudocomponent. In both cases, the predictedasphaltene precipitation onset and bubble point pressure de-creases as the OBM contamination increases. Figure 4 comparessimulation results to experimental measurements.

Fluid B Modeling.The PC-SAFT asphaltene parameters forfluid B are tuned to meet contaminated reservoir fluid density,bubble point, and asphaltene precipitation onset at high-pressureand high-temperature conditions (see Table 8).

The PC-SAFT EOS parameters for the other components areobtained by correlations with molecular weight. In the simulationof Fluid B, seven pseudocomponents represent the live fluid.OBM is assumed to be composed by saturates, and it is added

to the saturates pseudocomponent proportionally to the amountof contamination in the sample. Table 9 shows the correspondingcompositions, molecular weights, and PC-SAFT parameters thatbest fit the above properties.

Thekij parameters have the same values as presented in Table6 except for the corresponding asphaltene parameters adjustedto tune the measured onset. Since the OBM composition isknown, the OBM free fluid composition is calculated math-ematically by subtracting the corresponding fraction.

The OBM free fluid characterization is presented in Table10. Asphaltene parameters and the characteristic aromaticity arekept the same, but the global composition and MWs for thesaturates pseudocomponent are different. Note that the GORvalue for the uncontaminated fluid is 1664 scf/bbl instead of1601 scf/bbl.

The calculated properties of the uncontaminated fluid at 1664scf/bbl are given in Table 11.

Figure 5 shows a decrease in the asphaltene onset pressureand bubble point pressure with contamination calculated using

Table 6. Binary Interaction Parameters (kij) for Reservoir Fluid A

kij N2 CO2 CH4 light saturates A+ R asphaltenes

N2 0.000 0.00016 0.03017 0.06018 0.12019 0.11020,21 0.110CO2 0.000 0.05022 0.100 0.130 0.10023-25 0.100CH4 0.000 0.00026,27 0.03028 0.02929 0.029light 0.000 0.01030 0.01031 0.010saturates 0.000 0.00731 0.0024A + R 0.000 0.000asphaltenes 0.000

Table 7. Fluid A Properties at 1180 scf/bbl

experimental calculated

Ponset(psia) 9900 9949Pb (psia),T ) 188°F 4050 3964density at 188.6°F & 14 500 psia (g/cm3) 0.718 0.736liquid (STO) density (g/cm3) 0.8676 0.8563

Figure 4. OBM contamination effect on the asphaltene phase behavior of fluid A.

Table 8. Contaminated Reservoir Fluid B Properties at 1601 scf/bbl

experimental calculated

fluid density (g/cm3) at 186°Fand 14 500 psia

0.700 0.704

Psatat 178°F (psia) 5850 5413Ponsetat 178°F (psia) 7650 7609

Table 9. Contaminated Reservoir Fluid B Composition andPC-SAFT Parameters at 1601 scf/bbl

Xmole MWn Xmass m σ (Å) ε/k (K)

N2 0.00308 28.01 0.0012 1.2053 3.313 90.96CO2/H2S 0.00068 41.80 0.0004 2.0729 2.785 169.21methane 0.60543 16.04 0.1347 1.0000 3.704 150.03light 0.15195 49.07 0.1035 2.1677 3.638 208.10saturates 0.14781 200.95 0.4121 6.010 3.933 254.34arom+ resins 0.08838 232.38 0.2849 6.149 3.780 286.14asphaltenes 0.00267 1700.00 0.0631 29.50 4.390 388.00

Asphaltene Instability with the SAFT EOS Energy & Fuels, Vol. 21, No. 3, 20071235

PC-SAFT EOS. Once this fluid is freed of 2.6% OBMcontamination, the onset pressure will increase about 415 psiat 220°F and 512 psi at 120°F.

Figure 6 shows the decrease of the asphaltene precipitationonset when successive amounts of OBM are added to an originalhigh asphaltene content oil sample.

The saturate like behavior assumptions for all of thecomponents in the OBM define the limits of expected behavior.

Note that GOR also decreases by the OBM addition. Theasphaltene stability improvement effect follows a similar trendto that in the case that GOR in the original oil/gas mixture woulddecrease. Both, the onset and the saturation pressure curvesestimated by SAFT, closely follow the experimental findings.

Case 2: Asphaltene Precipitation Prediction for HighGas-Oil Ratio Wells

Kokal et al.33 presented experimental information on asphalt-ene precipitation observed in a number of high GOR wells inthe North Ghawar-Arab D reservoir in Saudi Arabia. Even

Figure 5. Asphaltene precipitation behavior of reservoir fluid B calculated with the PC-SAFT EOS.

Figure 6. PC-SAFT simulation of asphaltene onset and bubble point pressures as a function of OBM contamination of reservoir fluid B. Experimentaldata from ref 32.

Table 10. OBM Free Fluid Pseudocomponents and PC-SAFTParameters at 1664 scf/bbl

Xmole MWn m σ (Å) ε/k (K)

N2 0.00311 28.01 1.2053 3.313 90.96CO2/H2S 0.00068 41.80 2.0729 2.785 169.21methane 0.61044 16.04 1.0000 3.704 150.03light 0.15320 49.07 2.1677 3.638 208.10saturates 0.14086 198.80 5.956 3.931 253.99arom+ resins 0.08902 232.09 6.143 3.780 286.13asphaltenes 0.00270 1700.00 29.50 4.390 388.00

Table 11. OBM Free Contaminated Sample Calculated Properties

fluid density (g/cm3) at 186°F and 14 500 psia 0.703Psatat 178°F (psia) 5534Ponsetat 178°F (psia) 8023

1236 Energy & Fuels, Vol. 21, No. 3, 2007 Gonzalez et al.

though the oil reservoir was undersaturated, two small gas capsare present as a result of gas injection performed about 40 yearsago. New development wells drilled recently to produce oil andgas from the gas-cap areas have experienced asphaltene deposi-tion. Experimental results indicate that the crude does not havea natural tendency to precipitate when pressure is reduced;however, asphaltene precipitation occurs after a certain amountof gas is added to the crude. Even though the onset takes placeat relatively low GOR values, asphaltene precipitation anddeposition increase with increasing GORs.

Fluid Properties. A reservoir fluid (fluid C in this work) of32.03 °API gravity with a characteristic GOR of 580 scf/sblhas a bubble point of 1900 psi at 215°F and is combined witha synthetic gas with a similar composition to that of the actualinjected gas. Fluid compositional information and reservoirproperties are presented in Table 12.

The SARA content of the black oil reservoir fluid (saturates44.14 wt %, aromatics 40.13 wt %, resins 12.79 wt %, andasphaltenes 2.94 wt %) indicates that the reservoir fluid sampleis aromatic in nature (aromatics+ resins> 50%) and that theasphaltene content is too high for the crude to have severeasphaltene problems (>1%).13 SARA values show a relativelystable fluid. The addition of gas changes composition byincreasing the amount of light gas components, like methane,which is a strong asphaltene precipitant. All these variables thatdrive asphaltene precipitation need to be integrated in a singlemodel.

Asphaltene Experimental Characterization.The asphalteneprecipitation onset was determined by isothermal depressuriza-tion of fluid samples. Techniques used to identify asphalteneonset values were the following:

- SDS technique- high-pressure filtration to quantify asphaltene bulk deposi-

tion amount.Using the SDS technique, results of gas injection are plotted

in terms of GOR in Figure 7.Experimental results indicate that the onset of asphaltene

precipitation at 215°F and 3000 psia will occur at a GOR valueof approximately 625 scf/stb. This suggests that the crude isnearly saturated with asphaltenes and a small amount of gas isenough to start the precipitation.

A depressurization test was also conducted in anotherexperiment in which 7 cm3 of gas was added to 30 cm3 of oil.The light transmittance result is shown in Figure 8 as an insetin the P-T diagram. The crude oil and gas mixture was firstpressurized to more than 6000 psi. During depressurization, theonset of asphaltene precipitation started at∼4500 psia. Thebubble was observed at∼3000 psia.

Monodisperse Asphaltene.The PC-SAFT EOS parametersfor each of the components are calculated from fluid compo-sitional information as describe above in the PC-SAFT Ther-modynamic Modeling Section. Table 13 summarizes compo-sition, molecular weight, and parameter values for each componentand pseudocomponent of the live sample. Monodisperse as-phaltene parameters were tuned to meet experimental asphalteneprecipitation onset measurements. This specific crude oil has adensity of 32.03°API gravity, similar to the crude oil density(33.6°API) characterized by Ting;10 therefore, initial asphalteneparameter values are adjusted from the original values ofm )29.5,σ ) 4.3 Å, andε/k ) 395 K. The effects on variation inPC-SAFT parameters indicate that the solubility parameter issensitive to changes in the segment propertiesε/k and σ. Adecrease in the segment energy will decrease the solubilityparameter, and a decrease in the segment diameter will increasethe solubility parameter; therefore, the chain length (m) and thesegment diameter (σ) which represent the volume of themolecule are kept constant, and only the segment energy (ε/k)parameter is modified to meet the asphaltene onset experimentaldata. The aromaticity value for this crude oil was determinedto be 0.06 which indicates a close behavior to benzene derivativecompounds. The binary interaction parameters used in thesesimulations are the same as the values presented in Table 6with this case, all asphaltene binary parameters are equal to thearomatic/resins pseudocomponent.

The PC-SAFT model calculates the properties shown in Table15 and the thermodynamic behavior shown in Figure 9.

The amount of asphaltene precipitated due to gas addition iscalculated as the asphaltene percentage that separates from crudeoil to the asphaltene-rich phase. Figure 10 shows the results at3000 psia and 215oF. PC-SAFT predicts that the amount ofasphaltenes precipitated will start at about 700 scf/bbl (additionof ∼10% gas) and that it will increase up to 50% as the GORreaches a value of∼1000 scf/bbl.

Polydisperse Asphaltene.The method used to obtain theSAFT parameters for polydisperse asphaltenes is similar to themonodisperse SAFT asphaltene characterization procedure.Ting10 presented a PC-SAFT EOS characterization for Lagraveoil asphaltene subfractions based on titration experimentsperformed by Wang34 using excessn-pentane,n-heptane, and

(33) Kokal, S.; Al-Ghamdi, A.; Krinis, D.Asphaltene Precipitation inHigh Gas-Oil-Ratio Wells; SPE 81567, Society of Petroleum Engineers:Richardson, TX, 2003; p. 1-11.

Table 12. Reservoir Fluid C Summary33

Reservoir Conditionspressure (psia) >3000temperature (˚F) 215depth (MD [ft]) ∼6900

Compositional Analysis of the Fluids (mol %)

injected gas

reservoir fluid actual experiment

N2 0.14 0.41 0.34CO2 5.89 12.30 12.62H2S 1.82 1.91 2.49C1 24.01 56.00 56.00C2 9.79 17.45 16.23C3 7.49 8.20 8.39C4 4.92 2.64 2.86C5 3.95 0.84 0.83C6 3.14 0.25 0.25C7+ 38.85 0.00 0.01C7+ molecular weight 240C7+ specific gravity 0.8652MW 26.53 (calc)

Figure 7. Onset of asphaltene precipitation during addition of gas toa crude oil.33

Asphaltene Instability with the SAFT EOS Energy & Fuels, Vol. 21, No. 3, 20071237

n-pentadecane precipitants. Polydisperse asphaltene was repre-sented in this work as four pseudocomponents in SAFT: then-C15+, then-C7-15, then-C5-7, and then-C3-5n-alkaneinsolublesubfraction which corresponds to the resins subfraction. TheSAFT parameters were fit for each subfraction to reproduce the

experimental data on the minimum volume fraction precipitantneeded to induce asphaltene instability in the system asphaltene/toluene/precipitant at ambient conditions. The fitted SAFTasphaltene parameters and the corresponding solubility param-eter (δ) and density (F) in this previous work are listed in Table15.

(34) Wang, J. X., Predicting Asphaltene Flocculation in Crude Oils. Ph.D.Thesis, New Mexico Institute of Mining & Technology, 2000.

(35) Vazquez, D.; Mansoori, G. A. Analysis of Heavy Organic Deposits.J. Pet. Sci. Eng. 26(1-4), 46-49.

Figure 8. Onset of asphaltene precipitation vs gas added. Experimental data is taken from the work of Kokal et al.33

Figure 9. Asphaltene boundaries for reservoir fluid C considering monodisperse asphaltene.

Table 13. PC-SAFT Characterization for Live Fluid C at 580 scf/stb

total gas Xmole MWn m σ (Å) ε/k (K)

N2 0.00185 28.01 1.2053 3.3130 90.96CO2/H2S 0.08227 44.01 2.0729 2.7852 169.21methane 0.30489 16.04 1.0000 3.7039 150.03light 0.15549 38.71 1.9057 3.5750 200.32

total liquid

saturates 0.19694 250.00 7.251 3.961 261.50A + R 0.25664 230.00 6.419 3.75 258.98asphaltene 0.001929 1700 29.5 4.30 392.3

Table 14. Reservoir Fluid C Sample Properties at 580 scg/bbl

experimental calculated

Ponset(psia), 620.5 scf/bbl 2229 no onsetPonset(psia), 890 scf/bbl 4588 4588Pb (psia),T ) 215°F, 552 scf/bbl 1852 2119Pb (psia),T ) 215°F, 898 scf/bbl 3032 3029liquid (STO) density (g/cm3) 0.865 (32.03°API) 0.8707

Table 15. SAFT Parameters for Asphaltene Subfractions IncludingResins10

asph subfraction MW m σ (Å) ε/k (K) δ (MPa0.5) F (g/cm3)

n-C15+ 2500 54 4.00 350.5 22.17 1.150n-C7-15 1852 40 4.00 340.0 21.52 1.137n-C5-7 1806 39 4.00 335.0 21.25 1.133resin 556 12 4.00 330.0 20.41 1.103

1238 Energy & Fuels, Vol. 21, No. 3, 2007 Gonzalez et al.

Live oil with polydisperse asphaltene is simulated in this workunder two different options:

(1) polydisperse asphaltene that includes three asphaltenesubfractions,n-C15+, n-C7-15 andn-C5-7 with resins integratedinto the aromatic/resins pseudocomponent

(2) polydisperse asphaltene with four asphaltene subfrac-tions including then-C3-5n-alkane insoluble subfraction orresins.

Option 1: Polydisperse Asphaltene with Three AsphalteneSubfractions.In this option, live oil components and pseudo-components are kept as defined for the monodisperse case(Table 13) except for the asphaltene portion. The asphaltenecomponent is divided into three subfractions that representn-C15+, n-C7-15, and n-C5-7 asphaltene cuts. Contrary to thecase reported by Ting,10 no experimental data is available inthis work to determine the mass distribution of the asphaltenesubfractions; therefore, similar proportions will be assumed(Figure 11).

Typical asphaltene SAFT parameters are better representedby the benzene-derivatives correlations; therefore, in this work,asphaltene parameters (m, σ, andε/k) for each subfraction arecalculated from eqs 8-10. The required molecular weightdistribution input for these equations is the only adjustableparameter used to tune the experimental onset data.

Each asphaltene subfraction should meet the following criteriaat 1 atm and 60°F:

(1) n-C15+: insoluble in pentadecane.(2) n-C7-15: insoluble in heptane and soluble in pendadecane.(3) n-C5-7: insoluble in pentane and soluble in heptane.(4) Resins: insoluble in propane (tested at 10 atm) and soluble

in n-pentane (option 2).All of the fractions must be soluble in toluene.Table 16 presents a set of asphaltene parameters tuned to

the asphaltene precipitation onset experimental data that meetsthe previous criteria. The asphaltene average molecular weightis 1539 g/mol. Binary interaction parameters between asphaltenesubfractions are set to zero.

The asphaltene molecular weight distribution proposed in thiswork is presented in Figure 12.

The asphaltene precipitation envelope and amount of pre-cipitated asphaltene as a function of the amount of gas addedis presented in Figures 13 and 14, respectively.

Option 2: Polydisperse Asphaltene with Four AsphalteneSubfractions Including Resins.SAFT simulations as proposedin this option require the redefinition of the crude oil liquid-phase pseudocomponents. Resins are eliminated from thearomatics/resins pseudocomponent and included as subfractionof the polydisperse asphaltene. A molecular weight value of

Figure 10. Asphaltene precipitated amount for reservoir fluid C: monodisperse asphaltene.

Figure 11. Mass distribution of asphaltene subfractions.10,35

Table 16. PC-SAFT Parameters for the Various AsphalteneSubfractions

asph subfraction MW wt % m σ (Å) ε/k (K)

n-C15+ 1850 43.0 39.4 4.31 402.5n-C7-15 1510 22.5 32.3 4.31 394.4n-C5-7 1170 34.5 25.2 4.30 369.0

Asphaltene Instability with the SAFT EOS Energy & Fuels, Vol. 21, No. 3, 20071239

800 g/mol for resins is supported by literature values.36,37 Thenew liquid-phase characterization of the live oil sample at 580scf/bbl is shown in Table 17; the gas-phase characterization iskept invariable.

The amount of precipitated asphaltene including resins as afunction of the amount of gas added is presented in Figure 15.

Simulation results show a higher asphaltene precipitated totalamount for the polydisperse case. An analysis of the massdistribution of the asphaltene subfractions in the precipitatedphase shows that the largest asphaltenes will precipitate first,

followed by the precipitation of smaller asphaltenes. As seenin the figures, SAFT is able to describe the change in magnitudein the amount of asphaltene that precipitates depending on thetype of n-alkane precipitant.

Conclusions

The following conclusions can be drawn from the presentinvestigation:

• The PC-SAFT EOS model showed a decreased in theasphaltene precipitation onset and bubble point pressure as theOBM contamination increases.

• The decrease in asphaltene precipitation onset is caused bya reduction in GOR as a result of the addition of OBM.

• We demonstrate that the effect of OBM contamination onasphaltene stability pressure can be accurately estimated.

(36) Peramanu, S.; Pruden, B. B.; Rahimi, P. Molecular Weight andSpecific Gravity Distributions for Athabasca and Cold Lake Bitumens andTheir Saturate, Aromatic, Resin and Asphaltene Fractions.Ind. Eng. Chem.Res.1999, 38, 3121.

(37) Speight, J. G.The Chemistry and Technology of Petroleum; MarcelDekker: New York, 1999.

Figure 12. Asphaltene molecular weight distribution.

Figure 13. Asphaltene phase envelope with resins in the aromatic/resins pseudocomponent.

1240 Energy & Fuels, Vol. 21, No. 3, 2007 Gonzalez et al.

Therefore, actual reservoir conditions can be predicted basedon laboratory samples contaminated with OBM.

• The asphaltene precipitation tendencies caused by alterationin the reservoir fluid composition during commingle with gascan be predicted, and proper measurements can be taken.

• A polydisperse asphaltene was represented in SAFT withfour pseudocomponents: then-C3-5 (the resins), then-C5-7,the n-C7-15, and then-C15+ subfractions. Using an extensionof the monodisperse SAFT asphaltene parameter fitting proce-dure, we were able to assign a set of SAFT parameters torepresent each of the four subfractions.

• An analysis of the mass distribution of the asphaltenesubfractions in the precipitated phase showed that the largest

asphaltenes would precipitate first, followed by the precipitationof smaller asphaltenes.

Figure 14. Amount of precipitated asphaltene subfractions (no resins as asphaltene subfraction).

Figure 15. Amount of precipitated asphaltene subfractions (resins as asphaltene subfraction).

Table 17. PC-SAFT Characterization of the Live Sample at 580scf/bbl

Xmole MW m σ (Å) ε/k (K)

N2 0.0018 28.01 1.2053 3.3130 90.96CO2/H2S 0.0823 44.01 2.0729 2.7852 169.21methane 0.3049 16.04 1.0000 3.7039 150.03light 0.1555 38.71 1.9057 3.5750 200.32saturates 0.2230 250.00 7.251 3.961 261.50aromatics 0.2213 220.00 6.169 3.75 259.32n-C15+ asphaltene 0.000336 1950 41.5 4.31 404.7n-C7-15 asphaltene 0.000218 1610 34.4 4.31 397.0n-C5-7 asphaltene 0.000415 1310 28.2 4.30 388.7resins 0.009236 800 17.6 4.15 369.0

Asphaltene Instability with the SAFT EOS Energy & Fuels, Vol. 21, No. 3, 20071241

• The live oil model using the PC-SAFT equation of stateproperly predicts the asphaltene phase behavior under thesecompositional changes. The PC-SAFT equation of state modelis a commercially available, proven tool.

Acknowledgment. The authors thank DeepStar, Consortium onProcesses in Porous Media at Rice University, and the Departmentof Energy for their financial and technical support.

EF060453A

1242 Energy & Fuels, Vol. 21, No. 3, 2007 Gonzalez et al.