Modeling of Asphaltene Precipitation Due to Changes in Composition Using the Perturbed Chain Statistical Associating Fluid Theory Equation of State

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1 Energy & Fuels 2007, 21, Modeling of Asphaltene Precipitation Due to Changes in Composition 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 Energy Technology Co., Houston, Texas ReceiVed September 6, ReVised Manuscript ReceiVed March 26, 2007 Asphaltene precipitation and deposition adversely affect production assurance and are key risk factors in assessing difficult environments such as deepwater. Deposition in the near well bore regions and production tubulars implies high intervention and remediation costs. Prediction of asphaltene precipitation onset represents a challenge for the flow assurance area. The applicability of the PC-SAFT equation of state model to predict asphaltene onset of the precipitation in live oils is demonstrated by studying representative examples from field experiences with asphaltene problems during production. These examples not only validate the proposed model but also confirm the theory that asphaltene phase behavior can be explained based only on molecular size and van der Waals interactions. The PC-SAFT equation of state estimates also properties such as densities and 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 as part of the equilibrium calculations. This paper presents experimental observations and simulation results at reservoir conditions using the PC-SAFT equation of state on the effect of compositional changes in live oils caused by two common processes in the oil industry: oil-based-mud (OBM) contamination and reinjection of associated gas. In the first case, the downhole oil samples can be contaminated with OBM, causing laboratory measurements of the bubble point and asphaltene precipitation to be different from the reservoir fluid. In the second case, the reinjection of gas into the field increases the gas-oil-ratio (GOR) of the oil. The addition of gas into the oil can cause asphaltene precipitation and deposition due to the increase of light components that reduces asphaltene solubility. Asphaltenes in this example are treated as both monodisperse and polydisperse pseudocomponents. 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 including pressure, temperature, and composition of the fluid. The effect of composition and pressure on asphaltene precipitation is generally stronger than the effect of temperature. Changes in composition arise in the presence of oil-based muds (OBMs). Significant overbalance pressure during the drilling process can result in the mud filtrate invasion into the formation and mix with the reservoir fluid. Mud filtrate can significantly modify the composition of the near wellbore crude. Phase behavior measurements performed on reservoir fluid samples are affected by OBM contamination resulting in wrong data interpretation. Both the bubble point and the asphaltene precipitation onset can be affected by contamination of the oil with drilling fluids. Changes in composition also occur during gas injection processes employed for both enhanced oil recovery (EOR) in the injection wells and for gas lift in the wellbore. The gas can Presented at the 7th International Conference on Petroleum Phase Behavior and Fouling. * Corresponding author. Mailing address: Department of Chemical Engineering, Rice University, MS #362, PO Box 1892, Houston, Texas 77251, USA. Tel.: Fax: wgchap@rice.edu. Rice University. ChevronTexaco Energy Technology Co. dissolve into the crude oil and decrease asphaltene solubility. 1 The miscible gas also decreases the density and viscosity so that the crude oil will flow more readily. The effect of considering asphaltenes as monodisperse or polydisperse pseudocomponent will be analyzed in this example. The objective of this paper is to present experimental observations and simulation results at reservoir conditions on the effect of compositional changes in live oils that may result in either asphaltene precipitation or solubilization using the PC- SAFT equation of state (EOS) as implemented in Multiflash software from Infochem. THE PC-SAFT EQUATION OF STATE Thermodynamic phase behavior of fluid mixtures can be described by perturbation theory. In this approach, the properties of a fluid are obtained by expanding about the same properties of a reference fluid. The statistical associating fluid theory (SAFT) equation of state was developed by Chapman et al. 2,3 (1) Gonzalez, D. L.; Ting, P. D.; Hirasaki, G.; Chapman, W. G. Prediction of Asphaltene Instability under Gas Injection with the PC-SAFT Equation of State. Energy Fuels 2005, 19, (2) Chapman, W. G.; Jackson, G.; Gubbins, K. E. Mol. Phys. 1988, 65, (3) Chapman, W. G.; Gubbins, K. E.; Jackson, G.; Radosz, M. Ind. Eng. Chem. Res. 1990, 29, /ef060453a CCC: $ American Chemical Society Published on Web 05/02/2007

2 1232 Energy & Fuels, Vol. 21, No. 3, 2007 Gonzalez et al. by applying and extending Wertheim s first-order perturbation theory 4,5 to chain molecules. In this theory, molecules are modeled as chains of bonded spherical segments and the properties of a fluid are obtained by expanding about the same properties of a reference fluid. Gross and Sadowski 6 proposed the perturbed chain modification (PC-SAFT) to account for the effects of chain length on the segment dispersion energy, by extending the perturbation theory of Barker and Henderson 7,8 to a hard chain reference. PC-SAFT employs a hard sphere reference fluid described by the Mansoori-Carnahan-Starling- Leland equation of state. 9 This version of SAFT properly predicts the phase behavior of mixtures containing high molecular weight fluids similar to the large asphaltene molecules. PC-SAFT describes the residual Helmholtz free energy (A res ) of a mixture of associating fluid as A res RT ) Aseg RT + Achain RT ( ) m A hs 0 RT + A disp 0 RT ) + Achain RT + Aassoc RT (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, (7) Barker, J. A.; Henderson, D. J. J. Chem. Phys. 1967, 47, (8) Barker, J. A.; Henderson, D. J. J. Chem. Phys. 1967, 47, (9) Mansoori, G. A.; Carnahan, N. F.; Starling, K. E.; Leland, T. W. J. Chem. Phys. 1971, 54, (1) where A seg, A chain, A 0 hs, A 0 disp, A assoc are the segment, chain, hardsphere, dispersion, and association contributions to the mixture Helmholtz free energy. In eq 1, R is the gas constant and T is temperature. The main assumption in this approach is that asphaltene associates to form preaggregates and further association is not considered during precipitation. Therefore, asphaltene phase behavior can be qualitatively explained in terms of London dispersion interactions (contribution to the van der Waals forces) and polar interactions are assumed to have an insignificant contribution. Aromatic ring compounds like asphaltenes are highly polarizable; therefore, the polarizability determines the ability of hydrocarbons to serve as a precipitant or as a solvent for asphaltenes. Because of this assumption, the association term in SAFT is not used in this asphaltene modeling work The PC-SAFT EOS requires three parameters for each nonassociating component. These parameters are the temperature-independent diameter of each molecular segment (σ), the number of segments per molecule (m), and the segmentsegment dispersion energy (ɛ/k). The temperature-independent binary interaction parameters between components are estimated by adjusting binary vaporliquid equilibria at the corresponding temperature for the combination of pure components. For pseudocomponents, a representative component is selected. Generally, binary interaction parameters for asphaltenes and other components are assumed equal to those for aromatics and the same components. PC-SAFT Thermodynamic Modeling. The asphaltene phase behavior simulation procedure for a live oil starts with the definition of four pseudocomponents that represent the gas phase: nitrogen (N 2 ), carbon dioxide (CO 2 ), methane (CH 4 ), and light pseudocomponents (hydrocarbons C 2 and heavier). The characterization is based on the compositional information for the gas phase. The PC-SAFT EOS parameters for the pure components, N 2, CO 2, and methane, are available in the literature. 6 The average molecular weight of the light pseudocomponent is used to estimate the corresponding PC-SAFT EOS parameters through correlations of n-alkanes series. Gross and Sadowski 6 identified the three pure-component parameters required for nonassociating molecules for 20 n-alkanes by correlating vapor pressures and liquid volumes. Equations 2 to 4 present correlations generated from these parameters. m ) MW (2) σ ) (0.1037MW ) /m (3) ɛ/k ) 32.8 ln(mw) (4) Three pseudocomponents represent the liquid phase: saturates, aromatics plus resins, and asphaltenes. The characterization of this phase is based on the liquid fluid compositional information (for example, C 30+ ) and SARA (saturates, aromatics, resins, and asphaltene) analysis. Above the C 10 cut, the proportion of saturates, from SARA analysis, are considered the saturates pseudocomponent. The remaining fraction from C 10 to C 29 corresponds to aromatics/resins. All asphaltenes are found in the heaviest subfraction(s). The PC-SAFT parameters for saturates and for aromatics/ resins pseudocomponents are calculated from their average molecular weight. Saturates are treated as n-alkanes; therefore, PC-SAFT parameters are calculated using eqs 2-4. The aromatics/resins pseudocomponent is linearly weighted by the aromaticity parameter between poly-nuclear-aromatic (PNA) and benzene-derivative components, characterized by the correlations presented in eqs 5-7 for PNA and 8-10 for benzene derivatives. These correlations are generated from parameters listed in the works of Gross and Sadowski 6 and Ting 10 ), and presented in equations 5 to 7 for PNA and 8 to 10 for benzene derivatives. m ) MW (5) σ ) (0.0597MW ) /m (6) ɛ/k ) ln(mw) (7) m ) MW (8) σ ) (0.0901MW ) /m (9) ɛ/k ) ln(mw) (10) The aromaticity parameter (γ) determines the aromatics/resins tendency to behave as PNA or benzene derivatives. To quantify the degree of aromaticity, γ will take a value between one, for PNA, and zero, for benzene derivatives. The aromaticity parameter is tuned for the fluid to meet the experimental values of stock-tank-oil (STO) density, STO refractive index, and bubble point for live oils. Monodisperse Asphaltene. In a first approach, asphaltene is treated as a monodisperse pseudocomponent. The PC-SAFT EOS parameters for a monodisperse asphaltene are fitted to precipitation onset measurements based on ambient titrations and/or depressurization measurements. In this work, the average molecular weight of 1700 g/mol is used to represent the average molecular weight for a preaggregate asphaltene. This value is similar to values reported in the literature for asphaltenes. For example, Alboudwarej et al. 11 reported an asphaltene monomer (10) Ting, P. D. Thermodynamic Stability and Phase Behavior of Asphaltenes in Oil and of Other Highly Asymmetric Mixtures. Doctoral Thesis, Rice University, Houston, TX, 2003.

3 Asphaltene Instability with the SAFT EOS Energy & Fuels, Vol. 21, No. 3, Figure 1. Experimental determination of OBM contamination effect on asphaltene precipitation onset using the SDS technique (Schlumeberger-Oilphase-DBR). molar mass of 1800 g/mol based on the vapor-pressure osmometry (VPO) technique. 11 Polydisperse Asphaltene. Asphaltenes are a polydisperse class of compounds with resins as their lower molecular weight subfraction. They are a continuum of aggregates (self-associated asphaltenes) of increasing effective molar mass. 11 Typical MW values using VPO are in the range of g/mol in good solvents (e.g., toluene, benzene). 12 Comparisons between considering asphaltene as monodisperse or polydisperse are presented in Case 2. Case 1: Effect of Oil-Based Mud Contamination on Asphaltene Stability OBM used to increase borehole stability during the drilling process can contaminate near wellbore reservoir fluids. Drilling fluid can mix with crude oil either during drilling or during the flow back for sampling. The effect of these OBM filtrates in the reservoir fluid on asphaltene stability is shown by the tracer of the solid deposition system (SDS) technique in Figure 1. Fluids Properties. The development of the asphaltene model is based on the PVT fluid information and the asphaltene characterization provided by Chevron-Texaco of two deepwater reservoir fluids with different characteristics, fluids A and B. Reservoir fluid A of 30.6 API gravity and a characteristic GOR of 1180 scf/sbl has a bubble point of 4085 psi at 188 F. The onset pressure measured using SDS technique was determined to be 9900 psi at 188 F. The SARA content for this fluid was measured as 64.9 wt % saturates, 16.3 wt % aromatics, 16.3 wt % resins, and 12.6 wt % n-c 5 insoluble or 3.7 wt % n-c 7 insoluble of asphaltenes. These values indicate that the reservoir fluid sample is saturate in nature (saturates > 50%), but its asphaltene content is high enough that according to the de Boer criteria 13 severe asphaltene problems would not be (11) Alboudwarej, H.; Akbarzedeh, K.; Beck. J.; Svrcek, W. Y.; Yarranton, H. W. Regular Solution Model of Asphaltene Precipitation from Bitumen, AIChE J. 2003, 49 (11), (12) Spiecker, P. M.; Gawrys, K. L.; Kilpatrick, P. K. Aggregation and Solubility Behavior of Asphaltenes and their sub-fractions. J. Colloidal Interface Sci. 2003, 267, (13) de Boer, R. B.; Leerlooyer, K.; Eigner, M. R. P.; van Bergen, A. R. D. Screening of Crude Oils for Asphalt Precipitation: Theory, Practice and the Selection of Inhibitors; SPE Production & Facilities, (14) Ashcroft, S. J.; Clayton, A. D.; Shearn, R. B. J. Chem. Eng. Data 1979, 24, 195. (15) Richon, D.; Laugier S.; Renon, H. J. Chem. Eng. Data 1991, 36, 104. (16) Brown, T. S.; Niesen, V. G.; Sloan, E. D.; Kidnay, A. J. Fluid Phase Equilib. 1989, 53, 7. Table 1. Reservoir Fluid A Composition Crude Oil and Gas Composition overall component liquid (wt %) gas (mol %) wt % mol % N CO C C C C C C C C C cyclics/aromatics C C C C C C C C C C C C C C C C C C C C C MW expected. SARA values alone do not indicate the stability of the fluid. Gas composition also affects the asphaltene instability of a live oil. The reservoir fluid A chromatographic (GC) composition of the gas and liquid phases is presented in Table 1. Reservoir fluid B of 33.0 API gravity and a characteristic GOR of 1601 scf/sbl has a bubble point of 5850 psi at 178 F. The onset pressure measured using SDS technique was determined to be 7650 psi at 178 F. Reservoir fluid B is originally contaminated with OBM at a 2.6 wt % live oil basis which (17) Stryjek, R.; Chappelear P. S.; Kobayashi, R. J. Chem. Eng. Data 1974, 19, 334. (18) Grauso, L.; Fredenslund, A.; Mollerup, J. Fluid Phase Equilib. 1977, 1, (19) Azarnoosh, A.; McKetta, J. J. J. Chem. Eng. Data 1963, 8, 494. (20) Richon, D.; Laugler, S.; Renon, H. J. Chem. Eng. Data 1992, 37, (21) Miller, P.; Dodge, B. F. Ind. Eng. Chem. 1940, 32, (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. Data 1985, 30, 259. (24) Robinson, D. B.; Ng, Heng-Joo. J. Chem. Eng. Data 1978, 23, 325. (25) Katayam, T.; Ohgaki, K. J. Chem. Eng. Data 1976, 21 (1). (26) Wichterle, I.; Kobayashi, R. J. Chem. Eng. Data 1972, 17, 4. (27) Akers, W. W.; Burns, J. F.; Fairchild, W. R. Ind. Eng. Chem. 1954, 46, (28) Reamer, H. H.; Sage B. H.; Lacey, W. N. Ind. Eng. Chem. 1951, 43, (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. Data 1991, 36, 104. (32) Muhammad, M.; Joshi, N.; Creek, J.; McFadden, J. In Effect of Oil Based Mud Contamination on LiVe Fluid Asphaltene Precipitation Pressure. Presented at the 5th International Conference on Petroleum Phase Behavior and Fouling, Banff, Alberta, Canada, 2004; pp

4 1234 Energy & Fuels, Vol. 21, No. 3, 2007 Gonzalez et al. Table 2. Reservoir Fluid B Composition Crude Oil and Gas Composition overall component liquid (wt %) gas (mol %) wt % mol % N CO C C C C C C C C C C C C C C C C C C C C C C MW corresponds to a 3.6 wt % dead oil basis. The SARA content for this fluid was measured as 52.3 wt % saturates, 28.0 wt % aromatics, wt % resins, and 8.3 wt % n-c 7 insoluble asphaltenes. These values also indicate that the reservoir fluid sample is saturate in nature (saturates > 50%), but its asphaltene content is above the limit for a crude with asphaltene severe problems (>1%). 13 Again, SARA analysis is not a clear indication of the fluid stability. The composition of the reservoir fluid B is presented in Table 2. An internal olefin was the base oil for the OBM fluid used as drilling fluid in the field from which the crude oil sample was obtained. The average molecular weight of this fluid was 236 g/mol and its density was g/cm 3 at 74 F. The carbon number distribution of components in the filtrate sample used as the contaminant in the depressurization experiments was determined by gas chromatographic analysis as shown in Figure 2. Fluid A Modeling. In the live oil simulation procedure, Fluid A is treated as a mixture of eight components: four in the gas phase (N 2,CO 2, methane, and light pseudocomponent) and four in the liquid phase (saturates, aromatics + resins, asphaltenes, and olefins). The olefins pseudocomponent represents the OBM contamination; therefore, its mole fraction value is zero for the Figure 2. OBM filtrate carbon number distribution. Table 3. PC-SAFT Characterization of Precipitants and STO of Reservoir Fluid A precipitant MW m σ (Å) ɛ/k (K) C C C STO STO X mole MW m σ (Å) ɛ/k (K) saturates aromatics + resins asphaltenes Table 4. Binary Interaction Parameters (k ij) for STO-Fluid A and Precipitants k ij saturates a A + R b asphaltenes C C C saturates arom + resins asphaltenes 0.00 a Saturates are represented by decane or dodecane; k saturates-n-alkanes ) b Aromatic + resins are represented by toluene or benzene; k A+R-n-alkanes. 14,15 Figure 3. Precipitant volumetric fraction (φ ppt) at the onset of asphaltene precipitation for fluid A. Table 5. PC-SAFT Characterization of Live Fluid A (GOR ) 1180 scf/stb) total gas X mole MW m σ (Å) ɛ/k (K) N CO methane light total liquid saturates aromatics + resins asphaltenes OBM - olefinic uncontaminated fluid. OBM can also be represented as an additional saturates component; in this case, seven components represent the live fluid and the OBM is added to the saturates pseudocomponent proportionally to the amount of contamination in the sample. The amount and characteristic molecular weight of each of the components and pseudocomponents are defined using SARA, GOR, and compositional information. The PC-SAFT parameters are calculated using the procedure described in the PC-SAFT thermodynamic modeling section presented above. The asphaltene PC-SAFT parameters were fitted to meet the titration of the fluid A STO with a series of n-alkanes (C 7,C 11, and C 15 )at20 C and 1 atm measured by New Mexico Tech

5 Asphaltene Instability with the SAFT EOS Energy & Fuels, Vol. 21, No. 3, Table 6. Binary Interaction Parameters (k ij) for Reservoir Fluid A k ij N 2 CO 2 CH 4 light saturates A + R asphaltenes N , CO CH , light saturates A + R asphaltenes Table 7. Fluid A Properties at 1180 scf/bbl experimental calculated P onset (psia) P b (psia), T ) 188 F density at F & psia (g/cm 3 ) liquid (STO) density (g/cm 3 ) (NMT). Table 3 presents STO fluid A characterization for the titration experiments. Titration measurements and simulation results are presented in Figure 3 as the volumetric fraction of precipitant (φ ppt )at the onset of asphaltene instability vs carbon number. The temperature-independent binary interaction parameters (k ij ) used in these calculations are shown in Table 4. Table 5 summarizes composition, molecular weight, and parameter values for each of the live fluid A components with a GOR value of 1180 scf/bbl. The k ij parameters are presented in Table 6. Comparison between the PC-SAFT model fluid properties and experimental results are presented in Table 7. Calculations for fluid A consider the OBM contaminant as an independent pseudocomponent with either olefin characteristics (MW and PC-SAFT parameters correlations for olefins) or as a saturate pseudocomponent. In both cases, the predicted asphaltene precipitation onset and bubble point pressure decreases as the OBM contamination increases. Figure 4 compares simulation results to experimental measurements. Fluid B Modeling. The PC-SAFT asphaltene parameters for fluid B are tuned to meet contaminated reservoir fluid density, bubble point, and asphaltene precipitation onset at high-pressure and high-temperature conditions (see Table 8). The PC-SAFT EOS parameters for the other components are obtained by correlations with molecular weight. In the simulation of Fluid B, seven pseudocomponents represent the live fluid. OBM is assumed to be composed by saturates, and it is added Table 8. Contaminated Reservoir Fluid B Properties at 1601 scf/bbl experimental calculated fluid density (g/cm 3 )at186 F and psia P sat at 178 F (psia) P onset at 178 F (psia) Table 9. Contaminated Reservoir Fluid B Composition and PC-SAFT Parameters at 1601 scf/bbl X mole MW n X mass m σ (Å) ɛ/k (K) N CO 2/H 2S methane light saturates arom + resins asphaltenes to the saturates pseudocomponent proportionally to the amount of contamination in the sample. Table 9 shows the corresponding compositions, molecular weights, and PC-SAFT parameters that best fit the above properties. The k ij parameters have the same values as presented in Table 6 except for the corresponding asphaltene parameters adjusted to tune the measured onset. Since the OBM composition is known, the OBM free fluid composition is calculated mathematically by subtracting the corresponding fraction. The OBM free fluid characterization is presented in Table 10. Asphaltene parameters and the characteristic aromaticity are kept the same, but the global composition and MWs for the saturates pseudocomponent are different. Note that the GOR value for the uncontaminated fluid is 1664 scf/bbl instead of 1601 scf/bbl. The calculated properties of the uncontaminated fluid at 1664 scf/bbl are given in Table 11. Figure 5 shows a decrease in the asphaltene onset pressure and bubble point pressure with contamination calculated using Figure 4. OBM contamination effect on the asphaltene phase behavior of fluid A.

6 1236 Energy & Fuels, Vol. 21, No. 3, 2007 Gonzalez et al. 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. Experimental data from ref 32. Table 10. OBM Free Fluid Pseudocomponents and PC-SAFT Parameters at 1664 scf/bbl X mole MW n m σ (Å) ɛ/k (K) N CO 2/H 2S methane light saturates arom + resins asphaltenes PC-SAFT EOS. Once this fluid is freed of 2.6% OBM contamination, the onset pressure will increase about 415 psi at 220 F and 512 psi at 120 F. Figure 6 shows the decrease of the asphaltene precipitation onset when successive amounts of OBM are added to an original high asphaltene content oil sample. The saturate like behavior assumptions for all of the components in the OBM define the limits of expected behavior. Table 11. OBM Free Contaminated Sample Calculated Properties fluid density (g/cm 3 )at186 F and psia P sat at 178 F (psia) 5534 P onset at 178 F (psia) 8023 Note that GOR also decreases by the OBM addition. The asphaltene stability improvement effect follows a similar trend to that in the case that GOR in the original oil/gas mixture would decrease. Both, the onset and the saturation pressure curves estimated by SAFT, closely follow the experimental findings. Case 2: Asphaltene Precipitation Prediction for High Gas-Oil Ratio Wells Kokal et al. 33 presented experimental information on asphaltene precipitation observed in a number of high GOR wells in the North Ghawar-Arab D reservoir in Saudi Arabia. Even

7 Asphaltene Instability with the SAFT EOS Energy & Fuels, Vol. 21, No. 3, Table 12. Reservoir Fluid C Summary 33 Reservoir Conditions pressure (psia) >3000 temperature ( F) 215 depth (MD [ft]) 6900 Compositional Analysis of the Fluids (mol %) injected gas reservoir fluid actual experiment N CO H 2S C C C C C C C C 7+ molecular weight 240 C 7+ specific gravity MW (calc) though the oil reservoir was undersaturated, two small gas caps are present as a result of gas injection performed about 40 years ago. New development wells drilled recently to produce oil and gas from the gas-cap areas have experienced asphaltene deposition. Experimental results indicate that the crude does not have a natural tendency to precipitate when pressure is reduced; however, asphaltene precipitation occurs after a certain amount of gas is added to the crude. Even though the onset takes place at relatively low GOR values, asphaltene precipitation and deposition increase with increasing GORs. Fluid Properties. A reservoir fluid (fluid C in this work) of API gravity with a characteristic GOR of 580 scf/sbl has a bubble point of 1900 psi at 215 F and is combined with a synthetic gas with a similar composition to that of the actual injected gas. Fluid compositional information and reservoir properties are presented in Table 12. The SARA content of the black oil reservoir fluid (saturates wt %, aromatics wt %, resins wt %, and asphaltenes 2.94 wt %) indicates that the reservoir fluid sample is aromatic in nature (aromatics + resins > 50%) and that the asphaltene content is too high for the crude to have severe asphaltene problems (>1%). 13 SARA values show a relatively stable fluid. The addition of gas changes composition by increasing the amount of light gas components, like methane, which is a strong asphaltene precipitant. All these variables that drive asphaltene precipitation need to be integrated in a single model. Asphaltene Experimental Characterization. The asphaltene precipitation onset was determined by isothermal depressurization of fluid samples. Techniques used to identify asphaltene onset values were the following: - SDS technique - high-pressure filtration to quantify asphaltene bulk deposition 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 value of approximately 625 scf/stb. This suggests that the crude is nearly saturated with asphaltenes and a small amount of gas is enough to start the precipitation. (33) Kokal, S.; Al-Ghamdi, A.; Krinis, D. Asphaltene Precipitation in High Gas-Oil-Ratio Wells; SPE 81567, Society of Petroleum Engineers: Richardson, TX, 2003; p Figure 7. Onset of asphaltene precipitation during addition of gas to a crude oil. 33 A depressurization test was also conducted in another experiment in which 7 cm 3 of gas was added to 30 cm 3 of oil. The light transmittance result is shown in Figure 8 as an inset in the P-T diagram. The crude oil and gas mixture was first pressurized to more than 6000 psi. During depressurization, the onset of asphaltene precipitation started at 4500 psia. The bubble was observed at 3000 psia. Monodisperse Asphaltene. The PC-SAFT EOS parameters for each of the components are calculated from fluid compositional information as describe above in the PC-SAFT Thermodynamic Modeling Section. Table 13 summarizes composition, molecular weight, and parameter values for each component and pseudocomponent of the live sample. Monodisperse asphaltene parameters were tuned to meet experimental asphaltene precipitation onset measurements. This specific crude oil has a density of API gravity, similar to the crude oil density (33.6 API) characterized by Ting; 10 therefore, initial asphaltene parameter values are adjusted from the original values of m ) 29.5, σ ) 4.3 Å, and ɛ/k ) 395 K. The effects on variation in PC-SAFT parameters indicate that the solubility parameter is sensitive to changes in the segment properties ɛ/k and σ. A decrease in the segment energy will decrease the solubility parameter, and a decrease in the segment diameter will increase the solubility parameter; therefore, the chain length (m) and the segment diameter (σ) which represent the volume of the molecule are kept constant, and only the segment energy (ɛ/k) parameter is modified to meet the asphaltene onset experimental data. The aromaticity value for this crude oil was determined to be 0.06 which indicates a close behavior to benzene derivative compounds. The binary interaction parameters used in these simulations are the same as the values presented in Table 6 with this case, all asphaltene binary parameters are equal to the aromatic/resins pseudocomponent. The PC-SAFT model calculates the properties shown in Table 15 and the thermodynamic behavior shown in Figure 9. The amount of asphaltene precipitated due to gas addition is calculated as the asphaltene percentage that separates from crude oil to the asphaltene-rich phase. Figure 10 shows the results at 3000 psia and 215 o F. PC-SAFT predicts that the amount of asphaltenes precipitated will start at about 700 scf/bbl (addition of 10% gas) and that it will increase up to 50% as the GOR reaches a value of 1000 scf/bbl. Polydisperse Asphaltene. The method used to obtain the SAFT parameters for polydisperse asphaltenes is similar to the monodisperse SAFT asphaltene characterization procedure. Ting 10 presented a PC-SAFT EOS characterization for Lagrave oil asphaltene subfractions based on titration experiments performed by Wang 34 using excess n-pentane, n-heptane, and

8 1238 Energy & Fuels, Vol. 21, No. 3, 2007 Gonzalez et al. 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 X mole MW n m σ (Å) ɛ/k (K) N CO 2/H 2S methane light total liquid saturates A + R asphaltene n-pentadecane precipitants. Polydisperse asphaltene was represented in this work as four pseudocomponents in SAFT: the n-c 15+, the n-c 7-15, the n-c 5-7, and the n-c 3-5n-alkane insoluble subfraction which corresponds to the resins subfraction. The SAFT parameters were fit for each subfraction to reproduce the (34) Wang, J. X., Predicting Asphaltene Flocculation in Crude Oils. Ph.D. Thesis, New Mexico Institute of Mining & Technology, (35) Vazquez, D.; Mansoori, G. A. Analysis of Heavy Organic Deposits. J. Pet. Sci. Eng. 26 (1-4), Table 14. Reservoir Fluid C Sample Properties at 580 scg/bbl experimental calculated P onset (psia), scf/bbl 2229 no onset P onset (psia), 890 scf/bbl P b (psia), T ) 215 F, 552 scf/bbl P b (psia), T ) 215 F, 898 scf/bbl liquid (STO) density (g/cm 3 ) (32.03 API) Table 15. SAFT Parameters for Asphaltene Subfractions Including Resins 10 asph subfraction MW m σ (Å) ɛ/k (K) δ (MPa 0.5 ) F (g/cm 3 ) n-c n-c n-c resin experimental data on the minimum volume fraction precipitant needed to induce asphaltene instability in the system asphaltene/ toluene/precipitant at ambient conditions. The fitted SAFT asphaltene parameters and the corresponding solubility parameter (δ) and density (F) in this previous work are listed in Table 15.

9 Asphaltene Instability with the SAFT EOS Energy & Fuels, Vol. 21, No. 3, Figure 10. Asphaltene precipitated amount for reservoir fluid C: monodisperse asphaltene. Table 16. PC-SAFT Parameters for the Various Asphaltene Subfractions asph subfraction MW wt % m σ (Å) ɛ/k (K) n-c n-c n-c Figure 11. Mass distribution of asphaltene subfractions. 10,35 Live oil with polydisperse asphaltene is simulated in this work under two different options: (1) polydisperse asphaltene that includes three asphaltene subfractions, n-c 15+, n-c 7-15 and n-c 5-7 with resins integrated into the aromatic/resins pseudocomponent (2) polydisperse asphaltene with four asphaltene subfractions including the n-c 3-5 n-alkane insoluble subfraction or resins. Option 1: Polydisperse Asphaltene with Three Asphaltene Subfractions. In this option, live oil components and pseudocomponents are kept as defined for the monodisperse case (Table 13) except for the asphaltene portion. The asphaltene component is divided into three subfractions that represent n-c 15+, n-c 7-15, and n-c 5-7 asphaltene cuts. Contrary to the case reported by Ting, 10 no experimental data is available in this work to determine the mass distribution of the asphaltene subfractions; therefore, similar proportions will be assumed (Figure 11). Typical asphaltene SAFT parameters are better represented by the benzene-derivatives correlations; therefore, in this work, asphaltene parameters (m, σ, and ɛ/k) for each subfraction are calculated from eqs The required molecular weight distribution input for these equations is the only adjustable parameter used to tune the experimental onset data. Each asphaltene subfraction should meet the following criteria at 1 atm and 60 F: (1) n-c 15+ : insoluble in pentadecane. (2) n-c 7-15 : insoluble in heptane and soluble in pendadecane. (3) n-c 5-7 : 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 meets the previous criteria. The asphaltene average molecular weight is 1539 g/mol. Binary interaction parameters between asphaltene subfractions are set to zero. The asphaltene molecular weight distribution proposed in this work is presented in Figure 12. The asphaltene precipitation envelope and amount of precipitated asphaltene as a function of the amount of gas added is presented in Figures 13 and 14, respectively. Option 2: Polydisperse Asphaltene with Four Asphaltene Subfractions Including Resins. SAFT simulations as proposed in this option require the redefinition of the crude oil liquidphase pseudocomponents. Resins are eliminated from the aromatics/resins pseudocomponent and included as subfraction of the polydisperse asphaltene. A molecular weight value of

10 1240 Energy & Fuels, Vol. 21, No. 3, 2007 Gonzalez et al. Figure 12. Asphaltene molecular weight distribution. Figure 13. Asphaltene phase envelope with resins in the aromatic/resins pseudocomponent. 800 g/mol for resins is supported by literature values. 36,37 The new liquid-phase characterization of the live oil sample at 580 scf/bbl is shown in Table 17; the gas-phase characterization is kept invariable. The amount of precipitated asphaltene including resins as a function of the amount of gas added is presented in Figure 15. Simulation results show a higher asphaltene precipitated total amount for the polydisperse case. An analysis of the mass distribution of the asphaltene subfractions in the precipitated phase shows that the largest asphaltenes will precipitate first, (36) Peramanu, S.; Pruden, B. B.; Rahimi, P. Molecular Weight and Specific Gravity Distributions for Athabasca and Cold Lake Bitumens and Their Saturate, Aromatic, Resin and Asphaltene Fractions. Ind. Eng. Chem. Res. 1999, 38, (37) Speight, J. G. The Chemistry and Technology of Petroleum; Marcel Dekker: New York, followed by the precipitation of smaller asphaltenes. As seen in the figures, SAFT is able to describe the change in magnitude in the amount of asphaltene that precipitates depending on the type of n-alkane precipitant. Conclusions The following conclusions can be drawn from the present investigation: The PC-SAFT EOS model showed a decreased in the asphaltene precipitation onset and bubble point pressure as the OBM contamination increases. The decrease in asphaltene precipitation onset is caused by a reduction in GOR as a result of the addition of OBM. We demonstrate that the effect of OBM contamination on asphaltene stability pressure can be accurately estimated.

11 Asphaltene Instability with the SAFT EOS Energy & Fuels, Vol. 21, No. 3, Figure 14. Amount of precipitated asphaltene subfractions (no resins as asphaltene subfraction). Figure 15. Amount of precipitated asphaltene subfractions (resins as asphaltene subfraction). Therefore, actual reservoir conditions can be predicted based on laboratory samples contaminated with OBM. The asphaltene precipitation tendencies caused by alteration in the reservoir fluid composition during commingle with gas can be predicted, and proper measurements can be taken. A polydisperse asphaltene was represented in SAFT with four pseudocomponents: the n-c 3-5 (the resins), the n-c 5-7, the n-c 7-15, and the n-c 15+ subfractions. Using an extension of the monodisperse SAFT asphaltene parameter fitting procedure, we were able to assign a set of SAFT parameters to represent each of the four subfractions. An analysis of the mass distribution of the asphaltene subfractions in the precipitated phase showed that the largest Table 17. PC-SAFT Characterization of the Live Sample at 580 scf/bbl X mole MW m σ (Å) ɛ/k (K) N CO 2/H 2S methane light saturates aromatics n-c 15+ asphaltene n-c 7-15 asphaltene n-c 5-7 asphaltene resins asphaltenes would precipitate first, followed by the precipitation of smaller asphaltenes.

12 1242 Energy & Fuels, Vol. 21, No. 3, 2007 Gonzalez et al. The live oil model 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. Acknowledgment. The authors thank DeepStar, Consortium on Processes in Porous Media at Rice University, and the Department of Energy for their financial and technical support. EF060453A