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Fossil Fuels
A Predictive Model for PVT Properties and Asphaltene Instability of Crude Oils Under Gas Injection Wael A. Fouad, Mohammed I. L. Abutaqiya, Kristian Mogensen, Yit Fatt Yap, Afshin Goharzadeh, Francisco M. Vargas, and Lourdes F. Vega Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.8b01783 • Publication Date (Web): 11 Jul 2018 Downloaded from http://pubs.acs.org on July 11, 2018
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A Predictive Model for PVT Properties and Asphaltene Instability of Crude Oils Under Gas Injection Wael A. Fouad,*,a Mohammed I. L. Abutaqiya,b Kristian Mogensen,c Yit Fatt Yap,d Afshin Goharzadeh,d Francisco M. Vargas,b and Lourdes F. Vegaa a
Gas Research Center and Department of Chemical Engineering, Khalifa University of Science
and Technology, Petroleum Institute, P.O. Box 2533, Abu Dhabi, United Arab Emirates b
Department of Chemical and Biomolecular Engineering, Rice University, Houston, Texas
77005, United States c
Abu Dhabi National Oil Company (ADNOC), P.O. Box 898, Abu Dhabi, United Arab Emirates
d
Department of Mechanical Engineering, Khalifa University of Science and Technology,
Petroleum Institute, P.O. Box 2533, Abu Dhabi, United Arab Emirates KEYWORDS asphaltene, flow assurance, EOR, SAFT, molecular modeling
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ABSTRACT A new approach based on the statistical associating fluid theory (SAFT) is presented here to model eight light crudes, with the SARA analysis as the only input for the model. Within the characterization procedure of Punnapala and Vargas (Fuel 2013, 108, 417-429), the aromaticity parameter and the asphaltene molecular weight were fixed to all crude oil samples, while the asphaltene aromaticity is the only fitted parameter of the model. A correlation for this parameter with the flashed gas molecular weight allows full predictions of the phase behavior without the need of any asphaltene onset data. The predictive molecular model was used to study asphaltene instability as a function of injected CO2 and natural gas concentration. The model can also accurately reproduce routine PVT experiments such as constant composition expansion, differential vaporization and multi-stage separation tests performed on the crude oils, thereby providing a unified framework for phase behavior studies.
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INTRODUCTION Asphaltenes are defined as fossil fuel derived constituents that are insoluble at ambient conditions in large excess of light hydrocarbons such as n-pentane and n-heptane and soluble in toluene1. Their exact chemical structure vary from one crude oil to another, but in general, they are known to be the heaviest and the most polar fraction of crude oil consisting of polyaromatic molecules surrounded by aliphatic and heteroatomic chains2. The polyaromatic core may also contain heteroatoms in the form of pyrrole, pyridine and thiophane. It was also reported that asphaltenes precipitants exhibit the characteristic optical patterns of liquid crystals at low temperatures3. The molecular weight of asphaltenes is a matter of disagreement in the literature due to their ambiguous chemical structure. Researchers considering asphaltene monomers as consisting of a single polynuclear aromatic (PNA) ring report molecular weights of less than 1000 Da4-8. Others report a molecular weight of 1000-10,000 Da, depending on the number of multiple PNA present in the structure under consideration9-10. Asphaltene deposition can occur during different stages of production and processing due to changes in pressure, temperature and composition. Oilfield reports indicate that asphaltene deposition in a well can lead to complete cease of fluid flow and production. Moreover, the cost of a typical asphaltene remediation job can get as high as $500,000 onshore or $3,000,000 offshore11. Downstream wise, asphaltene deposition can cause fouling in rotating equipment and plug tubing and flow lines. Asphaltene stability is influenced by changes in pressure and temperature, as well as crude oil composition. At constant temperature, light hydrocarbons released below the bubble pressure lead to an increase in oil density and asphaltene stability. Asphaltene instability is seen at higher
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pressures starting from their onset condition down to the bubble point. The crude oil composition can be highly influenced by natural gas and carbon dioxide injection during secondary and tertiary oil recovery which in return can enhance asphaltene instability and flocculation. Reports from a CO2 pilot in an Abu Dhabi onshore field indicate that three asphaltene removal jobs were carried out across the lifetime of the project12. Asphaltene deposition was observed just 3-4 weeks after cleanup. Moreover, asphaltene stability can also be disturbed by the presence of brine in petroleum reservoirs depending on the salinity13. Acid stimulation treatment to restore the initial permeability of a damaged formation can also participate in asphaltene instability and lead to severe permeability damage. Two approaches have been proposed so far in the literature to understand the phase behavior of asphaltenes. In the colloidal theory approach, asphaltenes are assumed to have a colloidal form stabilized by the adsorption of resins on their surface due to polar interactions14. The resins are made up of small aromatic rings with long hydrocarbon chains directed towards the oil phase to form micelles. Furthermore, asphaltene precipitation is assumed to be an irreversible process that occurs due to resin desorption, which leads to aggregation and phase separation. The theory, as a valid way to explain asphaltene stabilization, was opposed recently by various experimental and simulation studies15-18. On the contrary, in the solubility theory approach, asphaltenes are described as part of the oil blend and precipitation is viewed as a form of liquid phase split
19
.
The phase equilibrium is modeled using regular solution theory20-24, cubic equations of state (EoS) or different versions of the statistical associating fluid theory (SAFT)25-27. Wu and coworkers28-30 used the original form of the SAFT equation of state as well as its variable range form (SAFT-VR) to study asphaltene precipitation in crude oils. In their work, the association term was incorporated into the model to consider strong directional forces between the 4 ACS Paragon Plus Environment
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asphaltene molecules and between the asphaltene and the resin molecules. Panuganti et al.31 demonstrated the superiority of the perturbed chain form of the SAFT equation of state (PCSAFT)32-33 over the Soave-Redlich-Kwong-Peneloux (SRK-P) EoS34 in modeling asphaltene precipitation. The association term was not incorporated into their model. AlHammadi et al.35 performed a comparison between PC-SAFT, a solubility model, and the Cubic Plus Association (CPA) EoS, a colloidal model36. The association term was not incorporated in PC-SAFT, while CPA considered cross-association between asphaltenes and resins. Results indicate that with an optimized characterization, both methods give acceptable predictions of the phase behavior and asphaltene precipitation tendency, while PC-SAFT is superior in the prediction of derivative thermodynamic properties especially, at high pressures. In a later study, Arya et al.37 examined the effect of incorporating the association term in PC-SAFT, performing a comparison of the three models: PC-SAFT without association, CPA and PC-SAFT with association. For the two associating models, asphaltenes are modeled with four association sites (2 positive and 2 negative) and the maltene components of the crude oil (saturates, aromatics and resins) are modeled with a single neutral association site that can cross-associate with the positive or negative sites of the asphaltene. At least three upper onset pressures and one bubble pressure experimental point were required for all models. They investigated the performance of the three models for different types of asphaltene phase behavior for seven different fluids, showing that PC-SAFT (without association) was unable to correlate the upper onset pressure boundary for some of the crude oils, while the two associating models perform very similar. A question was raised about whether only van der Waals interactions are responsible for asphaltene precipitation or association forces also contribute to asphaltene precipitation. However, it should be noted that
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adding association directly implies adding extra parameters, given additional flexibility to the model, but limiting its predictive power substantially. We present in Table 1 the SARA analysis for bottom hole crude oil samples (AW1, AW2, BW2, D and E) previously published by researchers in Rice University38. In this work, we report new asphaltene precipitation onset conditions for these crudes as well as new PVT and asphaltene data for bottom hole crude oils BW1, C and F. Crudes D and E come from two different Abu Dhabi offshore fields and the samples were subjected in lab to CO2 and hydrocarbon gas injection respectively. The rest of the data emanates from onshore fields samples under lab CO2 injection. The composition of the hydrocarbon gas can be found in the Supporting Material. In addition, a predictive PC-SAFT model based on the characterization procedure of Punnapala and Vargas39 is developed here and used to predict the crude oils pressure-volume-temperature (PVT) properties and asphaltene phase behavior. Following Punnapala and Vargas, no association forces are considered in this work, the implications of this assumption on the performance of the model will be seen when checking its predictive capabilities. PVT AND ASPHALTENE PRECIPITATION EXPERIMENTS Experimental data used throughout this work were provided by the operating companies of the Abu Dhabi National Oil Company (ADNOC). To summarize the experimental procedure, live oil samples were first flashed in a gasometer to ambient conditions. Compositional analyses of the flashed liquids were then carried out using a liquid injection gas chromatograph (GC) with a flame ionization detector (FID). Compositional analyses of the flashed gases were carried out using a gas injection GC with two separation columns. The first column is a combination of a 100 mesh packed column and a 100 mesh molecular sieve with high purity helium as a carrier
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gas. The second column is made up of fused silica with thick methyl silicone as the stationary phase. Separation of light hydrocarbons up to C6, inert and acid gases was achieved using the first column while the heavier components were separated using the second column. Gaseous components up to C4 were analyzed using a thermal conductivity detector (TCD) while heavier components were analyzed using a FID. A summary of samples SARA analyses, stock tank densities at standard and saturation conditions and gas/oil ratios (GORs) is provided in Table 1. Asphaltene onset pressures were determined using near infrared red (NIR) light transmittance and high pressure microscope (HPM). Table 2 illustrates the bubble (BP) and asphaltene onset pressures (AOP) for each of the samples at bottom hole temperature of 250/260oF and as a function of injection gas mass concentration. Constant composition expansion, differential vaporization and multi-stage separation tests were performed on crude oils considered in this work to determine their corresponding PVT properties. Detailed description of these experiments can be found in Pedersen et al.40. PC-SAFT OIL CHARACTERIZATION The SAFT equation of state25-27 models molecules as chains of spherical segments with long range dispersion interactions among them. An advantage of the model is that the contributions to the free energy are derived from statistical mechanics-based theory and validated versus molecular simulation results of the same underlying model. In addition, the structure of the molecules is built into the equation from its inception. Thus, the equation of state requires a minimal number of physical parameters that can be fit to pure fluid properties such as vapor pressure and saturated liquid density.
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Table 1 SARA analysis and fluid properties of crude oils considered in this work
Component Saturates Aromatics Resins Asphaltenes STO MW (g mol−1) STO density at 60oF (g cm−3) Density at saturation (g cm−3) Zero flash GOR (scf/bbl)
Crude AW1 70.42 22.64 6.24 0.18
Crude AW2 70.20 22.89 4.85 0.12
Composition (wt. %) Crude Crude Crude BW1 BW2 C 70.60 68.77 74.97 21.00 23.72 17.38 5.50 6.77 7.50 0.10 0.25 0.14 Fluid Properties
Crude D 59.4 22.57 13.97 1.73
Crude E 80.64 17.44 1.47 0.45
Crude F 71.31 20.29 8.00 0.4
202.1
206.9
192.2
212.5
184.3
212.4
195.5
203.1
0.8404
0.8402
0.8292
0.8464
0.829
0.867
0.8239
0.8377
0.6547
0.6362
0.6236
0.6105
0.6154
0.764
-
0.6913
888*
1085*
1113
1603*
952
214
382
469
* Solution GOR at saturation
Table 2 Measured bubble and asphaltene onset pressures of crude oils considered in this work T (oF) 250 250 250 250
% BP Inj. (psia) Crude AW1 0 2392 20 2800 30 2056 45 3765
AOP (psia)
T (oF)
ND* 3765 6045 8015
250 250 250 250 180 180 180
260 260
Crude AW2 0 2870 40 3904
ND ND
250
260 180 150 120 260 260 260
0 0 0 0 10 20 30
Crude E** 1104 988 906 838 1541 1941 2393
ND ND 2223 4223 3107 4644 7501
260 210 160
% BP Inj. (psia) Crude BW1 0 3479 20 3835 30 4045 40 4515 10 3655 20 3640 30 3768 Crude BW2 0 3981
0 0 0
Crude F 1276 1175 1026
AOP (psia)
T (oF)
% Inj.
ND ND 5229 7575 ND 4636 6028
260 260 260 260
0 20 30 40
BP (psia) Crude C 2896 3409 3576 3891
ND
212 212 212
0 34 45
Crude D 835 -
2228 3396 4115
* ND = not detected
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AOP (psia) ND 4323 4957 7957
ND 2850 3850
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** hydrocarbon gas injection
Similar to a cubic equation of state, the model requires only three pure-component parameters for the case of a non-associating fluid. Furthermore, these parameters have physical meaning and correlate well with molecular weight for a given homologous series. The complete equation of state in PC-SAFT32-33, in terms of the reduced Helmholtz free energy, is given as the sum of an ideal gas contribution , a hard-sphere contribution based on an equation of state by Boublik and Mansoori41-42, a chain formation contribution as formulated by Chapman et
al.27 and a dispersion contribution based on Barker and Henderson43 perturbation theory:
≡ − = + +
(1)
More details about different terms used in the PC-SAFT equation of state can be found in the work of Gross and Sadowski32-33. Table 3 PC-SAFT pure component parameters of gaseous species explicitly modeled in this work
H 2S
MW (g mol−1) 34.081
CO2
1.649
σ (Å) 3.06
ε/kB (K) 229.84
T Range (K) 188-372
AAD % psat 0.10
AAD % ρsat 0.76
44.009
1.513
3.19
163.33
216-304
0.34
1.27
32
N2
28.013
1.210
3.31
90.96
80-133
2.21
1.38
32
CH4
16.043
1.000
3.70
150.03
97-300
0.36
0.67
32
C 2H 6
30.070
1.610
3.52
191.42
90-305
0.30
0.57
32
C 3H 8
44.097
2.002
3.62
208.11
85-523
1.29
0.77
32
Component
m
Ref. 44
Following the latest characterization method proposed by Punnapala and Vargas39, hydrogen sulfide (H2S), carbon dioxide (CO2), nitrogen (N2), methane (CH4), ethane (C2H6) and propane (C3H8) are explicitly modeled within the SAFT framework. Table 3 illustrates their corresponding PC-SAFT parameters that were previously fitted to pure component saturated 9 ACS Paragon Plus Environment
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liquid density and vapor pressure. These components make up the flashed gas phase in addition to a pseudo-component named "heavy gas" to represent C4+ fractions found in the compositional analysis. PC-SAFT parameters for the heavy gas pseudo-component were calculated using molecular weight dependent correlations developed by Gonzalez et al.45 for n-alkanes and are given below:
= 0.0257 + 0.8444 Å = 4.047 − 4.8013
ln
# 9.523 K = exp *5.5769 − $%
(2) (3)
(4)
The stock tank oil is composed of three pseudo-components namely: “saturates”, “aromatics + resins (A+R)” and “asphaltenes (Asphalt)” to represent different molecular structures found in the liquid phase. The SARA analysis is used to determine the composition of each of the pseudocomponents. The molecular weight of C11+ saturates was fixed to a value of 290 g mol−1 in this work and the corresponding molecular weight of C11+ A+R was then calculated based on the STO molecular weight. Saturates are assumed to consist solely of n-alkanes and therefore their PC-SAFT parameters were determined using Gonzalez et al. correlations for n-alkanes. Parameters for A+R and Asphalt are obtained by introducing a weighting factor (called aromaticity) where γ = 0 represents n-alkanes and γ = 1 represents PNA.
= 1 − . 0.0257 + 0.8444 + . 0.0101 + 1.7296
Å = 1 − . *4.047 − 4.8013
ln 93.98 - + . *4.6169 −
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(5) (6)
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# 9.523 234100 K = 1 − . /exp *5.5769 − -0 + . 1508 − 4 $% 2.3
(7)
Using the measured compositional analysis, STO density and gas/oil ratio (GOR), the recombined oil composition is constructed and used for the SAFT calculations. Table 4 illustrates the recombined oil composition for each of the eight crude oils. Table 4 Composition of PC-SAFT characterized recombined oils Component H2S CO2 N2 CH4 C2H6 C3H8 Heavy gas Saturates A+R Asphalt
Crude AW1 0.000121 0.0278 0.00121 0.322 0.0647 0.0608 0.127 0.285 0.111 4.834E-05
Crude AW2 0.00280 0.0264 0.00120 0.376 0.0679 0.0589 0.133 0.242 0.0918 2.817E-05
Crude BW1 0.00588 0.0247 0.000859 0.448 0.0560 0.0462 0.0790 0.251 0.0878 2.237E-05
Composition (mol. %) Crude BW2 Crude C 0.0527 0 0.0368 0.0262 0.000900 0.002389 0.459 0.387 0.0535 0.0704 0.0417 0.0516 0.105 0.0754 0.179 0.312 0.0710 0.0755 4.456E-05 3.295E-05
Crude D 0 0.0093 0.000964 0.125 0.0460 0.0510 0.0513 0.549 0.166 9.076E-04
Crude E 0.00679 0.0109 0.00401 0.191 0.0429 0.0475 0.1033 0.479 0.114 1.748E-04
Crude F 0 0.0238 0.00217 0.181 0.0552 0.0625 0.137 0.414 0.124 1.462E-04
As seen in Eqs. 3-6, the molecular model requires three fitting parameters namely: the A+R aromaticity parameter (.567 , the asphaltene aromaticity parameter (.5 89: and the asphaltene molecular weight (5 89: ). These parameters were then fitted to oil density, BP and AOP data in previous SAFT modeling works35, 38-39. Upon investigation on crude oils from Abu Dhabi region, it was found that a universal aromaticity factor .567 of 0.7 could be used to model the PVT phase behavior. In addition, it
was found that fixing the molecular weight of asphaltenes 5 89: to 3000 g mol−1 could well reproduce experimental AOP data after only tuning .5 89: . This molecular weight value
corresponds to a small aggregate formed by three or four asphaltene molecular units. It agrees
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well with the molecular weight of asphaltenes (3066 g mol−1) measured using HPLC-gel permeation chromatography (GPC) in tetrahydrofuran for Mexican crude oil samples30, 46. The asphaltene aromaticity parameter (.5 89: was tuned to AOP data at the bottom hole temperature of 250/260oF. Table 5 reports the optimized .5 89: for six of the studied crude oils.
It was found that the fitted .5 89: correlates well with the flashed gas molecular weight as shown in Figure 1. The latter procedure eliminates the need of any tuning parameters, and,
therefore making the model purely predictive. Following the solubility theory approach, asphaltene precipitation is modeled here as a liquid-liquid phase equilibrium. Binary interaction parameters ($; ) used within the SAFT framework were also fixed for all crude oils and are shown in Table 6. Table 5 Molecular weight and aromaticity of the pseudo-components for determining their PCSAFT parameters Pseudo Component
Crude AW1
Heavy gas Saturates A+R Asphalt
73.410 198.894 210.339
