Measurement and Prediction of Hydrocarbon Dew Points of Synthetic

Article pubs.acs.org/jced

Cite This: J. Chem. Eng. Data XXXX, XXX, XXX−XXX

Measurement and Prediction of Hydrocarbon Dew Points of Synthetic Natural Gas Mixtures Liang Mu* and Qingyan Cui

J. Chem. Eng. Data Downloaded from pubs.acs.org by NORTH CAROLINA A&T STATE UNIV on 10/16/18. For personal use only.

College of Chemical Engineering, Fuzhou University, Fuzhou 350116, P. R. China ABSTRACT: It is very important to predict the condensation of liquid hydrocarbons when transporting natural gas with pipelines in industry. Using a high-pressure transparent sapphire cell, the hydrocarbon dew points of eight synthetic natural gas mixtures were measured with the isothermal pressure search method. The test temperature ranges from 234.5 to 295.35 K and the pressure ranges from 1.706 to 11.495 MPa, and the results were used to evaluate the prediction performance of SRK and PR EOSs. The measured results showed that the cricondentherm and cricondenbar decrease with the increasing CH4 concentration; however, they present an increasing trend with the increasing concentration of other hydrocarbon components (C2H6 and C3+). It was found that 0.98 mol % changes in the n-C5 concentration lead to the cricondentherm decreasing by 22 K, and 0.46 mol % changes in the n-C6 concentration result in the cricondentherm reducing by 27 K. Correspondingly, the cricondenbar decreased by 1.9 and 2.7 MPa, respectively. In industry, a heavy hydrocarbon can be absorbed with low-volatility oil before proceeding with a pipeline, which can prevent the condensation of liquid hydrocarbons. For the dew point prediction by EOS, the PR calculation exhibited good agreement with the experimental data, and the average absolute deviations were within 0.79−1.53% while the SRK calculation evidently deviated from the measured values.

1. INTRODUCTION In the oil and gas industry, natural gas is transmitted through pipelines to destinations needed to meet both water dew point (WDP) and hydrocarbon dew point (HDP) specifications. To control the WDP, natural gas is usually dehydrated through absorption or adsorption (such as glycol absorption or molecular sieve adsorption)1−6 because hydrate or ice may form in nondehydrated gas at low temperatures, which will be encountered in cold climates through the delivery system to users.7−9 In addition, water condensation can also lead to pipeline corrosion problems, especially from acid gas components such as CO2 and H2S.10,11 Another issue to note is that the HDP needs to be reduced to avoid heavy components condensation because liquid hydrocarbon can increase the pipeline pressure drop and require a higher frequency of pigging operations to maintain the delivery capacity.12 Therefore, it is very important to predict the HDP of natural gas before proceeding with pipeline transmission. Figure 1 shows the phase envelope for a typical natural gas, and the theoretical HDP can be defined as any point along the dew point line when moving from the gas phase to the first small drop of liquid. The cricondentherm and cricondenbar are the maximum temperature and pressure, respectively, at which hydrocarbon liquid dropout could occur.13 Natural gas usually contains hydrocarbons and water as well as other impurities, and its composition mainly depends on the source and can change over the life of a gas well. Rich gas refers to natural gas that has higher concentrations of C3 and C4 as well as intermediate-weight hydrocarbons from C5 to C8. After the heavy components are removed in a gas-processing © XXXX American Chemical Society

Figure 1. Phase envelope for a typical natural gas.

plant (by simple refrigeration and condensation, absorption, adsorption, or cryogenic processes),13 rich gas will be converted to lean gas with high concentrations of CH4 and C2H6 (typically ≥95 mol %). In industry, the conventional method is transmitting lean gas in single-phase form, which can avoid the condensation of heavy components from rich gas at low temperatures. However, this situation would not occur when the operating temperature is higher than the HDP of rich gas for a given pressure condition. The HDP analysis and prediction of natural gas have been discussed in the literature Received: August 13, 2018 Accepted: October 4, 2018

A

DOI: 10.1021/acs.jced.8b00706 J. Chem. Eng. Data XXXX, XXX, XXX−XXX

Journal of Chemical & Engineering Data

Article

Table 1. Composition (mol %) of SNG1−9 Used in This Studya component

SNG1

SNG2

SNG3

SNG4

SNG5

SNG6

SNG7

SNG8

SNG9

CH4 C2H6 C3H8 n-C4H10 n-C5H12 n-C6H14 CO2 N2

97.90 2.10

89.93 4.21 1.86 2.06 1.94

92.40 3.21 0.71 0.70 0.64 0.71 0.72 0.91

93.92 3.16 0.93 1.03 0.96

92.32 3.58 1.30 1.44 1.36

90.73 4.00 1.67 1.86 1.74

95.15 2.65 0.35 0.35 0.32 0.36 0.36 0.46

95.97 2.49 0.25 0.24 0.23 0.25 0.25 0.32

92.95 3.11 0.63 0.63 0.58 0.64 0.64 0.82

a

The standard uncertainty for each mixture composition is 0.01 mol %.

for several decades,14−19 and the common methods used to determine HDP are direct measurement using a chilled mirror procedure and indirect measurement using compositional analysis from a gas chromatograph (GC) combined with the equation of state (EOS). Avila et al.20 and Jarne et al.21 measured the dew point curves of synthetic natural gas and correlated the experimental data with model calculations. Blanco et al.22 tested the dew points of ternary (CH4 + C2H6 + C4H10) gas mixtures and predicted them with models. However, from these studies it was found that the average absolute deviation in calculating dew point temperatures using models could be as large as 3.7 K compared to experimental data. To apply the GC-EOS method, the dew points of natural gas need to be predicted using appropriate thermodynamic models. The most commonly used models are cubic EOS belonging to the Redlich−Kwong23 (RK) and Peng− Robinson24 (PR) family because of their simplicity and accuracy. Nasrifar et al.25,26 investigated various thermodynamic models in predicting natural gas dew points, and their results indicated that the Patel-Teja27 (PT) EOS was better for rich gas while the RK family of EOS was better for lean gas. Louli et al.28 measured six synthetic natural gas mixtures with the chilled mirror method in the temperature range of 256− 286 K and the pressure range of 0.36−10.52 MPa and then compared their results with the predictions made with the PR, PPR78,29 and UMR-PRU models.30 Their results indicate that the use of binary interaction parameters (BIP) in PR EOS can improve the dew point predictions only in systems that contain large quantities of CO2. Mørch et al.17 tested the hydrocarbon dew points of five synthetic natural gas mixtures by comparing the results with SRK predictions, and they observed considerable deviations between calculated and experimental dew points as the pressure approached the cricondenbar. Therefore, they used RK EOS with the Mathias and Copeman temperature-dependent term31 to improve the calculation accuracy. It is obvious that the investigation of the natural gas dew point is an ongoing process of great significance in which both experimental and thermodynamic modeling studies are necessary. The existing high-pressure PVT apparatus has mainly been designed to test formation fluid (such as condensate gas) which has a high dew point temperature.32,33 However, the rich gas dew point is very low, and most PVT apparatuses do not have refrigeration systems and cannot be used to test it. In this work, by using a high-pressure sapphire cell apparatus which can provide low temperature and visualization conditions, we tested the HDP of eight synthetic natural gas samples with the pressure search method. It was reported that the influence of the hydrocarbon component on the HDP is more sensitive as the number of carbons increases.14,34

However, there was few reports to quantify it in the literature; therefore, this study investigated the influence of a small trace change of n-C5 or n-C6 on the cricondentherm and cricondenbar. In addition, the adaptability of the PR and SRK35 EOSs in predicting dew points was examined. The results can provide basic research information on predicting the HDP for the natural gas industry.

2. EXPERIMENTAL SECTION 2.1. Materials. Three synthetic natural gas mixtures (SNG1−3) were purchased from the Beijing AP Beifen Gas Industry Company. SNG1 is a lean gas sample which contains only C1 and C2. SNG2 and SNG3 are rich gas samples, and the main difference is that SNG2 consists of C1 ∼ n-C5 while SNG3 contains n-C6 as well as CO2 and N2. SNG4−6 were made by us with SNG2 and SNG1 in mole ratios of 5:5, 7:3, and 9:1, and SNG7−9 were prepared with SNG3 and SNG1 in mole ratios of 5:5, 7:3, and 9:1. The compositions of all gas samples were analyzed with an Agilent gas chromatograph (HP 7890) and are shown in Table 1. 2.2. Experimental Apparatus. Figure 2 shows a schematic diagram of the experimental setup. The critical part of this setup is a transparent sapphire cell installed in an air bath where the working temperature can be controlled within 223.15−373.15 K. The cell’s effective volume is 60 cm3 (inner diameter: 2.54 cm), and it can be changed by moving a

Figure 2. Schematic diagram of the experimental apparatus. DPT, differential pressure transducer; PRT, resistance thermometer detector; and DAS, data acquisition system. B



Article

than the true value because this method needs to accumulate a certain amount of liquid hydrocarbon on the mirror before it can be observable or detectable.14 However, the mirror is still cooling at that time and the temperature measurements are not at the first dew condensation but are a little later than that. Therefore, the isothermal pressure search method was used to test the dew points in this study because the system pressure can be easily controlled and changed with time. To check the reliability of the experimental setup and method, a gas sample of given composition was measured (Table 2) and compared

piston with a hand pump. A magnetic stirrer coupled with a magnet mounted outside the cell is used to stir the reaction system. To clearly observe the experimental phenomena, a cool light lamp (LG100H) is fixed on the outside of the cell. Two high-precision platinum resistance thermometers (Pt100) located at the upper and bottom parts of the cell are used to measure the experimental temperature. The cell’s pressure is monitored by a differential pressure transducer and a Heise pressure gauge simultaneously. The detailed setup description in the introduction can refer to previous publications.36−38 2.3. Experimental Procedure. The isothermal pressure search method39,40 was used to measure the dew point of SNG. First, the sapphire cell was cleaned and dried and then installed in the air bath to eliminate air in the cell and external piping, which were evacuated using a vacuum pump. Subsequently, the sapphire cell was filled with an SNG sample to a possible pressure higher than the predicted dew point pressure to keep it in the single-phase region. The air bath temperature was then adjusted to the desired value, and the stirrer was started at a speed of 15 rpm. When the system temperature was maintained at a constant value for 3 h, the pressure searching process was performed as follows: decreasing slowly at 0.5 MPa intervals until a film of condensate is observed through the transparent cell, increasing to a desired value slightly higher than the dew point, and decreasing at 0.2 MPa intervals to a film of condensate formed again where the current pressure was recorded as the dew point pressure. A typical pressure curve was shown in Figure 3. In this work, one data point was

Table 2. HDP Measured Values for a Gas Sample of a Given Composition (94.085 mol % CH4 + 4.468 mol % C2H6 + 1.447 mol % n-C5)a T/K

P/MPa

266.10 268.30 268.00 266.40 262.80 255.90

7.051 5.590 4.513 3.534 2.662 1.554

a Standard uncertainty (u) values are u(T) = 0.02 K and u(P) = 0.01 MPa for P < 5.5 MPa and u(P) = 0.025 MPa for P > 5.5 MPa.

Figure 4. Comparison of measured values in this work against literature data.17 Figure 3. Typical pressure changes in the process of searching for dew points.

with the literature data.17 As shown in Figure 4, the results proved that the measured values are consistent with those from the literature, which confirms the reliability of the apparatus and the feasibility of our test method. In this study, the uncertainty in the measurement results mainly comes from the uncertainties in the platinum resistance thermometer (Pt 100) and the pressure transducer. The standard uncertainty in temperature is u(T) = 0.02 K, and the standard uncertainties in pressure are u(P) = 0.01 MPa for P < 5.5 MPa and u(P) = 0.025 MPa for P > 5.5 MPa. In addition, to ensure more accurate results, the composition of each gas sample was analyzed with an Aglient GC (HP 7890), which was calibrated against a standard sample with a known gas composition and has an uncertainty of 0.01 mol %. 3.2. HDP Measurement by the Pressure Search Method. In this work, we mainly investigated the hydrocarbon dew point of SNG samples in the region between the cricondenbar and cricondentherm, in which the HDP pressure decreases with the increase in temperature. However, for the

tested five times by repeating the above steps, and when the deviation of each pressure measurement was less than 0.05 MPa, the average value was calculated as the dew point pressure. Then the air bath temperature was set to a new desired value, and the dew point pressure was determined similarly. It should be noted that the cell and external piping should be keep dry and clean when testing the samples because the existence of a little water would reduce the measurement accuracy. In addition, the dew point pressure is recorded when a film (rather than droplet) of condensate is formed in the cell, and the cell’s pressure can be repeatedly increased or decreased for better searching for the dew point.

3. RESULTS AND DISCUSSION 3.1. Experimental Validation and Uncertainty Evaluation. Some researchers believe that the dew points measured by the chilled mirror method are slightly lower C



Article

Table 3. HDP Measured Values for the Samples Not Containing n-C6a SNG2

SNG4

SNG5

SNG6

T/K

P/MPa

T/K

P/MPa

T/K

P/MPa

T/K

P/MPa

253.65 257.15 261.15 266.15 272.15 277.65 282.15 286.25 290.31 292.15b 290.15 287.15 281.65 278.55

10.653 10.882c 10.777 10.605 10.306 9.873 9.156 8.267 7.116 5.531 4.066 3.076 2.084 1.753

240.30 243.06 247.83 253.65 258.15 261.15 264.15 268.15 270.25b 268.57 265.75 261.65

9.030 9.172c 8.996 8.701 8.186 7.802 7.193 6.002 4.442 3.259 2.469 1.752

247.77 250.55 255.42 261.15 265.15 268.15 272.15 275.15 279.15 280.15b 279.05 276.25 271.15

9.859 9.954c 9.784 9.508 9.123 8.809 8.212 7.582 6.105 4.626 3.721 2.816 1.912

250.88 253.65 259.15 265.45 271.67 276.15 282.12 286.13 288.45b 287.15 283.95 278.35

10.464 10.608c 10.504 10.265 9.861 9.313 8.331 6.961 4.926 3.962 2.998 2.036

a

Standard uncertainty (u) values are u(T) = 0.02 K and u(P) = 0.01 MPa for P < 5.5 MPa and u(P) = 0.025 MPa for P > 5.5 MPa. bThe cricondentherm. cThe cricondenbar.

Table 4. HDP Measured Values for the Samples Containing n-C6a SNG3

SNG7

SNG8

SNG9

T/K

P/MPa

T/K

P/MPa

T/K

P/MPa

T/K

P/MPa

249.95 253.15 261.15 269.15 276.15 282.15 288.15 293.85 295.35b 293.05 287.65

11.275 11.495c 11.405 11.054 10.443 9.619 8.526 6.658 4.871 3.229 1.981

239.17 242.21 246.45 253.15 261.15 268.15 272.15 275.15 276.15b 275.95 273.15 270.25

9.463 9.567c 9.482 9.309 8.658 7.573 6.706 5.595 4.512 3.401 2.303 1.706

234.50 239.89 244.55 248.65 253.15 257.15 261.15 264.15 266.27 267.43b 265.39

8.609 8.647c 8.282 8.178 7.648 7.151 6.487 5.586 4.888 3.727 2.429

249.08 253.15 258.29 264.55 269.83 275.23 281.13 285.92 289.60 292.15b 290.22 284.32

10.837 11.114c 10.795 10.627 10.167 9.577 8.780 7.730 6.428 4.667 3.405 2.102

a

Standard uncertainty (u) values are u(T) = 0.02 K and u(P) = 0.01 MPa for P < 5.5 MPa and u(P) = 0.025 MPa for P > 5.5 MPa. bThe cricondentherm. cThe cricondenbar.

of other hydrocarbon components (C2H6, C3+). The reason might be that CH4 has a lower boiling point, which means that the sample containing a higher concentration of CH4 does not easily have liquid dropout occurring at a given pressure. As for the influence of each component in the samples on the cricondenbar, a similar variation tendency was observed. Voulgaris et al.41 investigated the relationship between the natural gas composition and the risk of condensation, and they believe that an increase in the CH4 concentration in a natural gas can decrease the risk of condensation for a given pressure value because it increases the heavy component solubility in the vapor phase when the gas−liquid equilibrium was established. By comparing the dew points of the samples not containing n-C6, it was observed that the cricondentherm decreased by 22 K when the concentration of n-C5 decreased by 0.98 mol %. For the samples containing n-C6, the cricondentherm decreased by 27 K when the concentration of n-C6 decreased by 0.46 mol %. Correspondingly, the cricondenbar decreased by 1.9 and 2.7 MPa when the n-C5 and n-C6 concentrations undergo these changes. The reason might be that n-C6 has a higher boiling point than n-C5, which leads to the samples containing n-C6 undergoing liquid hydrocarbon condensation

region under the cricondentherm, the HDP pressure increases as the temperature increases. It was meaningless to test the HDP in the region between the critical point and the cricondenbar because the HDP temperature in this region is very low and the pipeline transmission pressure is usually above the HDP line. Using the experimental procedures mentioned above, the HDP pressures of eight gas samples (SNG2−9) were measured systematically. Tables 3 and 4 show the HDP measured results for which the experimental temperature ranged from 234.5 to 295.35 K and the pressure ranged from 1.706 to 11.495 MPa. The dew point of SNG1 was not tested because its HDP temperature is very low and the experiments under 223.15 K are difficult to be performed using this apparatus. By analyzing the results, it can be seen that SNG2 and SNG3 exhibited the widest vapor−liquid phase region. It is obvious that the width of the vapor−liquid phase region mainly depends on the cricondentherm and cricondenbar points of corresponding samples. The influence of each component in the samples on the cricondentherm and cricondenbar was investigated. It was observed that the cricondentherm measured values showed a decreasing trend with the increasing in the CH4 concentration; however, it presents an increasing trend with the increasing concentrations D



Article

Table 5. Equation of State and Mixing Rules Used in This Studya EOS SRK PR

α-function

PVT relation

P=

RT v−b

−

acα(Tr) v(v + b)

P=

RT v−b

−

acα(Tr) v(v + b) + b(v − b)

α = [1 + m(1 −

mixing rules

Tr )]2

a = ∑i ∑j xixj(aiaj)0.5 (1 − kij) n

b = ∑i = 1 xibi

a

P is the pressure, T is the temperature, R is the universal gas constant, Tr is the reduced temperature, v is the molar volume, ac is the attractive parameter at the critical temperature, α is the attractive parameter temperature dependence or the α-function, b is the van der Waals co-volume, m is a function of the acentric factor, x is the liquid/vapor mole fraction, and kij represents the binary interaction parameters.

Table 6. Parameters Used in SRK and PR EOSsa ac

EOS SRK PR

ac =

b

R2T 2 0.42747 P c c

ac = 0.45724

R2Tc 2 Pc

b=

m

RT 0.08664 P c c

b = 0.07780

RTc Pc

m = 0.480 + 1.574ω − 0.176ω2 m = 0.37464 + 1.54226ω − 0.26992ω2

a ac is the attractive parameter at the critical temperature, b is van der Waals covolume, m is a function of the acentric factor, Pc is critical pressure, Tc is critical temperature, ω is the acentric factor.

Figure 5. Comparison of predicted and measured values for the samples not containing n-C6.

more easily at a given pressure. It can be seen that the existence of small amounts of n-C5 or n-C6 can dramatically enlarge the pressure and temperature ranges of liquid dropout, leading to an increasing risk of natural gas transportation. Considering that the cricondentherm was significantly decreased when the small fraction of the heavy component (for example, n-C5 or n-C6+) was removed from the rich gas, in industry, the heavy hydrocarbon can be absorbed with lowvolatility oil before proceeding with pipeline transmission,

which would lower the risk of rich gas transportation in the pipeline. 3.3. HDP Prediction by the Equation of State. For HDP calculations with the GC-EOS method, an important influencing factor for accurate results is GC analysis. Brown et al.14 compared HDP predictions with the same EOS but different types of GC and was found that this can result in a discrepancy of up to 2 K due to the GC accuracy. Another influencing factor is the performance of EOS used for E



Article

Figure 6. Comparison of predicted and measured values for the samples containing n-C6.

prediction. The SRK and PR EOSs are extensively used to calculate the thermodynamic properties of natural gas, although various modifications were made by some researchers to improve their accuracy.42−52 In this study, the original SRK and PR EOSs coupled with the classical van der Waals mixing rules (Table 5) were examined to predict the dew points of gas mixtures. The parameters used in the two EOSs are given in Table 6, and the calculations with the EOS were performed using zero binary interaction parameters (BIP) because it was reported that the application of BIP does not necessarily improve the dew point predictions unless the mixtures have a high concentration of N2 or CO2.14,28 Comparisons of predictions and measurements for eight SNG samples are shown in Figures 5 and 6. Here, the dew point temperature values are calculated by means of the above two models using the experimental pressure and SNG composition. It can be seen that the PR prediction exhibited good agreement with the experimental data, while the SRK calculation evidently deviated from the measured values. This indicated that the choice of thermodynamic model has a significant influence on the HDP predicting precision. It was observed that the HDP temperatures predicted by the PR and SRK EOSs are slightly higher than the measured values. The average absolute deviations (AAD %) of HDP temperatures predicted by the two models are calculated and listed in Table 7, and it was found that the AAD % values of PR and SRK predictions are within 0.79−1.53% and 2.81−4.51%, respectively (the total average absolute deviations of PR and SRK

Table 7. HDP Average Absolute Deviations for Eight Samples Using EOSsa,b AAD%

a

sample

N

SRK

PR

SNG2 SNG3 SNG4 SNG5 SNG6 SNG7 SNG8 SNG9 total

14 11 12 13 12 12 11 12 97

4.19 3.76 4.27 2.81 4.33 3.34 4.51 3.22 3.68

0.87 1.53 0.79 1.06 1.01 1.23 0.92 0.98 1.01

N is the number of experimental data points. AAD% is the average

absolute deviation, AAD% =

100 N

N

∑n = 1

|Tnexp − Tnpre| b . The Tnexp

standard

uncertainty u is u(AAD%) = 0.01.

predictions are 1.01 and 3.68%, respectively), which also demonstrated that the performance of PR is better than that of SRK in predicting the HDP. In addition, the deviations between the predicted cricondentherm or cricondenbar and the measured values are shown in Table 8. Here, the cricondenbar predicted values are calculated by the two models with the experimental temperatures and SNG composition, while the cricondentherm predicted values are calculated with the measured pressures and SNG composition. It can be observed that the maximum deviations of the F



Article

(2) Tagliabue, M.; Farrusseng, D.; Valencia, S.; Aguado, S.; Ravon, U.; Rizzo, C.; Corma, A.; Mirodatos, C. Natural gas treating by selective adsorption: material science and chemical engineering interplay. Chem. Eng. J. 2009, 155, 553−566. (3) Bernardo, P.; Drioli, E.; Golemme, G. Membrane gas separation: A review/state of the art. Ind. Eng. Chem. Res. 2009, 48, 4638−4663. (4) Yang, Y.; Wen, C.; Wang, S.; Feng, Y.; Witt, P. The swirling flow structure in supersonic separators for natural gas dehydration. RSC Adv. 2014, 4, 52967−52972. (5) Bahadori, A.; Vuthaluru, H. B. Simple methodology for sizing of absorbers for TEG (triethylene glycol) gas dehydration systems. Energy 2009, 34, 1910−1916. (6) Bahadori, A.; Vuthaluru, H. B. Rapid estimation of equilibrium water dew point of natural gas in TEG dehydration systems. J. Nat. Gas Sci. Eng. 2009, 1, 68−71. (7) Caputo, F.; Cascetta, F.; Lamanna, G.; Rotondo, G.; Soprano, A. Estimation of the damage in a natural gas flow line caused by the motion of methane hydrates. J. Nat. Gas Sci. Eng. 2015, 26, 1222− 1231. (8) Hammerschmidt, E. G. Formation of Gas Hydrates in Natural Gas Transmission Lines. Ind. Eng. Chem. 1934, 26, 851−855. (9) Sloan, E. D.; Koh, C. A. Clathrate Hydrates of Natural Gases, 3rd ed.; CRC Press-Taylor & Francis: New York, 2008. (10) Gonfa, G.; Bustam, M. A.; Sharif, A. M.; Mohamad, N.; Ullah, S. Tuning ionic liquids for natural gas dehydration using COSMO-RS methodology. J. Nat. Gas Sci. Eng. 2015, 27, 1141−1148. (11) Shi, L.; Wang, C.; Zou, C. Corrosion failure analysis of L485 natural gas pipeline in CO2 environment. Eng. Failure Anal. 2014, 36, 372−378. (12) Galatro, D.; Marín-Cordero, F. Considerations for the dew point calculation in rich natural gas. J. Nat. Gas Sci. Eng. 2014, 18, 112−119. (13) Mokhatab, S.; Poe, W. Handbook of Natural Gas Transmission and Processing, 2nd ed.; Gulf Professional Publishing, 2012. (14) Brown, A. S.; Milton, M. J. T.; Vargha, G. M.; Mounce, R.; Cowper, C. J.; Stokes, A. M. V.; Benton, A. J.; Lander, D. F.; Ridge, A.; Laughton, A. P. Measurement of the Hydrocarbon Dew Point of Real and Synthetic Natural Gas Mixtures by Direct and Indirect Methods. Energy Fuels 2009, 23, 1640−1650. (15) Baker, C. J.; Hughes, T. J.; Graham, B. F.; Marsh, K. N.; May, E. F. Rapid hydrocarbon dew points by infrared spectroscopy: Results and validation for binary mixtures of methane + {propane, isobutane and butane}. J. Ind. Eng. Chem. 2018, 58, 304−310. (16) Skylogianni, E.; Novak, N.; Louli, V.; Pappa, G.; Boukouvalas, C.; Skouras, S.; Solbraa, E.; Voutsas, E. Measurement and prediction of dew points of six natural gases. Fluid Phase Equilib. 2016, 424, 8− 15. (17) Mørch, Ø.; Nasrifar, K.; Bolland, O.; Solbraa, E.; Fredheim, A. O.; Gjertsen, L. H. Measurement and modeling of hydrocarbon dew points for five synthetic natural gas mixtures. Fluid Phase Equilib. 2006, 239, 138−145. (18) Valiollahi, S.; Kavianpour, B.; Raeissi, S.; Moshfeghian, M. A new Peng-Robinson modification to enhance dew point estimations of natural gases. J. Nat. Gas Sci. Eng. 2016, 34, 1137−1147. (19) Avila, S.; Benito, A.; Berro, C.; Blanco, S. T.; Otín, S.; Velasco, I. Dew-Point Curves of Natural Gas. Measurement and Modeling. Ind. Eng. Chem. Res. 2006, 45, 5179−5184. (20) Avila, S.; Blanco, S. T.; Velasco, I.; Rauzy, E.; Otín, S. Thermodynamic Properties of Synthetic Natural Gases. Part 1. Dew Point Curves of Synthetic Natural Gases and their Mixtures with Water and Methanol. Measurement and Correlation. Ind. Eng. Chem. Res. 2002, 41, 3714−3721. (21) Jarne, C.; Avila, S.; Blanco, S. T.; Rauzy, E.; Otín, S.; Velasco, I. Thermodynamic Properties of Synthetic Natural Gases. 5. Dew Point Curves of Synthetic Natural Gases and Their Mixtures with Water and with Water and Methanol: Measurement and Correlation. Ind. Eng. Chem. Res. 2004, 43, 209−217. (22) Blanco, S. T.; Avila, S.; Velasco, I.; Rauzy, E.; Otín, S. Dew points of ternary methane+ethane+butane and quaternary methane

Table 8. Deviations between Experimental and Predicted Values on the Crincondentherm and Cricondenbara,b experimental

SRK

PR

sample

Tcir/K

Pcir/MPa

ΔT/K

ΔP/MPa

ΔT/K

ΔP/MPa

SNG2 SNG3 SNG4 SNG5 SNG6 SNG7 SNG8 SNG9

292.15 295.35 270.25 280.15 288.45 276.15 267.43 292.15

10.882 11.495 9.172 9.954 10.608 9.567 8.647 11.114

2.05 2.52 1.95 2.32 2.09 2.45 2.51 2.68

0.362 0.230 0.233 0.338 0.349 0.210 0.269 0.293

0.20 0.20 0.10 0.50 0.20 0.20 0.32 0.10

0.121 0.129 0.004 0.101 0.108 0.109 0.028 0.060

Tcir is the crincondentherm, Pcir is the cricondenbar, ΔT = |Tpred cir − pred exp b Texp cir |, and ΔP = |Pcir − Pcir |. Standard uncertainty (u) values are u(Tcri) = 0.02 K, u(Pcri) = 0.025 MPa, u(ΔT) = 0.02 K, and u(ΔP) = 0.025 MPa. a

cricondentherm and cricondenbar values predicted by the SRK EOS are 2.68 K and 0.362 MPa, respectively, while they are 0.50 K and 0.129 MPa, respectively, for the PR predictions. It can be seen that from these results the original PR EOS combined with the van der Waals mixing rules can essentially meet the calculation needs.

4. CONCLUSIONS The hydrocarbon dew points of eight SNG samples are measured, and the results are used to evaluate the performance of the thermodynamic models: SRK and PR EOSs. The experimental data are obtained using a transparent highpressure sapphire cell and cover a temperature range from 234.5 to 294.35 K and a pressure range from 1.706 to 11.495 MPa. It was observed that the cricondentherm showed a decreasing trend with increasing CH4 concentration; however, it presents an increasing trend with increases in the concentrations of the other hydrocarbon components (C2H6 and C3+). For the influence of each component on the cricondenbar, similar variation tendencies were observed. The cricondentherm decreased by 22 K when the n-C5 concentration decreased by 0.98 mol %, and it decreased by 27 K when the n-C6 concentration decreased by 0.46 mol %. Correspondingly, the cricondenbar decreased by 1.9 and 2.1 MPa, respectively. In industry, heavy hydrocarbons can be absorbed with low-volatility oil before proceeding with pipeline transmission, which would lower the risk for rich gas transportation in the pipeline. The PR prediction showed good agreement with the experimental data, and the average absolute deviations were within 0.79−1.53% while the SRK prediction deviated significantly from the measured values.

■

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel: +86-0591-22865220. Fax: 86-0591-22865220. ORCID

Liang Mu: 0000-0002-2898-3999 Notes

The authors declare no competing financial interest.

■

REFERENCES

(1) Netusil, M.; Ditl, P. Comparison of three methods for natural gas dehydration. J. Nat. Gas Chem. 2011, 20, 471−476. G



Article

+ethane+butane+water mixtures: measurement and correlation. Fluid Phase Equilib. 2000, 171, 233−242. (23) Redlich, O.; Kwong, J. N. S. On the Thermodynamics of Solutions. V. An Equation of State. Fugacities of Gaseous Solutions. Chem. Rev. 1949, 44, 233−244. (24) Peng, D. Y.; Robinson, D. B. A New Two-Constant Equation of State. Ind. Eng. Chem. Fundam. 1976, 15, 59−64. (25) Nasrifar, K.; Bolland, O.; Moshfeghian, M. Predicting Natural Gas Dew Points from 15 Equations of State. Energy Fuels 2005, 19, 561−572. (26) Nasrifar, K.; Bolland, O. Prediction of thermodynamic properties of natural gas mixtures using 10 equations of state including a new cubic two-constant equation of state. J. Pet. Sci. Eng. 2006, 51, 253−266. (27) Patel, N. C.; Teja, A. S. A new cubic equation of state for fluids and fluid mixtures. Chem. Eng. Sci. 1982, 37, 463−473. (28) Louli, V.; Pappa, G.; Boukouvalas, C.; Skouras, S.; Solbraa, E.; Christensen, K. O.; Voutsas, E. Measurement and prediction of dew point curves of natural gas mixtures. Fluid Phase Equilib. 2012, 334, 1−9. (29) Jaubert, J. N.; Mutelet, F. VLE predictions with the PengRobinson equation of state and temperature dependent kij calculated through a group contribution method. Fluid Phase Equilib. 2004, 224, 285−304. (30) Louli, V.; Boukouvalas, C.; Voutsas, E.; Magoulas, K.; Tassios, D. Application of the UMR-PRU model to multicomponent systems: Prediction of the phase behavior of synthetic natural gas and oil systems. Fluid Phase Equilib. 2007, 261, 351−358. (31) Mathias, P. M.; Copeman, T. W. Extension of the PengRobinson equation of state to complex mixtures: Evaluation of the various forms of the local composition concept. Fluid Phase Equilib. 1983, 13, 91−108. (32) Sun, C. Y.; Liu, H.; Yan, K. L.; Ma, Q. L.; Liu, B.; Chen, G. J.; Xiao, X. J.; Wang, H. Y.; Zheng, X. T.; Li, S. Experiments and Modeling of Volumetric Properties and Phase Behavior for Condensate Gas under Ultra-High-Pressure Conditions. Ind. Eng. Chem. Res. 2012, 51, 6916−6925. (33) Liu, H.; Sun, C. Y.; Yan, K. L.; Ma, Q. L.; Wang, J.; Chen, G. J.; Xiao, X. J.; Wang, H. Y.; Zheng, X. T.; Li, S. Phase behavior and compressibility factor of two China gas condensate samples at pressures up to 95 MPa. Fluid Phase Equilib. 2013, 337, 363−369. (34) Elsharkawy, A. M. Predicting the dew point pressure for gas condensate reservoirs: empirical models and equations of state. Fluid Phase Equilib. 2002, 193, 147−165. (35) Soave, G. Equilibrium constants from a modified RedlichKwong equation of state. Chem. Eng. Sci. 1972, 27, 1197−1203. (36) Mei, D. H.; Liao, J.; Yang, J. T.; Guo, T. M. Experimental and Modeling Studies on the Hydrate Formation of a Methane + Nitrogen Gas Mixture in the Presence of Aqueous Electrolyte Solutions. Ind. Eng. Chem. Res. 1996, 35, 4342−4347. (37) Zhang, Q.; Chen, G. J.; Huang, Q.; Sun, C. Y.; Guo, X. Q.; Ma, Q. L. Hydrate Formation Conditions of a Hydrogen + Methane Gas Mixture in Tetrahydrofuran + Water. J. Chem. Eng. Data 2005, 50, 234−236. (38) Zhang, L. W.; Huang, Q.; Sun, C. Y.; Ma, Q. L.; Chen, G. J. Hydrate Formation Conditions of Methane + Ethylene + Tetrahydrofuran + Water Systems. J. Chem. Eng. Data 2006, 51, 419−422. (39) Mei, D. H.; Liao, J.; Yang, J. T.; Guo, T. M. Hydrate Formation of a Synthetic Natural Gas Mixture in Aqueous Solutions Containing Electrolyte, Methanol, and (Electrolyte + Methanol). J. Chem. Eng. Data 1998, 43, 178−182. (40) Zhang, S. X.; Chen, G. J.; Ma, C. F.; Yang, L. Y.; Guo, T. M. Hydrate Formation of Hydrogen + Hydrocarbon Gas Mixtures. J. Chem. Eng. Data 2000, 45, 908−911. (41) Voulgaris, M. E.; Peters, C. J.; Arons, J. S. On the Retrograde Condensation Behavior of Lean Natural Gas. Int. J. Thermophys. 1995, 16, 629−642. (42) Danesh, A.; Xu, D. H.; Tehrani, D. H.; Todd, A. C. Improving predictions of equation of state by modifying its parameters for super

critical components of hydrocarbon reservoir fluids. Fluid Phase Equilib. 1995, 112, 45−61. (43) Nasrifar, K.; Bolland, O. Square-Well Potential and a New α Function for the Soave-Redlich-Kwong Equation of State. Ind. Eng. Chem. Res. 2004, 43, 6901−6909. (44) Graboski, M. S.; Daubert, T. E. A Modified Soave Equation of State for Phase Equilibrium Calculations. 1. Hydrocarbon Systems. Ind. Eng. Chem. Process Des. Dev. 1978, 17, 443−448. (45) Soave, G. Improving the treatment of heavy hydrocarbons by the SRK EOS. Fluid Phase Equilib. 1993, 84, 339−342. (46) Souahi, F.; Sator, S.; Albane, S. A.; Kies, F. K.; Chitour, C. E. Development of a new form for the alpha function of the RedlichKwong cubic equation of state. Fluid Phase Equilib. 1998, 153, 73−80. (47) Twu, C. H.; Coon, J. E.; Cunningham, J. R. A new generalized alpha function for a cubic equation of state Part 2. Redlich-Kwong equation. Fluid Phase Equilib. 1995, 105, 61−69. (48) Stryjek, R.; Vera, J. H. PRSV: An improved Peng-Robinson equation of state for pure compounds and mixtures. Can. J. Chem. Eng. 1986, 64, 323−333. (49) Gasem, K. A. M.; Gao, W.; Pan, Z.; Robinson, R. L., Jr A modified temperature dependence for the Peng-Robinson equation of state. Fluid Phase Equilib. 2001, 181, 113−125. (50) Jaubert, J. N.; Privat, R. Relationship between the binary interaction parameters (kij) of the Peng-Robinson and those of the Soave-Redlich-Kwong equations of state: Application to the definition of the PR2SRK model. Fluid Phase Equilib. 2010, 295, 26−37. (51) Twu, C. H.; Coon, J. E.; Cunningham, J. R. A new generalized alpha function for a cubic equation of state Part 1. Peng-Robinson equation. Fluid Phase Equilib. 1995, 105, 49−59. (52) Flöter, E.; Loos, T. W.; Arons, J. S. Improved Modeling of the Phase Behavior of Asymmetric Hydrocarbon Mixtures with the PengRobinson Equation of State Using a Different Temperature Dependency of the Parameter a. Ind. Eng. Chem. Res. 1998, 37, 1651−1662.

H


Measurement and Prediction of Hydrocarbon Dew Points of Synthetic

Recommend Documents