Category: Gas Processing

In facilities operations the understanding of where the process is on a phase diagram can often help the engineer and operator avoid extremely embarrassing design and operating mistakes. The oil and gas industry is full of many “war stories” about “phase diagram disasters.” Most instances are never related back to the phase diagram misunderstanding. In one well-documented but poorly published case a “dry gas” pipeline that was pigged flooded miles of sandy beach. In another case thousands of kilowatts of compression power were installed to maintain the pressure of a reservoir above the dew point when in fact the reservoir was at a temperature above the cricondentherm. In many cases equipment manufacturers and purchasers of gas have specifications of “superheat” or dew point that have not been met and led to upset customers and/or millions of dollars of lawsuits.

One of the first issues to be resolved by a facilities engineer working in a gas plant or gas production facility is where is the process operating with respect to the phase diagram. A general knowledge, if not a detailed knowledge, will allow the design engineer and the facilities operator to make intelligent decisions that have significant impact on the profitability of a gas production facility.

The following figure is a “generic hydrocarbon mixture” phase diagram for a lean gas. The area to the left of the Bubble Point line is the sub-cooled liquid region.

The area to the right of the Dew Point line is the super-heated gas region. Between these two lines the mixture is two-phase. Other areas of interest are the retrograde region and the supercritical region. Each of these regions provides advantages and disadvantages for operations.

This month we will start to define the points of interest so that we may choose proper operating points for various types of processes. The first point to define is the cricondentherm. The definition of this point is the highest temperature at which twophases (liquid and vapor for most processes) can coexist. In Figure 1, this is point M. Point M has considerable theoretical and practical importance. For example, if the cricondentherm for a sales gas (point M) is 0 ºC (32 ºF) cooling the gas to 4 ºC (40 ºF) at any pressure will not result in condensation of liquids. This type of operation is typically the type used for cross-country transportation of gas in pipelines. Operation with this type of system will not require “slug catchers” at the end of the pipeline and will significantly decrease pressure drop in the pipeline.

If the gas were processed in a cold separator such that point B (a dew point) was 0 ºC (32 ºF) problems could occur in the same conditions as the pipeline mentioned above. If the pressure of the pipeline was between the pressure of point B and F and the pipeline cooled to 4 ºC (40 ºF) there could be significant quantities of liquid in the pipeline. If the operations people were not familiar with the phase diagram they might increase the operating pressure of the cold separator and still keep the temperature at 0 ºC (32 ºF). This action would result in increased liquids in the pipeline, not decreased. However, if the cold separator was operated at the pressure of point M, at a temperature of 0 ºC (32 ºF), in theory there would be no liquids in the pipeline again. (More about the difference between theory and practice in future tips).

To learn more about similar cases and how to minimize operational problems, we suggest attending our G4 (Gas Conditioning and Processing) and G5 (Gas Conditioning and Processing – Special) courses.

Dr. Larry L. Lilly

In order to continue the last tip of the month’s discussion on MEG injection plant, in this “Tip of the Month”, we will focus on two more questions:

1. Does MEG have any dehydration ability at the three phase cold separator condition of a typical mechanical refrigeration plant?
2. What is the dehydration ability of MEG if the mechanical refrigeration in a typical MEG injection plant goes out of service?

As described in the last tip of the month, a typical mechanical refrigeration process is used for hydrocarbon dew point control and moderate NGL recovery that uses MEG injection to prevent hydrate formation. Warm inlet gas is cross-exchanged with the cold dry sales gas and then flows to the gas chiller. To prevent hydrates from forming, MEG is injected in the tubes at the warm end of both exchangers. The temperature of the chiller is adjusted to condense liquids from the feed gas. The cold gas exiting the chiller together with the rich MEG solution and condensed hydrocarbons enters the cold three-phase separator. The rich MEG is sent to the regeneration section of the unit where the water is removed. The resulting lean MEG is sent back to the process. In short, two things are taking place: temperature reduction of the process gas to condense both water and hydrocarbons; and, MEG injection and subsequent regeneration to prevent hydrates from forming. In this scheme, the sales gas exiting the gas-to-gas exchanger has a water and hydrocarbon dew point determined by the operating temperature of the cold separator. The key point to remember here is that the water is being removed from the gas by low temperature condensation. The purpose of the injected MEG is not to “dehydrate” the gas but to prevent formation of hydrates. For more detail, refer to chapters 6 and 16 of Gas Conditioning and Processing, Volumes 1 and 2, [1, 2] respectively.

Question 1: Does MEG have any dehydration ability at the three phase cold separator condition of a typical mechanical refrigeration plant?

In order to answer this question, first we determine the water dew point temperature without any MEG injection and compare the results with the case of 80 weight percent lean MEG injection. Let’s assume a typical natural gas, cold separator pressure of 40 bara and -20°C [580 psia & -4°F] with 10 weight dilution (i.e. rich MEG concentration of 70 weight %). By performing computer simulation using ProMax [3], the water dew point temperature:

• without MEG injection is -22.7°C (-8.7°F) corresponding to water content of 30.72 kg/106 std m3 [1.94 lbm/MMSCF]
• with MEG injection is -29.6°C (-21.2°F) corresponding to water content of 17.6 kg/106 std m3 (1.11 lbm/MMSCF)

Therefore, the water dew point temperature depression is 6.9°C (12.4°F). Similarly, a water dewpoint temperature depression of 7.8°C [14°F] was obtained for the case of 5 weight percent MEG dilution (i.e. rich MEG concentration of 75 weight %). These results indicate that even at low temperature, in addition to the hydrate inhibition effect, MEG has the ability to do partial dehydration. It should be noted that for this gas the hydrate formation temperature at 40 bara [580 psia] is 14.9°C [58.7°F].

Question 2: What is the dehydration ability of MEG if the mechanical refrigeration in a typical MEG injection plant unexpectedly goes out of service?

Let’s assume the same gas as in question 1 is passing through a mechanical refrigeration system with the same chiller temperature of -20°C [-4°F]. Let’s also assume that due to the break down of mechanical refrigeration system (lack of chilling) the cold separator temperature reaches 21.1°C [70°F]. Again, we used ProMax to perform the simulations and the calculated results are plotted in Figures 1 (A&B) and 2 (A&B). Figure 1 (A&B) presents the effect of lean MEG circulation rate on water dew point temperature and water content. Figure 2 (A&B) indicates that for a 10 weight % dilution, about 4350 kg MEG solution per 106 std m3 [270 lbm MEG solution per MMSCF] of gas is required. Figure 2 (A&B) also indicates that for this amount of dilution, the water dew point temperature drops from 21.1°C [70°F] to about 12.2°C [54°F] and the corresponding water content drops from 567 to 325 kg/106 std m3 [35 to 21 lbm/MMSCF]. Again, it can be seen that the MEG can dehydrate natural gas partially at higher temperature. It is also interesting to see from Figures 1 and 2 that further increase in lean MEG solution circulation rate, beyond 4350 kg/106 std m3 [270 lbm/MMSCF], does not reduce the water dewpoint temperature considerably and; therefore, it justifies the rule of thumb for 10 weight % dilution.

For more information about dehydration and hydrate inhibition, the reader should refer to JMC books and enroll in our G4 (Gas Conditioning and Processing) and G5 (Gas Conditioning and Processing – Special) courses.

By Dr. Mahmood Moshfeghian

References:

1. Campbell, J. M. “Gas conditioning and processing, Volume 1: Basic Principles,” 8th Ed., John M. Campbell and Company, Norman, Oklahoma, USA, 2001.
2. Campbell, J. M. “Gas conditioning and processing, Volume 2: The Equipment Modules,” 8th Ed., John M. Campbell and Company, Norman, Oklahoma, USA, 2000.
3. ProMax, version 1.2, Bryan Research & Engineering Inc, Bryan, Texas, 2005.

In this “Tip of the Month”, we will focus on the question of: Which technology should you choose? The answer, of course, is “It depends.” It depends on what you are trying to accomplish, the constraints imposed on your system and the relative economics.

A Rule of Thumb is “Use MEG injection if you have to cool the gas for NGL recovery anyway.” Like all Rules of Thumb, there are exceptions. But let’s explore the basics of each technology.

Let’s begin by defining our terms. See Figure 1 for a typical mechanical refrigeration process used for hydrocarbon dew point control and moderate NGL recovery that uses MEG injection to prevent hydrate formation. Warm inlet gas is cross-exchanged with the cold dry sales gas and then flows to the gas chiller. To prevent hydrates from forming, MEG is injected in the tubes at the warm end of both exchangers. The temperature of the chiller is adjusted to condense liquids from the feed gas. The cold gas exiting the chiller together with the rich MEG solution and condensed hydrocarbons enters the cold three-phase separator. The rich MEG is sent to the regeneration section of the unit where the water is removed. The resulting lean MEG is sent back to the process.

Copyright © 2007 John M. Campbell and Company

Figure 1. Typical mechanical refrigeration plant with glycol injection system [1]

In this flow diagram, two things are taking place: temperature reduction of the process gas to condense both water and hydrocarbons; and, MEG injection and subsequent regeneration to prevent hydrates from forming. Inspection of Figure 1 reveals the majority of the equipment, including the refrigeration compressors, etc. which are not shown, is employed to reduce the temperature. Besides mechanical refrigeration, other options to achieve the required gas cooling include JT – valve expansion or use of a turboexpander. For either of these options, the MEG injection and regeneration portion of this plant is minor by comparison.

In this scheme, the sales gas exiting the gas-to-gas exchanger has a water and hydrocarbon dew point determined by the operating temperature of the cold separator. The CAPEX of this system is essentially driven by the gas cooling equipment, including the refrigeration system. The key point to remember here is that the water is being removed from the gas by low temperature condensation. The purpose of the injected MEG is not to “dehydrate” the gas but to prevent formation of hydrates. At the MEG concentrations normally used in these systems, approximately 80 – 85 wt%, the MEG absorbs only a small amount of water vapor from the gas.

Let’s now look at a typical circulating TEG system. See Figure 2. The same rich, water saturated natural gas stream flows to a properly sized inlet separator to remove liquids. The gas then enters a glycol contactor equipped with either structured packing or bubble cap trays. As the gas rises, the water is removed by the falling TEG. The concentration of the lean glycol entering the top of the contactor is the main variable that determines the water dew point specification that can be made. The rich glycol that leaves the glycol contactor is sent to a flash drum and then to a regeneration section. The lean glycol leaving the regenerator is then returned to the contacting tower.

In this system, we are only making water dew point specification gas. The NGL content/hydrocarbon dew point of the sales gas is the same as that of the feed gas. Circulating TEG systems are therefore used only for dehydration. A significant cost item for the circulating TEG system is the high pressure contacting tower.

Now let’s explore how we can compare and contrast these two technologies.

If your objective is to make only pipeline water specification gas, you will most likely choose a circulating TEG system. This is intuitively obvious from a comparison of the two flow diagrams cited above. Assume, for example, that you want to dehydrate a lean natural gas stream that is water saturated at 70 bar and 40°C. A quick comparison of Figures 1 and 2 shows that there is much more equipment associated with chilling the feed gas (Figure 1 + the refrigeration compressors, etc. that are not shown) then there is with a circulating TEG system (Figure 2). Hence, for dehydration only to pipeline water specifications, a circulating TEG system will almost always be selected.

On the other hand, if your objective is to recover hydrocarbons and remove water simultaneously, then a low – temperature process with MEG injection may be the best choice. Assume you have a rich natural gas stream that is water saturated at 70 bar and 40°C. Assume a mechanical refrigeration process is selected for hydrocarbon liquids recovery with a cold temperature of -35°C. We have two options to consider: we can dehydrate the gas with a circulating TEG system to a water dew point of -35°C and then send the dehydrated gas to an LTS plant consisting of a gas-to-gas exchanger, chiller, refrigeration system, etc., but with no MEG injection/regeneration system; or, we can send the feed gas directly to the LTS plant which has an MEG injection system retrofitted to prevent hydrates from forming.

Copyright © 2007 John M. Campbell and Company

Figure 2. Basic glycol dehydration unit [2]

Since the underlying equipment required to recover NGL’s is the same in both options, the cost comparison is essentially between the circulating TEG system and the MEG injection system. The TEG system will use less circulating rates then the MEG system, but will likely have a higher regeneration duty. Achieving the large dew point depression of 75°C with a circulating TEG system will be challenge and will add to the system cost. The key difference, however, is the circulating TEG system requires a high pressure contactor while the MEG injection system does not. In this situation, the most likely choice will be to go with the MEG Injection system.

For more information about dehydration and hydrate inhibition, the reader should refer to JMC books and enroll in our G4 (Gas Conditioning and Processing) and G5 (Gas Conditioning and Processing – Special) courses.

By Harvey M. Malino and Mark Bothamley

References:

1. Campbell, J. M. “Gas conditioning and processing, Volume 1: Basic Principles,” 8th Ed., John M. Campbell and Company, Norman, Oklahoma, USA, 2001.
2. Campbell, J. M. “Gas conditioning and processing, Volume 2: The Equipment Modules,” 8th Ed., John M. Campbell and Company, Norman, Oklahoma, USA, 2000.

In the last two “Tip of the Month” we briefly discussed the importance of liquid density for process simulation and equipment design. Three different methods were introduced to compute liquid density. The methods were (a) charts and monographs, (b) correlations and (c) EoS or volume translated EoS. We also presented a comparison between accuracy of different correlations and EoS methods and provided guidelines for using correlations.

In this “Tip of the Month”, we will present a comparison between accuracy of HYSYS [1] and ProMax [2] process simulation packages which normally use correlations for liquid density calculations. For HYSYS we used the “Smooth Liquid Density” option and in ProMax there are two options of COSTALD [3, 4] and Rackett [5] but we only used the COSTAD method for the reasons discussed in the last tip of the month. Both of these methods are discussed in Chapter 3 of JMC Volume 1 of Gas Conditioning and Processing Book [6]. The focus will be on the mixture of light hydrocarbons which have wider applications in gas industry. We will provide guidelines to use these process simulation programs effectively. In this study we have used the experimental data reported in GPA Research Report RR-147 [7].

We predicted the saturated liquid density of the ethane-propane mixture for the conditions reported in the GPA research report using the default option of HYSYS and ProMax. For the default option for each set of experimental conditions, we entered temperature, pressure, composition and total number of moles (100 moles was used for all cases). In Figure 1, the predicted results for 90 points are plotted as a function of the experimental values.

As can be seen in this figure, for several points the errors are very large. These large errors are due to the fact that for these points the process simulators predict partially vaporized systems and the reported densities are for a two phase mixture and not for the actual liquid mixture as reported experimentally. Therefore, we performed a flash calculation for each experimental point, separated the gas from the feed and predicted the density for the resulting liquid stream and re-plotted the results in Figure 2. This causes some changes in composition but Figure 2 indicates that considerable improvement in accuracy is obtained by degassing the feed stream.

Since the reported experimental data were at saturated liquid conditions, a second option is to predict the liquid density using the bubble point option. For this option, we entered temperature, vapor fraction of zero, composition of components, and 100 moles for total feed. By performing bubble point calculation, the liquid density and bubble point pressure were calculated. Figures 3 and 4 show the accuracy of HYSYS and ProMax in predicting the liquid densities and bubble point pressures, respectively. Again, quite an improvement is obtained by performing bubble point calculation to obtain the liquid density.

We repeated similar calculations for propane-normal butane and normal butane-normal pentane mixtures and have summarized in Table 1 the error analysis for different options using the simulation softwares.

Table 1 indicates that if the default option of HYSYS and ProMax are used, the calculated liquid density may contain a large error. On the other hand, when the mixture was flashed and the vapor was removed the calculated density was more accurate. Finally, calculating the liquid density using bubble point calculation yields more accurate density; however, the pressure may deviate slightly from the specified system pressure. The deviation of pressure does not cause a major concern because the pressure effect on liquid properties is not that much and more often it is ignored.

To learn more about liquid density and its impact on facilities calculation, design and surveillance, refer to JMC books and enroll in our G4 (Gas Conditioning and Processing) and G5 (Gas Conditioning and Processing – Special) courses.

By Dr. Mahmood Moshfeghian

Reference:

1. HYSYS, version 2004.2, Aspen Technology Inc., Cambridge, Massachusetts, 2005.
2. ProMax, version 1.2, Bryan Research & Engineering Inc, Bryan, Texas, 2005.
3. Hankinson, R. W.; Thomson, G. H. A new correlation for saturated densities of liquids and their mixtures. AIChE J. 1979, 25, 653.
4. Thomson, G. H.; Brobst, K. R.; Hankinson, R. W. An improved correlation for densities of compressed liquids and liquid mixtures. AIChE J., 28, 671, 1982
5. Rackett, H. G. Equation of state for saturated liquids. J. Chem. Eng. Data, 15, 514, 1970
6. Campbell, J. M. “Gas conditioning and processing, Volume 1: Fundamentals,” John M. Campbell and Company, Norman, Oklahoma, USA, 2001.
7. Holcomb, C.D., Magee, J.W., and W.M. Haynes, “Density Measurements on Natural Gas Liquids,” Gas Processor Associations, RR-147, Tulsa, 1995.

In the previous “Tip of the Month” we briefly discussed the importance of liquid density for process simulation and equipment design and introduced different methods of their predictions. In addition to direct laboratory measurement, three different methods were introduced to compute liquid density. The methods were (a) charts and monographs, (b) correlations and (c) EoS or volume translated EoS.

In this “Tip of the Month”, we will present a comparison between accuracy of different correlations and EoS methods. The focus will be on correlations for light hydrocarbons which have wider applications in industry.

Recently, Mulero et al. [1] have evaluated nine empirical correlations for their accuracy and applicability in calculation of the liquid saturation density of pure fluids. All of them were based on the corresponding states principle, and they have included very recent correlations. One model required only the knowledge of critical parameters, but most of them needed the critical parameters and acentric factor as inputs, and one required the Lennard-Jones molecular parameters and the acentric factor as input data. As a reference, they took the numerical values for the liquid saturation density accepted by the DIPPR [2] project for 552 fluids, grouped into 30 families. Recommendations are given for the use of each model and for the choice of the adequate model for each family of fluids, including for particular fluids. For detail comparison and suggestions, the readers are referred to their paper; however, Table 1 is a summary of their comparison for pure fluids. The two most common correlations in gas industry, Rackett and COSTALD (highlighted in blue color) are also discussed in Chapter 3 of JMC Volume 1 of Gas Conditioning and Processing Book [3].

Table 1: MAPDs (Mean value of Absolute Percent Deviations) of the Calculated Liquid Saturation Densities for Several Families of Fluids with Respect to the DIPPR [2] Data when Using Correlations^a-c [1]

The numbers in italics represent the lowest MAPDs, and the numbers in bold show MAPDs that are similar (1%) to the lowest one. b YG) Yamada and Gunn; RRPS ) Reid et al.; B) Bhirud; QSMC1) Queimada et al.; QSMC2) Queimada et al.; SNM0) Mchaweh et al.; FMC) Fau´ndez et al.. c N) number of fluids, ND) number of data.

Similarly, Mchaweh et al. [12] reported the results of comparison study for light hydrocarbon mixtures containing nitrogen. A summary of their work is presented in Table 2. Their evaluation did not include COSALD; however, our experience indicates that COSTALD MAPD is below 0.5 %. It should be noted that even though Volume Translated SRK (VTSRK) improves the accuracy of the SRK EoS but still is not good enough for industrial applications.

Table 2: The MAPD for 17 multi-component low temperature systems (226 data points) using different method [12]

In another paper, Javanmardi et al. [18] evaluated several correlations and EoSs for prediction of LNG density. Among others, five LNG mixtures consisting of 22 experimental data were studied. The compositions of these LNG mixtures are presented in Table 3 and a summary of comparison between accuracies of different methods is shown in Table 4.

Analysis of Tables 1 through 4 indicates that, for pure compounds, the SNM [12] in general gives better accuracies. However, for light hydrocarbon mixtures (NGL and LNG) liquid densities prediction, it is highly recommended to use COSTALD [3, 8, 9] even though SNM correlation also give accurate and compatible results. The SRK [16] and its volume translated correction (VTSRK, [17]) accuracies are not as good as the correlations so their use for practical applications must be done with care and caution. Needless to point out that SRK predict gas densities accurately. Based on our experiences and similar observations, we have programmed, in the JMC GCAP software, SRK for gas and COSTALD for liquid densities.

In next “Tip of the Month” we will provide Part 2 of guidelines for proper use of commercial simulator to calculate liquid densities.

To learn more about liquid density and its impact on facilities calculation, design and surveillance, refer to JMC books and enroll in our G4 (Gas Conditioning and Processing) and G5 (Gas Conditioning and Processing – Special) courses.

By Dr. Mahmood Moshfeghian

Reference:

1. Mulero, A., Cachadina, I. and Parra, M. I., “Liquid Saturation Density from Predictive Correlations Based on the Corresponding States Principle. Part 1: Results for 30 Families of Fluids,” Ind. Eng. Chem. Res., 45, 1840-1848, 2006
2. DIPPR (Design Institute for Physical Property Data) files, Version 17.0; American Institute of Chemical Engineers: New York, 2003 (supplied by Technical Database Services, Inc., www.tds.cc).
3. Campbell, J. M. “Gas conditioning and processing, Volume 1: Fundamentals,” John M. Campbell and Company, Norman, Oklahoma, USA, 2001.
4. Rackett, H. G. Equation of state for saturated liquids. J. Chem. Eng. Data, 15, 514, 1970 5. Yamada, T.; Gunn, R. D. Saturated liquid molar volumes: The Racket equation. J. Chem. Eng. Data, 18, 234, 1973
5. Reid, R. C.; Prausnitz, J. M.; Sherwood, T. K. The Properties of Gases and Liquids; McGraw-Hill: New York, 1977.
6. Bhirud, V. L. A four-parameter corresponding states theory: Saturated liquid densities of anormal fluids. AIChE J., 24, 1127, 1978.
7. Hankinson, R. W.; Thomson, G. H. A new correlation for saturated densities of liquids and their mixtures. AIChE J. 1979, 25, 653.
8. Thomson, G. H.; Brobst, K. R.; Hankinson, R. W. An improved correlation for densities of compressed liquids and liquid mixtures. AIChE J., 28, 671, 1982
9. Faundez, C. A.; Mulero, A.; Cuadros, F. Molecular Thermodynamic Models for the Vapour-Liquids Equilibrium of Non-Polar Fluids. J.. Phase Equilib., 21, 364, 2000.
10. Queimada, A. J.; Stenby, E. H.; Marrucho, I. M.; Coutinho, J. A. P. A new corresponding states model for the estimation of thermophysical properties of long chain n-alkanes. Fluid Phase Equilib., 212, 303, 2003.
11. Mchaweh, A.; Alsaygh, A.; Nasrifar, Kh.; Moshfeghian, M. A simplified method for calculating saturated liquid densities. Fluid Phase Equilib., 224, 157, 2004.
12. M.J. Hiza, W.M. Haynes, W.R. Parrish, J. Chem. Thermodyn. 9, 873–896, 1977.
13. Haynes, W. M., Measurements of Orthobaric-Liquid Densities of Multicomponent Mixtures of LNG components Between 110 and 130 K, J. Chem. Thermodynamics, 14, 603-612, 1982.
14. M.J. Hiza, W.M. Haynes, J. Chem. Thermodyn. 1, 1–10, 1980.
15. Soave, G., Chem. Eng. Sci., vol. 27, 1197-1203, 1972.
16. Peneloux, A. E., Rauzy, E., and Freze, R., Fluid Phase Equilib., Vol. 8, 7-23, 1982.
17. Javanmardi, J., Nasrifar, Kh., Moshfeghian, M., Comparing different methods for prediction of liquefied natural gas densities, Engineering Journal of the University of Qatar, Vol. 18, 39-56, 2005

Liquid density is needed for process simulation and equipment design. For example, accurate predictions of liquid density are needed for calculation of pressure drop in a piping/pipeline and vessel sizing. Accurate liquid density is also essential for custody transfer.

Liquid density ranges from a few hundred above thousand to couple of 100 kg/m³. Table 1 presents typical range of liquid densities where as typical re-injection gas has a density in the range of 125 to 150 kg/m³ and pipeline gases at 7000kPa has a density in the order of 70 kg/m³.

Liquid densities are sometime expressed in terms of relative density (specific gravity) or API gravity. The relative density,? , is defined as:

and the API (American Petroleum Index) gravity is:

Depending on the applications, three different methods can be used to compute liquid density in addition to direct laboratory measurement. These methods are (a) charts and monographs, (b) correlations and (c) EoS or volume translated EoS, of which the correlations are usually the most accurate.

For the LNG density measurement and calculation, one of the standard procedures practiced in industry is ISO 6578: 1991 [1]. This procedure specifies the calculations to be made to adjust the volume of a liquid from the conditions at measurement to the equivalent volume of liquid or vapor at a standard temperature and pressure, or to the equivalent mass or energy (calorific content). Annexes A to H of this procedure form an integral part of this standard.

Generalized Charts

There are several generalized charts for prediction of liquid density of petroleum fluids and hydrocarbons [2].

The relative density of petroleum fluids are normally expressed in terms of two of three characteristics- API gravity at 15°C, the Watson characterization factor, KW, or the mean average boiling point. The Watson characterization factor is defined in terms of mean average boiling point, Tb, and the relative density at standard condition.

The charts normally present the relative density of paraffinic hydrocarbon mixtures at their boiling point or bubble point temperature and pressure. These charts apply to mixtures as well to pure components. Alignment points for paraffinic hydrocarbon mixtures and pure components are located according to their molecular weight. The accuracy of these charts is generally within 3 % of the measured values. However, the accuracy is somewhat less for mixtures having molecular weights less than 30 where temperature is low, and where the methane content is high or reduced temperatures above 0.9 [3].

EoS Methods and Volume Translation

The EoSs are used in commercial simulation softwares for predicting phase behavior and thermodynamic properties. Generally, EoSs need a few parameters (usually two or three) that are normally obtained from critical properties. The cubic equations of state (EOS) give accurate results for prediction of vapor-liquid equilibria, especially for non-polar or slightly polar systems. Furthermore, these equations could be used to accurately predict vapor densities, enthalpy and entropy. These advantages encourage the researchers to augment EoS ability more than before, especially, liquid density, although their accuracy for liquid density prediction is not as good as correlations. The popular EoSs such as SRK [4] and PR [5] predict liquid density with an average absolute error about 8%, much more than the correlations [6]. This large magnitude of error is not acceptable by industry; therefore; they are not used for this purpose. In order to overcome this deficiency, a volume translated method has been developed by Peneloux et al. [7]. The working equations are:

In the above equation, v^SRK is calculated by SRK EoS and the correction term “c” as follows:

Correlations

In order to calculate liquid density reliably, several correlations such as COrresponding STAte Liquid Density (COSTALD) and modified Rackett equation by Spencer and Danner (RSD), have been developed.

COSTALD correlation: The COSTALD correlation, Hankinson and Thomson [8], requires two parameters, ?_SRK, the optimized value of the acentric factor based on the SRK EoS and V*, the pure component characteristic volume.

The RSD correlation: Spencer and Danner [9] improved the liquid density correlation of Rackett [10]. The improved correlation for saturated liquid density calculation requires only Z_RA, the improved compressibility factor.

In next “Tip of the Month” we will provide guidelines for use of these methods and present the results of a comparison study between these methods.

To learn more about liquid density and its impact on facilities calculation, design and surveillance, refer to JMC books and enroll in our G4 (Gas Conditioning and Processing) and G5 (Gas Conditioning and Processing – Special) courses.

By Dr. Mahmood Moshfeghian

Reference:

1. http://www.iso.org
2. Campbell, J. M. “Gas conditioning and processing, Volume 1: Fundamentals,” John M. Campbell and Company, Norman, Oklahoma, USA, 2001.
3. Engineering Data Book, 10th and 11th Editions, Gas Processors and Suppliers Association Data Book, Tulsa, Oklahoma, 1998.
4. Soave, G., Chem. Eng. Sci., vol. 27, pp. 1197-1203, 1972.
5. Peng, D. Y., and Robinson, D. B., Ind. Eng. Chem. Fundam., vol. 15, p. 59, 1976.
6. Nasrifar, Kh. and M. Moshfeghian, J. of Fluid Phase Equilibria, 158-160, pp. 437-445, 1998.
7. Peneloux, A. E., Rauzy, E., and Freze, R., Fluid Phase Equilib., vol. 8, pp. 7-23, 1982
8. Hankinson, R. W., Thomson, G. H., AIChE J., vol. 25, no. 4, pp. 653-663, 1979.
9. Spancer, C. F., and Danner, R. P., J. Chem. Eng. Data, vol. 17, no. 2, pp. 236-241, 1972.
10. Rackett, H. G., J. Chem. Eng. Data, vol. 15, no. 4, pp. 514-517, 1970.

In the previous “Tip of the Month”, we presented several methods for estimating Kvalues. The methods presented were the GPA correlations and charts, Raoult’s law, Wilson’s correlation, EoS approaches, activity coefficient models and JMC Charts and Tables. However, the question arises as to which equation or method should be used? The answer to this question “depends” on many factors such as pressure, temperature, composition, and components of the system.

In this “Tip of the Month” we will provide guidelines for use of these methods and present the results of a comparison study between these methods.

Table 1 presents the list of suggested methods for estimation of K-values and the applicable pressure range.

Comparison of methods:

For mixture A shown in Table 2, a series of bubble pointand dewpoint calculations were performed using Raoult’s law, Wilson correlation, GPA charts, and the SRK EoS. The summary of results is shown in tables 3 and 4, respectively.

As can be seen from Table 3 and 4, at low pressures, all of the methods produce very close answers; however, as the pressure increases they deviates considerably from each other.

In general Raoul’t law and Wilson correlation generates close answers. The GPA and SRK results are close to each other up to 1000 psia. However, at higher pressures they deviate from each other. As can be seen by this comparison, it is important to not apply these K-value equations outside of their recommended range of application.

It can also be seen that even when the equations are applied properly widely varying results can be obtained as is the case with the GPA and SRK results. In order to determine which equation is providing the most accurate results it is a good idea to compare the results with actual data. Experimental data may also be used to tune (improve the accuracy) of a correlation or an EoS.

Similarly, for the same mixture shown in Table 1, a series of flash calculations for two isotherms were performed and the calculated liquid fractions (L/F) using different methods are compared in Table 5. Again, the calculated liquid fractions by the Raoult’s law and Wilson correlations are close to each other but they deviate considerably from the GPA charts and the SRK EoS results.

Guidelines:

Due to the observation made in the previous section and other studies, care must be taken in selecting K-values correlations. Therefore, the following guidelines extracted from page 128 of Vol 1 of JMC book are suggested.

The accuracy of the results of calculations involving K-Values depends on the reliability of sampling, of the analysis of that sample, and the K-Value correlation used.

There is no single K-Value correlation that is superior for all mixtures encountered. An experienced practitioner may have two or three different models or program available. Generally, crude oil and NGL phase behavior is handled by different models.

All K-values are sensitive to composition, particularly the very volatile components like nitrogen, methane, and ethane.

For design purposes, several models may be used to determine a range of results. This range, rather than one set of “magic” numbers, is then used to size equipment. The name of the game is flexibility. It is doubtful if one ever will encounter the analyses, flow rates and exact other conditions used as the design basis.

It is most important that the K-values be internally consistent. There are several methods available for this purpose (See pages 113-116 of Vol 1 of JMC Books).

An experienced practitioner usually can predict the quantity of a specified liquid within 6% (for a specified analysis and conditions). The compositional analysis on which the calculation was based will often be in error more than this. This is important, for in many systems a series of VLE calculations is made; the output from one is the input to another. The errors thus accumulate. Many less than desirable systems results from failure to recognize this.

To learn more on applications of K-values and their impact on facilities calculation, design and surveillance, refer to JMC books [1-3] and enroll in our G4 (Gas Conditioning and Processing) and G5 (Gas Conditioning and Processing – Special) courses.

By Dr. Mahmood Moshfeghian

Reference:

1. Maddox, R. N. and L. L. Lilly, “Gas conditioning and processing, Volume 3: Advanced Techniques and Applications,” John M. Campbell and Company, Norman, Oklahoma, USA, 1994.
2. Campbell, J. M. “Gas conditioning and processing, Volume 1: Fundamentals,” John M. Campbell and Company, Norman, Oklahoma, USA, 2001.
3. Campbell, J. M., “Gas conditioning and processing, Volume 2: Equipment Modules,” John M. Campbell and Company, Norman, Oklahoma, USA, 2001.

Nomenclature:

K_i – Vapor–liquid equilibrium ratio
P – Pressure, kPa [psia]
P_i^Sat– Saturation pressure of component I, kPa [psia]
T – Temperature, K [°R]
y_i – Mole fraction in the vapor phase
x_i – Mole fraction in the liquid phase
?_i^V – Fugacity coefficients of component I in the vapor phase
?_i^L – Fugacity coefficients of component I in the liquid phase
Y_i– Activity coefficient of component I in the liquid phase

Modeling and design of many types of equipment for separating gas and liquids such as flash separators at the well head, distillation columns and even a pipeline are based on the phases present being in vapor-liquid equilibrium. The thermodynamic equilibrium between vapor and liquid phases is expressed in terms equality of fugacity of component i in the vapor phase, f_i^V, and the fugacity of component i in the liquid phase, f_i^L, is written as

Equation (1) is the foundation of vapor-liquid equilibrium calculations; however, we rarely use it in this form for practical applications. For calculation purposes, Eq. (1) is transformed to a more common expression which is

Ki is called the vapor–liquid equilibrium ratio, or simply the K-value, and represents the ratio of the mole fraction in the vapor, yi, to the mole fraction in the liquid, xi. Equation (2) is also called “Henry’s law” and K is referred to as Henry’s constant. For the more volatile components the Kvalues are greater than 1.0, whereas for the less volatile components they are less than 1.0.
Depending on the system under study, any one of several approaches may be used to determine K-values. Obviously, experimental measurement is the most desirable; however, it is expensive and time consuming. Alternatively, there are several graphical or numerical tools that are used for determination of K-values. This “Tip of the Month” presents a history of many of those graphical methods and numerical techniques.

In general K-values are function of the pressure, temperature, and composition of the vapor and liquid phases. The components making up the system plus temperature, pressure, composition, and degree of polarity affect the accuracy and applicability, and hence the selection, of an approach. The widely used approaches are K-value charts, Raoult’s law, the equation of state (EoS) approach (f), activity coefficient approach (?) or combination of EoS and the EoS and ? approaches [1-5]. EoS approach requires use of a digital computer.

K-Value Charts

There are several forms of K-value charts. One of the earliest K-value charts for light hydrocarbons is presented in reference [1]. In these charts, K-values for individual components are plotted as a function of temperature on the x-axis with pressure as a parameter. In each chart the pressure range is from 70 to 7000 kPa (10 to 1000 psia) and the temperature range is from 5 to 260 ºC (40 to 500 ºF).

Early high pressure experimental work revealed that, if a hydrocarbon system of fixed overall composition were held at constant temperature and the pressure varied, the K-values of all components converged toward a common value of unity (1.0) at some high pressure. This pressure was termed the “Convergence Pressure” of the system and has been used to correlate the effect of composition on K-values, thus permitting generalized K-values to be presented in a moderate number of charts.

In more recent publications [2], the K-values are plotted as a function of pressure on the x-axis with temperature and Convergence Pressure as parameters. In order to use these charts, one should determine the Convergence Pressure first. The determination of convergence Pressure is a trial-and-error procedure and can be found elsewhere [6].

For computer use, later in 1958 these K-Value charts were curve fitted to the following equations by academic and industrial experts collaborating through the Natural Gas Association of America [7].

In Eq (3) T is temperature in ºR, P is pressure in psia and the fitted values of the bij coefficients are reported in an NGAA publication [7].
A relatively simple nomograph is normally presented in undergraduate thermodynamics and unit operations text books. In the nomograph, the K-values of light hydrocarbons, normally methane through n-decane, are plotted on one or two pages. Charts of this type do allow for an average effect of composition, but the essential basis is Raoult’s law and equilibrium constants derived from them are useful only for teaching and academic purposes.

Raoult’s Law

Raoult’s Law is based on the assumptions that the vapor phase behaves as an ideal gas and the liquid phase is an ideal solution. Under these conditions the fugacities are expressed as

The saturation pressure of a component is represented by P_i^Sat and the pressure of the system is represented by P. Substituting from Eqs (4) and (5) in Eq (1) gives

The vapor pressure may be read from a Cox chart or calculated from a suitable equation in terms of temperature. A typical Cox chart may be found in reference [8]. The Antoine [5] equation is recommended for calculating vapor pressure:

Values of A, B, and C for several compounds are reported in the literature [5]. Complex vapor pressure equations such as presented by Wagner [5], even though more accurate, should be avoided because they can not be used to extrapolate to temperatures beyond the critical temperature of each component. Raoult’s law is applicable to low pressure systems (up to about 50 psia or 0.35 MPa) or to systems whose components are very similar such as benzene and toluene. This method is simple but it suffers when the temperature of the system is above the critical temperature of one or more of the components in the mixture. At temperatures above the critical point of a component, one must extrapolate the vapor pressure which frequently results in erroneous K-values. In addition, this method ignores the fact that the K-values are composition dependent.

Correlation Method

As mentioned earlier, determination of K-values from charts is inconvenient for computer calculations. Therefore, scientists and engineers have developed numerous curve fitted expressions for calculation of K-values. However, these correlations have limited application because they are specific to a certain system or applicable over a limited range of conditions. Some of these are polynomial or exponential equations in which K-values are expressed in terms of pressure and temperature. One of these correlations presented by Wilson [9], is:

where Tci, critical temperature, in ºR or K, Pc_i, critical pressure, in psi, kPa or bar, ?_i is the acentric factor, P is the system pressure, in psi, kPa or bar, T is the system temperature, in ºR or K. (P and Pc, T and Tc must be in the same units.) This correlation is applicable to low and moderate pressure, up to about 3.5 MPa (500 psia), and the K-values are assumed to be independent of composition.

EoS Approach

The fugacity of each component is determined by an EoS. In other words, both phases are described by only one EoS. It is a powerful tool and relatively accurate if used appropriately. This approach is widely used in industry for light hydrocarbon and non polar systems. Under these conditions the fugacities are expressed by

The fugacity coefficients for each component in the vapor and liquid phases are represented by ?_i^V and ?_i^L
, respectively. Substitution of fugacities from Eqs (9) and (10) in Eq (1) gives

The EoS method has been programmed in the GCAP for Volumes 1 & 2 of Gas Conditioning and Processing Software to generate K-values using the SRK EoS [10].

EoS-Activity Coefficient Approach

The approach is based on an EoS which describes the vapor phase non-ideality through the fugacity coefficient and an activity coefficient model which accounts for the non-ideality of the liquid phase. This approach is widely used in industry for polar systems exhibiting highly non-ideal behavior. Under these conditions the fugacities are expressed by

The fugacity coefficients for each component in the vapor phase are represented by f_i^V . The saturation fugacity coefficient for a component in the system, f_i^Sat is calculated for pure component i at the temperature of the system but at the saturation pressure of that component. Normally, an EoS is used to calculate both f_i^V and f_i^Sat . Substitution of fugacities from Eqs (12) and (13) in Eq (1) gives

Activity coefficients are calculated by an activity coefficient model such as that of Wilson [11] or the NRTL (Non-Random Two Liquid) model [12]. In order to calculate K-values by equation 14, the mole fractions in both phases in addition to the pressure and temperature must be known. Normally not all of these variables are known. As is the case for the EoS approach, calculations are trial and error. This approach is applicable to polar systems such as water – ethanol mixtures from low to high pressures.

Normally, for low pressures, we can assume that the vapor phase behaves like an ideal gas; therefore both ?_i^V and ?_i^Sat are set equal to 1.0. Under such circumstances, Eq (14) is reduced to

Eq (15) is applicable for low pressure non-ideal and polar systems. Assuming the liquid phase is an ideal solution, ? i becomes unity and Eq (15) is reduced further to a simple Raoult’s law.

The JMC K-Values

Two sets of K-values are summarized in Appendices 5A and 5B at the end of Chapter 5 of Gas Conditioning and Processing, Vol. 1. Appendix 5A is a series of computer-generated charts using SRK EoS. The values shown are useful particularly for calculations of vapor liquid equilibrium wherein liquid being condensed from gas systems. Appendix 5B is based on the data obtained from field tests and correlations on oil-gas separators. The data set was based on over 300 values. This correlation has bee used for often for oil separation calculations.

To learn more on applications of K-values and their impact on facilities calculation, design and surveillance, refer to JMC books [12-13] and enroll in our G4 (Gas Conditioning and Processing) and G5 (Gas Conditioning and Processing – Special) courses.

By Dr. Mahmood Moshfeghian

Reference:

1. Natural Gasoline Supply Men’s Association, 20th Annual Convention, April 23-25, 1941.
2. Engineering Data Book, 10th and 11th Editions, Gas Processors and Suppliers Association Data Book, Tulsa, Oklahoma, (1998).
3. Prausnitz, J. M.; R. N. Lichtenthaler, E. G. de Azevedo, “Molecular Thermodynamics of Fluid Phase Equilibria,”, 3rd Ed., Prentice Hall PTR, New Jersey, NY, 1999.
4. Maddox, R. N. and L. L. Lilly, “Gas conditioning and processing, Volume 3: Advanced Techniques and Applications,” John M. Campbell and Company, Norman, Oklahoma, USA, 1994.
5. Reid, R. C.; J. M. Prausnitz, and B. E. Poling, “The properties of Gases and liquids,” 4th Ed., McGraw Hill, New York, 1987.
6. Engineering Data Book, 7th Edition, Natural Gas Processors Suppliers Association, Tulsa, Oklahoma, 1957.
7. Equilibrium Ratio Data for Computers, Natural Gasoline Association of America, Tulsa, Oklahoma, (1958).
8. Natural Gasoline and the Volatile Hydrocarbons, Natural Gasoline Association of America, Tulsa, Oklahoma, (1948).
9. Wilson, G., “A modified Redlich-Kwong equation of state applicable to general physical data calculations,” Paper No15C, 65th AIChE National meeting, May, (1968).
10. G. Soave, Chem. Eng. Sci. 27, 1197-1203, 1972.
11. Wilson, G. M., J. Am. Chem. Soc. Vol 86, pp.127-120, 1964
12. Campbell, J. M. “Gas conditioning and processing, Volume 1: Fundamentals,” John M. Campbell and Company, Norman, Oklahoma, USA, 2001.
13. Campbell, J. M., “Gas conditioning and processing, Volume 2: Equipment Modules,” John M. Campbell and Company, Norman, Oklahoma, USA, 2001.