## Ideal Water Content Correlation for Sweet Natural Gas

The analysis of Figures 1 through 3 indicates that the for pressures up to 100 psia (690 kPa) the Raoult’s law water content deviations from real state water content are within about +4% and -4%.  The water vapor content of natural gases in equilibrium with water is commonly estimated from Figure 6.1 of Campbell book [1] or Figure 20.4 of Gas Processors and Suppliers Association [2]. In the October, November, December 2007, February 2014 and September 2014 Tips of the Month (TOTM), we studied in detail the water phase behaviors of sweet and sour natural gases and acid gas systems. We presented several correlations and evaluated the accuracy of different methods for estimating the water content of sweet natural gas, sour natural gas, and acid gas systems.

In this TOTM, we will evaluate pressure and temperature applicability ranges and accuracy of the ideal water content correlation for sweet natural gases. In addition, the performance of the ideal water content correlations will be compared with the equation of state based rigorous calculation methods.

Equilibrium Water Content at Low Pressures

Assuming vapor phase is an ideal gas and liquid phase is an ideal solution, the equality of water fugacities at equilibrium simplifies to the Raoult’s law.

(1)

Where:

yw  = mole fraction water in the vapor phase

PV = vapor pressure of water at system temperature

P  = system pressure

xw = mol fraction water in the liquid water phase

The liquid mole fraction can be taken as xw = 1.0 because of the low solubility of the hydrocarbon phase in the aqueous phase and to cover cases where no liquid hydrocarbon is present – just vapor + liquid water.  Thus, for a known pressure and water vapor pressure the mole fraction water in the vapor phase is found from Equation 1.

Under ideal conditions, the mole fraction of water in the gas phase can be estimated by dividing water vapor pressure, PV, at the specified temperature, T, by the system pressure, P. The vapor pressure of pure water, from 0 to 360 °C, (32 to 680 °F) can be calculated by the following correlation [3].

(2)

Where:

τ = 1 – (T/TC)

The critical temperature, TC = 647.096 K (1164.77 °R)  and critical pressure, PC = 22064 kPa, (3199.3 psia) T in K (°R), and PV in kPa (psia), and

a1 = −7.85951783

a2 = 1.84408259

a3 = −11.7866497

a4 = 22.6807411

a5 = −15.9618719

a6 = 1.80122502

Knowing one kmole of water = 18 kg (lbmole=18 lbm) and one kmole of gases occupy 23.64 Sm3 at standard condition of 15 °C  and 101.3 kPa (one lbmole of gases occupy 379.5 SCF at standard condition of 60 °F  and 14.7 psia), the ideal water content is calculated by:

(3)

Bukacek Correlation

Bukacek [4] suggested a relatively simple correlation for the water content of lean sweet gases as follows:

(4)

(5)

where T is in °F and PV and P are absolute pressures in psia (kPa).

This correlation is reported to be accurate for temperatures between 60 and 460°F (15.5 and 238°C) and for pressure from 15 to 10,000 psia (0.105 to 69.97 MPa). The pair of equations in this correlation is simple in appearance. The added complexity that is missing is that it requires an accurate estimate of the vapor pressure of pure water. In this study, we have used equation 2 for water vapor pressure.

Evaluation of the Raoult’s Law (Ideal) Water Content

The performance of the Raoult’s law for estimating water content of sweet natural gases was evaluated against Bukacek correlation [4], GCAP software [5] and two simulation programs. The water content of GCAP is based on Figure 6.1 of Campbell book [1]. The SRK EOS (Soave-Redlich-Kwong equation of state) with its default binary interaction parameters was used in both simulation programs. The composition of gases needed for simulation study are shown in Table 1. The Raoult’s law, GCAP program and Bukacek correlation are independent of gas composition.

In simulators, there are several options to predict the equilibrium water content of a gas stream which may give different answers. In this study, the mole fraction of water in the desired stream is multiplied 47430 to get lbm/MMscf (or 761420 to get kg/106 Sm3).

Figure 1 through 5 present the percent deviations of water content estimated by Raoult’s law from GCAP program, and two simulation programs (Sim B and Sim C). In each figure, the percent deviations of Raoult’s law water content from those predicted by GCAP, Sim B and Sim C are presented on the vertical axis. The Raoult’s law and GCAP methods are independent of composition while Sim B and Sim C are composition dependent.

The pressure values are 25, 50, 100, 200, and 300 psia (172, 344, 690 1379, and 2069 kPa); respectively. For each pressure, the results for four isotherms of 40, 80, 120, and 160 °F (4.4, 26.7, 48.9, 71.1 °C) are presented.

Figure 1 indicates that at low pressure of 25 psia (172 kPa), the deviations of Raoult’s law water content from the other three methods are small and within -4 to +1%, span of 5%.

Figure 2 indicates that at low pressure of 50 psia (345 kPa), the deviations of Raoult’s law water content from the other three methods are small and within -3 to +2%, span of 5%.

Figure 3 indicates that at low pressure of 100 psia (690 kPa), the deviations of Raoult’s law water content from the other three methods are small and within -1 to +4%, span of 5%.

Fig 1. Water content by Raoult’s law vs GCAP and two simulators at 25 psia (172 kPa)

Fig 2. Water content by Raoult’s law vs GCAP and two simulators at 50 psia (345 kPa)

Fig 3. Water content by Raoult’s law vs GCAP and two simulators at 100 psia (690 kPa)

The analysis of Figures 1 through 3 indicates that the for pressures up to 100 psia (690 kPa) the Raoult’s law water content deviations from real state water content are within about +4% and -4%.

Figure 4 indicates that at the higher pressure of 200 psia (1379 kPa), the deviations of Raoult’s law water content from the other three methods are higher and within 0 to +9%, span of 9%. This figure also indicates that the Raoult’s law percent deviation from GCAP is the largest while simulator B gives lower values of deviations.

Figure 5 indicates that at the higher pressure of 300 psia (2069 kPa), the deviations of Raoult’s law water content from the other three methods are within +5 to +14%, span of 9%. This figure also indicates that the Raoult’s law percent deviations from GCAP is the largest while simulator B gives lower values of deviations.

In general, for a combination of pressure and temperature which results in less dense gas (low pressure and high temperature), there are fewer deviations of Raoult’s law from simulator results that are based on an EOS (equation of state).

Table 2 presents the absolute percent deviations and the overall average absolute percent deviations of Raoult’s law from GCAP, Sim B, Sim C, and Bukacek methods for 140 evaluated points. Note for each temperature, four gases with compositions shown in Table 1 were evaluated. Table 2 indicates that Raoult’s law results have the least deviation from Bukacek and the most deviation is from GCAP and the overall average absolute percent deviations is less than 4 % for pressures up to 300 psia (2069 kPa) and temperatures up to 160°F (71°C).

Fig 4. Water content by Raoult’s law vs GCAP and two simulators at 200 psia (1379 kPa)

Fig 5. Water content by Raoult’s law vs GCAP and two simulators at 300 psia (2069 kPa)

Table 2. Raoult’s law water content average absolute percent deviations from 4 methods

In addition to the sweet natural gas system, we have determined the equilibrium water mole fraction of propane vapor by simulators B and C, Bukacek method, and Raoul’s law (ideal). Table 3 presents the percent deviation of these 4 methods from the smoothed experimental water mole fraction reported in the GPA RR 132 [6]. The accuracy of these four methods are within experimental data. It should be noted that for temperatures of 53.8°F and 47.9°F, the corresponding experimental pressures were 98 psia and 90 psia, respectively. Since at these pressures and temperatures the state of propane was liquid, these two pressures were reduced slightly to 97.35 psia and 88.6 psia to produce 100% propane vapor.

Table 3. Propane vapor water content predictions vs RR 132 experimental data [6]

Conclusions:

The performance of Raoult’s law for predicting the water content of sweet natural gases against 4 methods is presented. The four methods are GCAP, Simulators A and B and Bukacek correlation. The following conclusions can be made:

1. The Raoult’s law (Eq. 1) combined with an expression to estimate water vapor pressure (Eq. 2) is a simple tool for predicting the water content of sweet natural gases.
2. In general, for a combination of pressure and temperature which results in less dense gas (low pressure and high temperature), there are fewer deviations of Raoult’s law from simulator results that are based on an EOS (equation of state).
3. Table 2 indicates that Raoult’s water content predictions have the least deviation from Bukacek correlation and the most deviations from GCAP.
4. The overall average absolute percent deviations for the systems considered in this tip are less than 4%  and the maximum deviation is less than 13.6% (Table 2) for pressures up to 300 psia (2069 kPa) and temperatures up to 160°F (71°C).

To learn more about similar cases and how to minimize operational problems, we suggest attending our G4 (Gas Conditioning and Processing), G5 (Practical Computer Simulation Applications in Gas Processing), and G6 (Gas Treating and Sulfur Recovery) courses.

By: Dr. Mahmood Moshfeghian

References

1. R. Kobayashi, “Water content of ethane, propane, and their mixtures in equilibrium with water and hydrates,” Gas Processor Association Research Report (GPA RR 132), Tulsa, Oklahoma, 1991.andSong, K
2. GCAP 9.2.1, Gas Conditioning and Processing, PetroSkills/Campbell, Norman, Oklahoma, 2015.
3. Bukacek, R.F., “Equilibrium Moisture Content of Natural Gases” Research Bulletin IGT, Chicago, vol 8, 198-200,  1959.
4. Wagner, W.  and Pruss, A.,  J. Phys. Chem. Reference Data, 22, 783–787, 1993.
5. GPSA Engineering Data Book, Section 20, Volume 2, 13th Edition, Gas Processors and Suppliers Association, Tulsa, Oklahoma, 2012.
6. Campbell, J.M., Gas Conditioning and Processing, Volume 1: The Basic Principles, 9th Edition, 2nd  Printing, Editors Hubbard, R. and Snow–McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.

## Optimizing Performance of Refrigeration System with Flash Tank Economizer

Continuing the January 2008 [1] Tip of The Month (TOTM), this tip demonstrates two methods to optimize the performance of a refrigeration system employing a flash tank economizer and two stages of compression. Specifically, we will minimize the compressor total power and condenser duty by optimizing the interstage pressure.

The details of a simple single-stage refrigeration system and a refrigeration system employing one flash tank economizer and two stages of compression are given in Chapter 15 of Gas Conditioning and Processing, Volume 2 [2]. The process flow diagram for a flash tank economizer refrigeration system with two stages of compression is shown in Figure 1. Note that provisions have been made to consider pressure drop in the suction line of the first stage compressor.

Figure 1. Process flow diagram for a refrigeration system with a flash tank economizer and two stages of compression

Let’s consider removing 10.391×106 kJ/h (2886 kW) from a process gas at -35°C and rejecting it to the environment by the condenser at 35°C. Pure propane is used as the working fluid. In this study, all the simulations were performed by UniSim Design software [3]. Assuming 5 kPa pressure drop in the chiller, the pressure of saturated vapor leaving the chiller at -35°C is 137.4 kPa.  Also, assuming 30 kPa pressure drop in the suction line, the first stage compressor suction pressure is 107.4 kPa. The condensing propane pressure at 35°C is 1220 kPa. The condenser pressure drop plus the pressure drop in the line from the compressor discharge to the condenser was assumed to be 50 kPa; therefore, compressor discharge pressure is 1270 kPa. In addition, an adiabatic efficiency of 75% was assumed for both stages of compression.

Assuming no pressure drop between the two stages, Figure 2 presents the variation of the compressor stages 1, 2, and the total power as a function of the interstage pressure.

Method 1:

The “Databook” option from “Tools” menu of the UniSim was used to generate powers (dependent variables) as a function of interstage pressure (Independent variable). The interstage pressure was varied from 200 kPa to 1000 kPa with an increment of 10 kPa.

As can be seen in this figure, the optimum interstage pressure is about 470 kPa. This pressure corresponds to the minimum total power and also the equality of stages 1 and 2 power.

Figure 2. Impact of interstage pressure on compressor power.

Similarly, Figure 3 presents the compressor total power, stages 1 and 2 compression ratios. Figure 3 clearly shows that the minimum total compressor power does not occur at equal stage compression ratios of  3.44. Yet Chapter 14 (Compressors) of Gas Conditioning and Processing, Volume 2 [2] states “The total power is typically minimized when the ratio in each stage is the same.”  Why is that not the case here?

The ideal optimum interstage pressure based on equal compression ratios can be found by the following equation:

The equal compression ratio for each stage is R= 369.3/107.4 = 3.44 and  R= 1270/369.3 = 3.44. The above equation is valid if the mass flow rates through both stages were the same and the suction temperatures for both stages were equal. In a refrigeration system with flash tank economizers and multiple stages of compression, usually neither of these conditions are met.  In this case, the mass flow rates through stages 1 and 2 are 3.106 x 104 and 4.171 x 10 4 kg/h, respectively. The suction temperatures are -35.8°C and 21.1°C, respectively.

Figure 3. Impact of interstage pressure on the total compressor power and stages compression ratio.

Method 2:

An alternative and easier method to determine the optimum interstage pressure is the “Adjust” tool in the simulation software. As shown in Figure 1, ADJ-2 was used to vary interstage pressure (stream R-12) so that first stage “R-Comp-LP Power” power becomes equal the second stage “R-Comp-HP Power” power. The setup for ADJ-2 is shown in Figure 4 and the detail of iterations and final results are shown in Figure 5. As shown in Figure 5, the optimum interstage pressure is 471.3 kPa and each stage compression power is 793 kW which adds up to a minimum total power of 1586 kW.

Summary:

Because the mass flow rates and suction temperatures were different in each stage of compression, the minimum total compressor power does not occur at equal compression ratios in each stage.

Two methods of “Databook” and “Adjust” were used to minimize the total compression power and condenser duty by selecting the optimum interstage pressure.

In the first method “Databook”, the optimum interstage was determined by minimizing the total compressor power. In the second method “Adjust”, the interstate pressure was determined by equalizing stages 1 and 2 powers. Both methods gave the same interstage pressure and total compressor power.

Figure 4. Detail of “Adjust” set up

Figure 5. Iteration and final results of “Adjust”

For the same chiller duty, chiller and condenser temperatures, and pressure drops, the results of the flash tank economizer system are compared with the results of a simple refrigeration system in Table 1. This table indicates that the compressor power and condenser duty saving are 17.4 % and 6.97 %, respectively. The interstage pressure drop is unique to flash tank economizer and its effect is the reduction of the power saving when compared to the simple refrigeration system and increases the condenser duty.

Table 1. Refrigeration specifications and calculated results

To learn more about similar cases and how to minimize operational problems, we suggest attending our G4 (Gas Conditioning and Processing), G5 (Practical Computer Simulation Applications in Gas Processing), and G6 (Gas Treating and Sulfur Recovery) courses.

References:

1. Moshfeghian, M., http://www.jmcampbell.com/tip-of-the-month/2008/01/refrigeration-with-flash-economizer-vs-simple-refrigeration-system/,  Tip of the Month, January 2008.
2. Printing, Editors Hubbard, nd Edition, 2thCampbell, J.M., “Gas Conditioning and Processing, Volume 2: The Equipment Modules,” 9R. and Snow–McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.
3. UniSim Design R443, Build 19153, Honeywell International Inc., 2017.

## Correlations for Vapor Pressure of Crude Oil Measured by Expansion Method (VPCRx)

Accurate measurement and prediction of crude oil and natural gas liquid (NGL) products vapor pressure are important for safe storage and transportation, custody transfer, minimizing vaporization losses and environmental protection. Vapor pressure speciﬁcations are typically stated in Reid Vapor Pressure (RVP) or/and True Vapor Pressure (TVP). In addition to the standard procedures for their measurements, there are rigorous and shortcut methods for their estimation and conversion.

Based on ASTM D323, there are figures and monographs for conversion of RVP to TVP for NGLs (Natural Gas Liquids) and crude oil at a specified temperature [1, 2]. Continuing the February 2016 [3] Tip of The Month (TOTM), this tip will present simple correlations for determination TVP and RVPE (Reid Vapor Pressure Equivalent) as described by ASTM Standard D6377-14 [4] at a specified temperature. The correlations are easy to use for hand or spreadsheet calculations.

Standard D6377 describes the use of automated vapor pressure instruments to determine the vapor pressure exerted in the vacuum of crude oils. This test method is suitable for testing samples that exert a vapor pressure between 25 kPa and 180 kPa at 37.8 °C (3.63 psia and 26.1 psia at 100 °F)  at vapor-liquid ratios from 4:1 to 0.02:1 (V/L = X = 4 to 0.02). A TVP reading can be determined by taking vapor pressure measurements at different expansion (V/L = X) ratios and extrapolating to V/L= X = 0.  Refer to reference [4] for detail description of this standard procedure.

To demonstrate the ASTM Standard D6377 procedure we generated vapor pressures of a sample condensate shown in Table 1 at four expansion ratios of  X = 1, 2, 3, 4 using ProMax simulation program [5] based on the Soave Redlich Kwong equation of state [6]. In this table, the heavy ends are presented by F-fractions and their properties are shown in Table 2.

Table 1. Composite of condensate

Table 2. Properties of the heavy end fractions used in Table 1

Table 3 presents the generated vapor pressure at 37.8 °C (100 °F) for four expansion ratios by ProMax mimicking the experimental measurements.

Table 3. Vapor pressure at 37.8 °C (100 °F) for four expansion ratios

The vapor pressures (VP) as a function of expansion ratio (X) in Table 3 were curve fitted to a quadratic equation as follows.

VP = a + bX +cX2

The fitted parameters a, b, and c are presented in Table 4 for pressures of Table 3 in kPa and psia.

Table 4. Fitted parameters for quadratic equation

1AAPD           = Average Absolute Percent Deviation

2MAPD          = Maximum Absolute Percent Deviation

3NP                = Number of data Points (NP)

Figure 1 presents the generated vapor pressure (filled circles) and  the quadratic fit (solid line) of the condensate of Table 1. The extrapolated vapor pressure at X=0 (expansion ratio) is 8.56 psia (59.0 kPa). This extrapolated vapor pressure matches very closely with the predicted bubble point of condensate of Table 1 by ProMax.

Figure 1. Quadratic fit of vapor pressure vs. expansion ratio

Exponential Equation:

The vapor pressures (VP) as a function of expansion ratio (V/L = X) in Table 3 can also be fitted to an exponential equation as follows.

VP = αe(βX)

The fitted parameters α and β are presented in Table 5 for pressures in Table 3 in kPa and psia.

Table 5. Fitted parameters for exponential equation

1AAPD           = Average Absolute Percent Deviation

2MAPD           = Maximum Absolute Percent Deviation

3NP                 = Number of data Points (NP)

Figure 2 presents the generated vapor pressure (filled circles) and the exponential fit (solid line) of the condensate of Table 1. The extrapolated vapor pressure at X=0 (expansion ratio) is 8.56 psia (59.0 kPa). Similar to the quadratic fit, this extrapolated vapor pressure matches very closely with the predicted bubble point of condensate of Table 1 by ProMax.

Figure 2. Exponential fit of vapor pressure vs. expansion ratio

ASTM D6377 RVPE:

The RVPE (Reid Vapor Pressure Equivalent) can be estimated by the following correlations:

a. Average bias of different crude oils [7]

RVPE = A x VPCRX=4 (at 100 °F or 37.8°C) + B

where A = 0.752 and B=0.88 psi (6.07 kPa).

For the condensate of Table 1 and from Table 3, VPCRX=4 = 7.63 psi (52.63 kPa)

RVPE = 0.752 x 7.63 + 0.88 = 6.62 psi

RVPE = 0.752 x 52.62 + 6.07 = 45.64 kPa

b. New correlation for ‘live’ crude  oils (for samples in pressurized ﬂoating piston cylinders) [4]

RVPE = 0.834 x VPCRX=4 = 7.63 psi (52.63 kPa)

RVPE = 0.834 x 7.63 = 6.36 psi

RVPE = 0.834 x 52.62 = 43.89 psi

c. New correlation for ‘dead’ crude oils (for samples in non-pressurized 1-liter sample containers) [4]

RVPE = 0.915 x VPCRX=4 (at 100 °F or 37.8°C)

Summary:

For accurate measurements, standard procedures outlined in ASTM D6377–14 and other guidelines should be consulted.  Several organizations are currently working to improve the accuracy of TVP estimation from RVP and/or VPCRx (ASTM D6377) measurement techniques. In all cases, Federal and State Laws and Regulations should be followed for safety and environmental protection.

A quadratic and an exponential correlation were presented to curve fit the measured vapor pressures at different expansion (V/L = X) ratios (e.g. 1, 2, 3, and 4). To demonstrate ASTM D6377 true vapor pressure measurements, a sample condensate vapor pressures at expansion ratios of V/L = X = 1, 2, 3, and 4 were estimated by ProMax, mimicking vapor pressure measurements. The estimated vapor pressures were curve fitted and extrapolated to zero expansion ratio (V/L = X) to estimate TVP. Then correlations of D6377 were used to estimate RVPE using the vapor pressure measurement at the expansion ratio of V/L = X = 4.

Figures 1 and 2 present almost a linear relationship between vapor pressure vs expansion ratio due to the narrow range of expansion ratio (1 through 4).  As shown in the Appendix, for a wider range of expansion ratios (5 through 50), vapor pressure vs expansion ratio is non-linear. In addition, the quadratic fit with three coefficients gives a better fit compared to exponential fit with only two coefficients.

To learn more about similar cases and how to minimize operational problems, we suggest attending our G4 (Gas Conditioning and Processing), G5 (Advanced Applications in Gas Processing), and PF4 (Oil Production and Processing Facilities), courses.

By: Dr. Mahmood Moshfeghian

References:

1. Campbell, J.M., Gas Conditioning and Processing, Volume 1: The Basic Principles, 9th Edition, 2nd Printing, Editors Hubbard, R. and Snow–McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.
2. ASTM D323: Standard Test Method for Vapor Pressure of Petroleum Products (Reid Method), 1999.
3. Moshfeghian, M., http://www.jmcampbell.com/tip-of-the-month/2016/02/correlations-for-conversion-between-true-and-reid-vapor-pressures-tvp-and-rvp/, 2016
4. ASTM D6377: Standard Test Method for Determination of Vapor Pressure of Crude Oil: VPCRX  (Expansion Method), 2014
5. ProMax 4.0, Bryan Research and Engineering, Inc., Bryan, Texas, 2017.
6. Soave, G., Chem. Eng. Sci. Vol. 27, No. 6, p. 1197, 1972.
ASTM D6377: Standard Test Method for Determination of Vapor Pressure of Crude Oil: VPCRx  (Expansion Method), 2003.

Appendix:

Table 3A. Vapor pressure at 37.8 °C (100 °F) for three expansion ratios

Table 4A. Fitted parameters for quadratic equation

1AAPD       = Average Absolute Percent Deviation

2MAPD      = Maximum Absolute Percent Deviation

3NP             = Number of data Points (NP)

Figure 1A. Quadratic fit of vapor pressure vs. expansion ratio

Table 5A. Fitted parameters for quadratic equation

Figure 2A. Exponential fit of vapor pressure vs. expansion ratio

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## Effect of CO2 on the TEG Vaporization Losses

Continuing the December 2013 [1] Tip of The Month (TOTM), this tip investigates the effect of COin the feed gas, stripping gas rate and the effect of the triethylene glycol (TEG) mass circulation ratio on the TEG vaporization loss from the regenerator and contactor columns top. By performing rigorous computer simulations of a TEG dehydration process, two charts for quick estimation of TEG vaporization losses from regenerator top and contactor top, which can be used for facilities type calculations are developed. In addition, the effect of CO 2 in the feed gas on the TEG vaporization losses for a case study is shown.

### COMPUTER SIMULATION RESULTS

In order to study the effect of CO2, stripping gas rate and TEG mass circulation ratio on the TEG vaporization losses, the TEG dehydration process was simulated using ProMax [2] software with its Soave-Redlich-Kwong (SRK) [3] equation of state (EOS). The process flow diagram used for these simulations is the same as in the November 2013 TOTM [4] and is shown in  Figure 1.

The water-saturated gas with a water content of 915 kg/106 std m3 (57 lbm/MMSCF) enters the bottom of the contactor column at 37.8°C (100°F) and 6897 kPaa (1000 psia) at a rate of 2.835×106 std m3/d (100 MMSCFD). The feed gas studied was either sweet or contained 10 mole % CO2. The contactor column has three theoretical trays. The lean TEG solution enters at the top of the contactor column and flows down in the column. As shown in Figure 1, the water content of the dried gas is 10 mg/std m3 (0.63lbm/MMSCF). The rich TEG solution contains 96.1 mass percent TEG entering the still column at 100°C (212°F) and 515 kPaa (74.7 psia). The reboiler temperature was set at 204.4°C (400°F) and boil-up ratio of 0.1 (molar bases). Two theoretical trays in the regenerator (still) column (NR = 2) and two theoretical trays (NS = 2) in the striping gas section were utilized. The striping gas enters the bottom of the stripping gas section at 204°C (399°F) and 524 kPaa (76 psia). Methane was used for the stripping gas at a rate of 53.6 std m3/h (1893 scf/hr). The regenerated lean solution contains 99.86 mass percent TEG and the ratio of stripping gas to lean TEG liquid volume rates is 20 std m3 of gas/std m3 of lean TEG solution (2.67scf/sgal) or a mass ratio of 28.3. The regenerator (still) top temperature is 91.4°C  (196.5°F). If the same stripping gas was sparged directly into the reboiler (N= 0, no stripping column), with everything else remaining the same, the regenerated solution contains 99.2 mass percent TEG and the regenerator column top temperature remains practically the same and is 91.1°C  (196°F). For the above case (N= 2) the number of theoretical trays in the still column is increased from 2 to 3 (NR = 3); the lean TEG concentration increased slightly from 99.6 to 99.8 mass percent but the regenerator column top temperature remained the same.

Using a similar set up as is shown in Figure 1, several simulations were performed for a range of stripping gas rates, for NR=2, N S=2 and reboiler pressure of 110.3 kPaa (16 psia) and temperature of 204.4°C (400°F). The results of these simulation runs are presented in Figures 2 and 3.

Figure 1. Sample results using ProMax [2] for TEG dehydration with reboiler P=110.3 kPaa (16 psia) with NR=2 and NS=2 [4]

Figure 2 presents the variation of the TEG vaporization losses from still/regeneartor column top with mass circulation ratio and the stripping gas rate. In addtion to the sweet feed gas (solid lines), Figure 2 also presents results for a feed gas containing 10 mole % CO2 identified by the dashed lines.

Figure 2 indicates that as the stripping gas ratio increases the TEG vaporization losses decrease due to the decrease in temperature at the top of the regenerator column. This figure also indicates that as the TEG mass circulation ratio increases, the TEG vaporization losses increases initially due to lower water content of TEG solution, followed by a decreasing trend with the exception for the case of low stripping gas rate. Figure 2 also indicates that the presence of 10 mole % CO 2 in the feed gas has little effect on the TEG vaporization losses from the regenerator column top. Figure 2 can be used for a quick estimate of the TEG vaporization loss from regenerator top for a given stripping gas rate and TEG circulation mass ratio.

Figure 2. Variation of TEG vaporization loss from regenerator top with circulation mass ratio and stripping gas rate at top P=101.3 kPaa (14.7 psia) and reboiler P=110.3 kPaa (16 psia) at 204.4°C (400°F)

As expected Figure 3 indicates that the TEG vaporization loss from the contactor top increases slightly with the stripping gas rate. In addition, this figure shows that as the TEG mass circulation ratio increases beyond 15 mass of TEG/mass of water removed, the TEG losses remain almost constant. The lower mass circulation ratio corresponds to the lower amount of TEG in contractor and lowers vaporization losses.

Figure 3 also shows that the TEG vaporization loss is higher for the feed gas containing 10 mole % CO2(dashed lines) by a factor of about 18%.

The comparison of Figures 2 and 3 indicates that the TEG vaporization loss from the contactor top is almost 10 times higher than the loss from still/regenerator column top.

Figure 3. Variation of TEG vaporization loss from contactor top with circulation mass ratio and stripping gas rate

### CONCLUSIONS

This TOTM studied the effect of CO2 in the feed gas, mass circulation ratio, and stripping gas rate on the TEG vaporization losses from the contactor top and regenerator top. The charts exhibited a quick estimation of the TEG vaporization losses from still/regenerator column top and contactor top at a specified stripping gas rate and TEG mass circulation ratio to achieve the desired level of lean TEG concentration. These are based on the rigorous calculations performed by computer simulations and can be used for facilities type calculations for evaluation and troubleshooting of an operating TEG dehydration unit. In addition, the following observations were made for the cases studied in this TOTM:

>>The TEG vaporization loss from the contactor top is almost 10 times higher than still/regenerator column top (see Figures 2 and 3).

>>Presence of 10 mole % CO2 in the feed gas to contactor column increases the TEG vaporization loss from the top of contactor columns (Figures 3) but has a small effect on TEG vaporization loss from the regenerator column (Figure 2).

>>The results of vaporization loss from the flash tank separator were very small, in the order of 0.0025 lit of TEG/106 Std m3 of gas (0.00002 gal of TEG/MMscf of gas).

>>Though not studied in this TOTM, mechanical losses such as entrainment from contactor top and regenerator top, as well as leaks from pump seals are usually much higher than the vaporization losses presented here.

To learn more about similar cases and how to minimize operational problems, we suggest attending our G4 (Gas Conditioning and Processing), G5 (Practical Computer Simulation Applications in Gas Processing)and G6 (Gas Treating and Sulfur Recovery) courses.

By: Dr. Mahmood Moshfeghian

References

Moshfeghian, M., http://www.jmcampbell.com/tip-of-the-month/2013/12/estimating-teg-vaporization-losses-in-teg-dehydration-unit/, Tip of the Month, December 2013.

ProMax 4.0, Bryan Research and Engineering, Inc., Bryan, Texas, 2017.

Soave, G., Chem. Eng. Sci. Vol. 27, No. 6, p. 1197, 1972.

Moshfeghian, M., http://www.jmcampbell.com/tip-of-the-month/2013/11/estimating-still-column-top-temperature-in-teg-dehydration-unit/, Tip of the Month, November 2013.

Moshfeghian, M., http://www.jmcampbell.com/tip-of-the-month/2013/09/high-pressure-regeneration-of-teg-with-stripping-gas/, Tip of the Month, September 2013.

### One response to “Effect of CO2 on the TEG Vaporization Losses”

1. russr ortiz says:

hi

## Effect of Methanol on Distribution of Sulfur Compounds in NGL Fractionation Train

In the February and May 2010 tips of the month (TOTM) we presented the distribution and concentration of sulfur compounds in an NGL Fractionation Train (NFT) using commercial simulation software [1-3].

Sulfur compounds that may be present in NGL include H2S, COS, CS2, and mercaptans (RSH). These are typically present in low concentrations and are often removed by adsorption on a molecular sieve, reaction with a caustic solution, or amine treating. In addition, the methanol content of the liquid hydrocarbon can be as high as 0.6 mole % (GPA-Midstream RR 149 [4]).

In this TOTM we will present the effect of methanol on the distribution and concentration of the sulfur compounds in the same NFT using ProMax [5] based on the Peng-Robinson equation of state (PR EoS) [6]. The software’s built-in binary interaction parameters were used. The tabular and graphical simulation results are presented. The feed composition, rate, and condition are shown in Table 1.

Table 1. Feed composition and condition [3]

The NFT process flow diagram is shown in Figure 1 [3]. The column and product specifications are shown in Table 2. An overall tray efficiency of 90 % was used for all columns.

Figure 1. Process Flow diagram for NGL Fractionation Train (NFT) [3]

Table 2. Column specification used in simulation [3]

Expected Product Distribution:

Figure 2, like Figure 9 presented by Likins and Hix [7], shows a descending order log scale bar-graph of the pure compounds vapor pressure for the components of interest to this study. The vapor pressures shown in this diagram are calculated using ProMax [5].

This figure shows that COS should distribute to both the ethane and the propane streams. MeSH, with a vapor pressure close to n-butane should distribute primarily with the butanes with a small amount distributing to the pentane stream. EtSH, having a vapor pressure between butane and pentane, should distribute primarily with butane and pentane. CS2 should distribute primarily to the pentane and the C6+ streams with only minor distribution to the butane stream. The heavier sulfur compounds should end up almost entirely in the C6+ stream.

Figure 2. Pure compound vapor pressure at 12.8°C (55°F)

Results of Computer Simulation:

The NFT described in the previous section was simulated using ProMax [5] based on the Peng-Robinson equation of state (PR EoS) [6]. In this study, the built-in (library) binary interaction parameters were used even though we recommend evaluating the accuracy of VLE results against experimental data and if necessary the insertion of VLE data regression into the EoS interaction parameters. This regression may be required to adequately model the systems dealing with mercaptans.

The focus of this study is on the distribution (% recovery) and concentration (PPM) of the sulfur compounds in the product streams in the absence and presence of methanol. Table 3 presents the PPM concentration of sulfur compounds in the feed and product streams. The maximum concentration of each compound in the product streams are shown in red color fonts.

Table 3. Concentration (ppm, mole) of sulfur compounds in the gas and product streams

Figures 2 through 6 present bar-graphs of the recovery of each sulfur compound in the “Gas” and the other product streams. Note in these figures, the “Gas” represents the sum of gas streams 9, 13, and 16. The mole percent recovery is defined as the number of moles of a component in the product stream divided by the moles of the same component in the feed stream (Stream 5).  Figures 8 through 11 present the effect of methanol on the recoveries of the sulfur compounds in the product streams.

H2S and COS:

Figure 3 shows the distribution and recovery of H2S and COS in the Gas, C2 and C3 product streams. As expected, much of the H2S distributes in the gas and the C2 product streams and much of the COS ends up in the C3 product stream. Note H2S in C3 ~ 0.

MeSH: Figure 4 shows the distribution and recovery of MeSH in the Gas, C2, C3, C4, and C5 product streams. Most of the MeSH distributes to the C3 and C4 stream. Note MeSH in C2 and C5 is ~ 0.

Figure 3. Distribution and recovery of H2S and COS in the gas, C2 and C3 product streams (H2S in C3 ~ 0)

EtSH and CS2: Figure 5 shows the distribution and recovery of EtSH and CS2 in the C3, C4, C5, and C6+ product streams. Most of the EtSH ends up in the C4 and C5 streams and most of the CS2 ends up in the C5 stream which are consistent with Figure 1 data. Note EtSH in C3 and C6+ is ~ 0 and CS2 in C6+ is ~ 0.

iC3SH and iC4SH: Figure 6 shows the distribution and recovery of iC3SH and iC4SH in the C4, C5 and C6+ product streams. As expected, iC3SH ends up in the C5 and C6+ streams and all of the iC4SH ends up in C6+ stream. Note iC3SH in the C4 is ~ 0.

Figure 4. Distribution and recovery of MeSH in the Gas, C2, C3, C4, and C5 product streams (MeSH in C2 and C5 is ~ 0)

Figure 5. Distribution and recovery of EtSH and CS2 in the Gas, C2, C3, C4, C5, and C6+ product streams (EtSH in C3 and C6+ is ~ 0 and CS2 in C6+ is ~ 0)

Figure 6. Distribution and recovery of iC3SH and iC4SH in the C4, C5, and C6+ product streams (iC3SH in the C4 is ~ 0)

Effect of Methanol:

To investigate the effect of methanol on the recoveries of sulfur compounds in product streams, the zero concentration of methanol in the feed (stream 5) was changed to 0.01, 0.1, 0.5, and 1 mole %.

As shown in Figure 7, simulation results indicated that almost all of the methanol was distributed only between C4 and C5 product streams. Based on Figure 2, all the of methanol should with go with C6 and C7 but it is not from the same family. Figure 7 also indicates that the level of recoveries in these two product streams is a linear function of the methanol concentration in the feed stream.

Figure 7. Recovery of methanol in product streams vs. its concentration in the feed

The simulation results indicated that the recoveries of H2S, COS, and iC4SH are independent of methanol concentration in the feed. The effect of methanol concentration in the feed on the recoveries of the other sulfur compounds are presented in Figures 8 through 11.

Figure 8 indicates that the presence of methanol in the feed has negligible effect on the recoveries of MeSH in the product streams.

Figures 9 and 10 indicate that the presence of methanol in the feed has appreciable effect on the recoveries of EtSH and CS2 in the C4 and C5 product streams but negligible effect on the C6+ product stream, respectively.

Figure 11 indicates that the presence of methanol in the feed has considerable effect on the recoveries of iC3SH in the C5 and C6+ product streams but negligible effect on the C4 product stream.

Figure 8. MeSH recovery in the Gas, C3, and C4 product streams.

Figure 9. EtSH recovery in the C4, and C5, and C6+ product streams

Figure 10. CS2 recovery in the C4, and C5, and C6+ product streams

Figure 11. iC3SH recovery in the C4, and C5, and C6+ product streams

Conclusions:

The calculation results presented and discussed here are specific to the NGL fractionation train considered in this work, but there are some general conclusions that can be drawn from this study. The results can be summarized as follows:

• The highest concentration of MeSH occurs in the C4 product (stream 20).
• The highest concentration of EtSH occurs in the C5 product (stream 23).
• The highest concentration of CS2 occurs in C5 product (stream 23).
• The highest concentration of iC3SH occurs in C5 Product (stream 23).
• The highest concentration of iC4SH occurs in C6+ Product (stream 24).
• Any methanol in the feed stream will be distributed between C4 and C5 product streams.
• The amount of methanol recoveries in the C4 and C5 product streams is a linear function of the methanol concentration in the feed stream.
• Presence of methanol in the feed has no effect on the recoveries of H2S, COS (the most volatile) and iC4SH (the least volatile) in the product streams.
• Presence of methanol in the feed has little effect on the recoveries of MeSH in the product streams.
• Presence of methanol in the feed has considerable effect on the recoveries of EtSH, CS2 and iC3SH in the product streams. In the absence of methanol, most of these three compounds were distributed in C4 and C5 product streams; therefore, their concentration in these two product streams are affected by presence of methanol.

The binary interaction parameters used in the EoS play an important role in the VLE behavior of the system under study, and affect the distribution of the sulfur compounds present in the feed. Use of improper or incorrect binary interaction parameters may generate erroneous results. Care must be taken to use correct values of binary interaction parameters. In this work, the simulator library values of the binary interaction parameters were used.

The results also indicate that some of these compounds were not distributed among the hydrocarbon products in the same way one would expect from their volatilities and concentrations. This may be explained by the conclusion reported by Harryman and Smith [8, 9] who wrote “iC3SH is formed during fractionation within the depropanizer and the deethanizer.” It should be also noted that the VLE behavior of components in the mixture is not the same as each individual component behavior. Therefore, further evaluation should be conducted to arrive at a concrete decision. This should be a good reason to perform laboratory tests and detailed thermodynamic calculations to determine process flow rates and composition. Detailed process analysis should always be made to justify and prove correct decisions as to selection of process flow schemes.

To learn more about similar cases and how to minimize operational problems, we suggest attending our G4 (Gas Conditioning and Processing), G5 (Practical Computer Simulation Applications in Gas Processing), and G6 (Gas Treating and Sulfur Recovery) courses.

By: Dr. Mahmood Moshfeghian

Reference:

1. Moshfeghian, M. “Distribution of Sulfur-Containing Compounds in NGL Products”, TOTM, Feb 2010.
2. Moshfeghian, M. “Distribution of Sulfur-Containing Compounds in NGL Products by Three Simulators,” TOTM, May 2010.
3. Al-Sayegh, A.R., Moshfeghian, M.  Abbszadeh, M.R., Johannes, A. H. and R. N. Maddox, “Computer simulation accurately determines volatile sulfur compounds,” Oil and Gas J., Oct 21, 2002.
4. Gas Processors Association, “GPA RR-149: Vapor-Liquid and Vapor-Liquid-Liquid Equilibrium for H2S, CO2, Selected Light Hydrocarbons and a Gas Condensate in Aqueous Methanol or Ethylene Glycol Solutions,” 1995.
5. ProMax 4.0, Bryan Research and Engineering, Inc, Bryan, Texas, 2017.
6. Peng, D.Y. and D. B. Robinson, Ind. Eng. Chem. Fundam. 15, 59-64, 1976.
7. Likins, W. and M. Hix, “Sulfur Distribution Prediction with Commercial Simulators,” the 46th Annual Laurance Reid Gas Conditioning Conference Norman, OK 3 – 6 March, 1996.
8. Harryman, J.M. and B. Smith, “Sulfur Compounds Distribution in NGL’s; Plant Test Data – GPA Section A Committee, Plant design,” Proceedings 73rd GPA Annual Convention, New Orleans, Louisiana, March, 1994.
9. Harryman, J.M. and B. Smith, “Update on Sulfur Compounds Distribution in NGL’s; Plant Test Data – GPA Section A Committee, Plant design,” Proceedings 75th GPA Annual Convention, Denver, Colorado, March, 1996.

### One response to “Effect of Methanol on Distribution of Sulfur Compounds in NGL Fractionation Train”

1. Omar Ben Hamed says:

Thanks a lot for this interesting subject.
I just wanted to share my experience and looking for some support in this subject.
We are operating NGL fractionation to produce commercial natural gas, commercial propane and commercial butane. The propane is stored in mounded bullets before it will be exported via 6″ CS pipeline to shipping terminal at 135 km from the processing facility. there was provision for methanol injection in NGL to mitigate hydrate formation whenever there is moisture breakthrough from upstream dehydration unit. It was noted that usage of methanol resulting in propane quality alteration in terms of copper strip test at shipping facility (135 km faraway from processing plant) whilst propane spec when tested at plant is acceptable !!?? Anyone have experienced similar case or have an explanation of that phenomena?

Best Regards
Omar

## Infinite Recycle Impacts on Compression Systems

This TOTM will discuss the phenomenon of infinite recycles and their impacts on design, troubleshooting and optimization to increase oil production simply by adjusting setpoint. As well as flaring reduction, unconventionals, identification and solutions.

Question: If you have an infinite recycle of LPG in your gas processing plant, how much horsepower does your compression system need?

Liquefied Petroleum Gas (LPG) is composed of propane and butane. The pressure at which LPG becomes liquid, called its vapor pressure, varies depending on composition and temperature; for example, it is approximately 220 kPa (32 psi) for pure butane at 20 °C (68 °F), and approximately 2,200 kPa (320 psi) for pure propane at 55 °C (131 °F).

In Figure 1 you have the standard propane refrigeration loop. Compressor (K-100) / Cooler (E100) / Separator (V-100) / JT Valve (VLV-100)/ Chiller Load (E101) and recycle back to the compressor.  Under normal operation, stream No 4 has zero flowrate and the system is a closed loop.  If we were to add an additional stream of pure propane to the system at the compressor suction it creates an infinite loop since the vapor out of V100 will still be zero due to the thermodynamic limits of the phase diagram. This system requires infinite horsepower and the rest of the equipment will need to increase in size as well. The molecules are trapped in a loop.

Figure 1 – Propane Refrigeration Loop

Steady State Process simulators generally handle this situation with an unconverged solution or in some instances negative flowrates.  Why is this important?  Although the simulator will not allow the condition to occur.  It can occur during actual operation.

Figure 2 shows a typical three stage compression system, it is like the propane refrigeration system process line up.  In a typical design where are the compressor discharge scrubber liquids sent?  Generally, it’s the previous stage suction scrubber.  Eventually it makes its way to the dry oil tank.  If the material in the scrubbers has propane and butane as a liquid and then sent to an essentially atmospheric tank the liquids will flash, and then be processed by the Oil Stock Tank Vapor Recovery compressor which will send the molecules back to the compression system.  This can set up an infinite recycle or very large recycle of LPG in the compressor system.

Figure 2 – Typical three stage compression system – notice a similar process in the boxes.

As shown in Figure 3 the system response to this recycle of LPG from compressor scrubbers will be to load the system to its capacity, and then flare.  This flaring breaks the recycle, but at a cost.

Indications that this is occurring at your offshore platform, gas plant, or unconventional tank battery is a hot flare with a smoky tail.  LPG’s have a significantly higher heating value than methane and the smoke is being caused by high temperatures in the flame cracking the LPG, and creating soot.  The flame will be a deep red rather than orange and we feel higher radiation from flare when walking in the area.

Figure 3 – System response to an LPG infinite recycle will be to completely load the system and then flare the excess gas.

Figure 4 shows how the flash gas composition becomes richer and richer in LPG.  This can lead to infinite recycles in the last two separators of the oil stabilization system. The last stage flash has 47% LPG in the vapor flash gas.

Figure 4 – Impact of stage separation on flash gas composition [1]

When we are in the design phase in field development planning gas compositions have a degree of uncertainty.  It is wise to have multiple dispositions for these LPG streams. They need a way out: sales gas, oil or fuel.

DESIGN SOLUTIONS:

1. Pump interstage liquids into the sales gas using a positive displacement pump.  The limitation here is the maximum heating value of the sales gas.  Liquids may need to be gas stripped of water to avoid hydrates.

2. Pump interstage liquids into the stock tanks oil.  The limitation is crude vapor pressure and additional recycling.

3. Operate your interstage compressor discharge coolers at a high enough temperature to avoid liquid accumulation in the discharge scrubbers.  This option increases the horsepower requirements of the next stage since you are sending higher temperature gas forward to the next stage of compression.  This is also a method to deal with recycles and reduce flaring in operation, but will reduce the inlet oil production since you will be using additional compression HP by operating at higher temperatures.

4. Fuel gas – spike the LPG into the low-pressure fuel gas system.  This is a preferred option, but the direct fire equipment must be designed to accommodate the higher heating value.

5. Change the gas composition by adding hydrocarbon dry stripping gas to the crude oil.

6. If unable to send the molecules to the gas (due to Btu limit) or oil (RVP limit) then a separate disposition like Pipeline. Pressurized trucks or a tanker is needed.

7. Add another process – in offshore consider power generator or low salinity waterflood- generation of distilled water using multi-effect evaporation. (e.g. Mechanical Flare)

Bottom line is that all the molecules need an evacuation route.

DESIGN CASE No 1:  Offshore Platform Associated Gas Processing

The case in Figure 5 is taken from “Oilfield Processing of Petroleum-Volume 1- Natural Gas” [2].  No recycling of LPG occurs as all liquids from compressor discharge scrubbers are routed to the sales oil pipeline.

Figure 5 – All compressor discharge scrubbers directly sent or pumped into the sales crude pipeline [2]

CASE STUDY No 2:  NGL Recovery Plant with 50,000 bbl Floating Roof Tank Emissions Issues

The NGL recovery plant (Figure 6) processed a small amount of crude oil and was spiking liquids into the crude.  An infinite recycles developed and the stock tanks were degassing large volumes of LPG.  Notice the large temperature drop of the crude going from 145°F (63°C) to 102°F (39°C) as the fluid flashes into the last stage separator. The design intent was to maximize oil volume and eliminate discharge scrubbers, by utilizing the main train separators.

This recycle was broken by adding hydrocarbon dry residue gas from the NGL plant at the inlet to the Electrostatic Treater mixing with the crude oil, and stripping out the LPG breaking the LPG recycle. (Same location near DeC4 bottoms injection point) The blue and red lines show the paths for the LPG Traps.

Figure 6 – Operational problems caused by infinite recycles / butane trap in an oil processing train leading to floating roof storage tank degassing.

CASE STUDY No 3:

An offshore FPSO (Floating Production, Storage and Onboarding) in the North Sea was in operation for two years and its production was constrained by its compression system.  The flare had a smoky tail.

Question: What would you recommend looking for?

After some process simulations, the pressure in the last stage of oil separation was increased by 0.5 barg (7.25 psig).  This broke the internal infinite recycle of LPG in the oil dehydration train sending the LPG into the crude oil rather than the flash gas to the compressor.  The resulting oil was within contract vapor pressure limits once cooled.

The upside was that inlet oil production was increased 30% immediately with zero capex!

Lesson- you need to visit the site to identify opportunities.  And if the system is running it doesn’t mean there is no opportunity to improve.

UNCONVENTIONAL DESIGNS:

Many unconventional plays have standard tank batteries with Tank Vapor Recovery Systems and/or Thermal Oxidizers.  Numerous plays have very rich associated gas that form these infinite recycles in their flash gas compression and tank vapor recovery systems.  Simply sending the liquids back to the stock tanks or water tanks will not fix this problem.  The molecules must be sent forward to the gas gathering system.  Also, ensure your design will function in the winter and that LPG condensation in suction piping will not occur, and that stock tanks are insulated and heated to prevent reflux condensation in the stock tanks.

QUICK TIPS:

Do not design for a single point of operation. (i.e. 40,000 bopd and 100 MMSCFD)

To ensure that the desing will work make sure to design during the early start-up phase with high or low rates. Additionally, make sure to design for extreme ambient condition variations in Summer/Winter and Day/Night. The design should also work during shutdown and composition changes over the life of the development.

SUMMARY:

Recycles limiting production are frequently found in oil processing facilities worldwide. However, they are easy to identify and fix with setpoint adjustments to increase production. Now that you know how to identify, prevent and take advantage of it for your company…go out and make some process improvements to your systems and make your company more profitable!

To learn more about similar cases and how to minimize operational problems, we suggest attending our G4 (Gas Conditioning and Processing), G5 (Practical Computer Simulation Applications in Gas Processing)PF3(Concept Selection and Specification of Production Facilities in Field Development Projects), PF4 (Oil Production and Processing Facilities), and PF49 (Troubleshooting Oil & Gas Processing Facilities) courses.

By: James F. Langer, P.E.

## Estimate BETX Absorption in TEG Dehydration Process

BETX stands for benzene, ethylbenzene, toluene, and xylene, a group of compounds that all belong to the broader category of Hazardous Air Pollutants (HAPs). Benzene and ethylbenzene are known carcinogens, and have also been shown to cause blood disorders, impact the central nervous system and the reproductive system.  Additionally, Toluene may affect the reproductive, respiratory and central nervous systems.  Xylene may have respiratory and neurological effects as well [1]. BETX components are present in many natural gas streams and are absorbed by the solvent in glycol dehydration and amine sweetening units.

In gas dehydration service, triethylene glycol (TEG) will absorb limited quantities of BETX from the gas. Based on literature data, predicted absorption levels for BETX components vary from 5-10% for benzene to 20-30% for ethylbenzene and xylene [2]. Absorption is favored at lower temperatures, increasing TEG concentration and circulation rate. The bulk of absorbed BETX is separated from the glycol in the regeneration unit and leaves the system in the regenerator overhead stream.

The emission of BETX components from glycol dehydration units is strictly regulated in most countries.  In the U.S., benzene emissions are limited to 1 ton/year (900 kg/year).  Mitigation of BETX emissions is an important component in the design of a dehydration system. Correctly estimating the quantity of absorbed BETX and understanding the factors that affect absorption levels is critical.

Moshfeghian and Hubbard [3] simulated a contactor column with two theoretical stages and a natural gas feed containing methane through n-decane (C1 through C10) and BETX compounds. The BETX concentrations in the feed gas were 400, 100, 50, and 50 ppmv for benzene, toluene, ethyl benzene, and o-xylene; respectively. The concentration of the lean TEG stream was 99.0 weight % TEG, and it was assumed the lean TEG temperature was the same as the feed gas. The feed gas was saturated with water at feed conditions. For each contactor pressure and temperature, the lean TEG circulation ratio was varied. To perform simulation, they used ProMax [4] with the Soave-Redlich-Kwong [5] equation of state (SRK EOS). Based on their simulation results, they presented two diagrams for quick estimation of BETX absorption in TEG dehydration process. Figures 1 and 2 [3] present the BETX absorption % (on weight basis) as a function of TEG circulation ratio and temperature for two pressures of 300 and 1000 psia (2069 and 6897 kPa).

This tip demonstrates application of these diagrams for quick estimation of BETX absorption in a case study. Specifically, TEG dehydration of a natural gas stream containing BETX compounds was considered and the estimated annual mass rate of BETX compounds absorbed by TEG solution. The graphical and hand calculation results were compared with the ProMax [4] simulation results and good agreement was observed.

Finally, an overview of the most commonly used designs for mitigation of BETX emissions will be provided.

.

Figure 1. Approximate BETX Absorption in TEG vs circulation ratio and contactor temperature at 300 psia (2069 kPa) [3]

Figure 2. Approximate BETX Absorption in TEG vs circulation ratio and contactor temperature at 1000 psia (6896 kPa) [3]

Example Problem

100 MMscfd (2.832×106 Sm3/day) of natural gas with a composition shown in Table 1 and saturated with water at feed conditions enters a TEG contactor. The inlet temperature is 110°F (43.3°C) and pressure is 1000 psia (6897 kPa). The outlet water dew point spec is 20°F (-6.7°C). The reboiler is operating at 360°F and there is one theoretical stage of random packing in the stripper.

Determine the quantity of BETX in lbm/year (kg/year) which would be vented to the atmosphere if no remedial actions were taken.

Assumptions: Approach temperature = 18°F (10°C) and lean TEG temperature = feed gas temperature

Solution

Based on the procedure outlined in Chapter 17 of Volume 2 of Gas Conditioning and Processing Book [6], the following parameters were determined:

Using Figure 3 for the lean TEG circulation ratio of 0.17 gpm TEG/MMscfd of gas (1.36 m3/h TEG/106 Sm3/day of gas), BETX absorption weight % for temperatures of 95 and 122°F (35 and 50°C) are presented in Table 2. Note that for 122°F (50°C), the lines were extrapolated by dotted lines for lower flow rates.  By linear interpolation, the estimated values of absorption weight % for temperature of 110°F (43.3°C) are presented in the last column of Table 2.

Figure 3. Estimating BETX Absorption (weight %) in TEG for example at psia (6896 kPa) [3]

For lean TEG concentration of 99.5 weight % and circulation rate of 17 gpm (3.861 m3/hr), the BETX absorption weight % from ProMax simulation results are shown in Table 3. As shown in Tables 2 and 3, there is a good agreement between the estimated BETX absorption weight % from Figure 3 and the ProMax simulation results. The ProMax calculated dry gas water dewpoint was also 20°F (-6.7°C) that matches the specified value.

The annual mass rate of each BETX compound entering the contactor in lbm/yr (kg/yr) can be determined from the following equations.

In the above equations q = 100 MMscfd (2.832×106 Sm3/day), MW (molecular weight) and ppmv (concentration) are given in Table 4. For each BETX compound, the absorbed mass rate of is determined by multiplying mass rate entering the contactor times the corresponding absorption weight % divided by 100.  The calculation results are presented in Table 4. The last two columns of Table 4 present the annual mass rate of each component absorbed in the TEG and subsequently regenerated and vented with the water.

The bulk of absorbed BETX will be vented with the water vapor at the top of the regenerator. The most common emission mitigation strategies are to [3]:

1. Condense the regenerator overhead vapor in a partial condenser and combust the remaining vapor.  The uncondensed vapors are typically routed to an incinerator or, if a direct-fired reboiler is used, routed to the reboiler fuel gas. The liquid hydrocarbons are collected and disposed of by blending into a crude oil or condensate stream.  The condensed water is typically routed to produced water disposal.

2. Route the regenerator overhead vapors to another process stream in the facility. This is typically a low-pressure stream such as flash vapors from the last stage of a crude or condensate stabilization system.

From an operational point of view, minimizing circulation ratio is the most effective way of decreasing the absorption of BETX components. This also minimizes reboiler duty and the size of the regeneration skid. Lower TEG circulation rates require more theoretical stages in the contactor to meet outlet water content specifications, but the additional cost of a taller contactor is often offset by savings in the regeneration package. Care should be taken that the glycol circulation rate is sufficient to ensure adequate liquid distribution over the packing. Packing vendors can provide minimum circulation guidelines.

Summary

Figures 1 and 2 present a simple tool for quick estimation of absorption of BETX compounds in TEG dehydration process. For the case study considered in this tip, the estimated absorption weight % for each of BETX compounds matched well with the ProMax simulation results.

To learn more about similar cases and how to minimize operational problems, we suggest attending our G4 (Gas Conditioning and Processing), G5 (Advanced Applications in Gas Processing),  and PF49 (Troubleshooting Oil & Gas Processing Facilities) courses.

### One response to “Estimate BETX Absorption in TEG Dehydration Process”

1. Alfred King says:

1. What is the effect of high levels of CO2 in the feed gas which bypass an upstream sweeting unit for emergency situations.

2. What is the effect of high levels of mercury on the BTEX absorpation and in the glycol closed loop system. Supposedly can reach 40 microgram/m3

3. What is the effect on the TEG system and BTEX absorption due tomsalts in the feed gas carried out from inlet separation that supposedly separate the formation water

4. How can we deal with BTEX in the vent stripper rather than destructive and Drizo techniques.

## Low Temperature Methane Gas Water Content

In the past tips of the month (October, November, December 2007, January 2011, February, September 2014. And April 2015), we studied in detail the water phase behaviors of sweet and sour natural gases and acid gas systems. We evaluated the accuracy of different methods for estimating the water content of sweet and sour natural gases as well as for acid gas systems. In addition, correlations to estimate vapor water content of lean sweet and sour gases were presented.

For normal gas conditioning processes, the water vapor content of natural gases in equilibrium with water is commonly estimated from McKetta and Wehe [1] based charts like Figure 6.1 of Campbell book [2] or Figure 20.4 of Gas Processors and Suppliers Association [3]. This tip presents a chart for estimating methane gas water content at low temperatures, e.g. cryogenic processes.

Hydrate formation is a kinetic (time dependent) process. During this transient “hydrate formation period” the liquid water present is termed “metastable liquid.” Metastable water is liquid water that, at equilibrium, will exist as a hydrate. At temperatures below the hydrate temperature of the gas, the “condensed” phase will be a solid (hydrate). The water content of a gas in equilibrium with a hydrate will be lower than equilibrium with a metastable liquid. The water content of gases in the hydrate region is a strong function of composition. Page 153 of Campbell book [2] provides more detail.

Figures 1A (SI, international system of units) and 1B (FPS field system of units) present a chart for methane gas water content for temperature range of 0 °C to -80 °C (32 °F to -110 °F) and pressures of 0.345 MPa, 3.45 MPa, and 6.9 MPa (50 psia, 500 psia, and 1000 psia). The chart is based on the experimental data reported in GPA-Midstream RR 187 [4] for pressures of 3.45 and 6.9 MPa (500 and 1000 psia) and the results generated using ProMax [5] freeze model (Solid-Vapor-Equilibrium) at low pressure of 0.345 MPa (50 psia).

Figure 1A (SI). Low temperature methane gas water content
(Dashed lines are GPA-Midstream RR 187 data [4], solid line predicted using ProMax [5])

Figure 1B (FPS). Low temperature methane gas water content
(Dashed lines are GPA-Midstream RR 187 data [4], solid line predicted using ProMax [5])

Based on the methane hydrate formation diagram shown in Figure 2, the above-mentioned low temperatures are generally below the hydrate formation temperature at the corresponding pressures. Therefore, the water contents reported in Figures 1A and 1B are in equilibrium with hydrates.

Figure 2. Methane hydrate formation temperature as a function of pressure

Summary

Figure 1 presents a simple chart to estimate methane gas water content in equilibrium with hydrates. The water content of gases in the hydrate region is a strong function of composition. Where experimental data is unavailable, utilization of an EOS-based correlation that has been tuned to empirical data can provide an estimate of water content in equilibrium with hydrates.

To learn more about similar cases and how to minimize operational problems, we suggest attending our G4 (Gas Conditioning and Processing), G5 (Practical Computer Simulation Applications in Gas Processing), and PF49 (Troubleshooting Oil & Gas Processing Facilities), courses.

By: Dr. Mahmood Moshfeghian

Reference:

1. McKetta, J. J., and Wehe, A. H., “Use This Chart for Water Content of Natural Gases,” Petroleum Refiner (Hydrocarbon Processing), Vol. 37, No. 8, p. 153, August 1958.
2. Campbell, J.M., Gas Conditioning and Processing, Volume 1: The Basic Principles, 9th Edition, 2nd Printing, Editors Hubbard, R. and Snow–McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.
3. GPSA Engineering Data Book, Section 20, Volume 2, 13th Edition, Gas Processors and Suppliers Association, Tulsa, Oklahoma, 2012.
4. Song, K. Y., Yarrison, M., Kobayashi, R., and W. Chapman, “Low Temperature V-L-E Data for Water, CO2, and Light Hydrocarbon Systems,” Gas Processors Association Research Report RR 187 Tulsa, Oklahoma, 2005.
5. ProMax 4.0, Bryan Research and Engineering, Inc., Bryan, Texas, 2017.

## Oil Dehydration Design Error Found in Most Designs Worldwide

This tip of the month (TOTM) discusses how to “avoid a costly design error found in most oil dehydration systems worldwide”.

• Are you having reverse emulsion problems?
• Are you having problems meeting your discharge oil in water specifications.

An area to look for immediately is the Process Flow Diagram (PFD).  Normally systems work as they were designed. In cases where I have visited sites experiencing problems…the problem is the design.

Why does this occur? The world we deal with is more complex than process simulation models. They are simply thermodynamic models to predict the phase separation of multicomponent systems and perform heat and energy balances. They are useful and very well proven tools. Most designs however; do not consider the various chemicals, presented in in Table 1, that are added to a system on a routine basis.

Table 1. Example of various problems and their typical treatment

Most of these chemicals are added to a system to improve a designs performance in oil water and water oil separation. Most of these chemicals are used in parts per million (ppm) fashion using proprietary formulations from Chemical Companies. Most assets will spend \$5-\$10 Million dollars per year on the use of these formulations. The ability to add the chemicals is included in most designs, but their effects are not normally included in the designs and it’s left to Field Operations and the Chemical Companies to come up with a solution.

So, What’s the design error? It’s mixing fluids that have come into contact with both oil treating and water treating chemicals and then recycling them back to the front of the process.

What are these streams?

• Oil skims from WEMCOs (induced gas floatation manufacture by Western Equipment Manufacturing Company) or Flotation Cells are routinely re-routed back into the Oil Dehydration Train.
• Hydrocyclone Oil Skims
• Closed Drain Oil Skims

I would encourage you to check this out at your asset using the real fluids. I perform this demonstration during the Petroskills PF-3 Course. I take a 50% water cut sample of a 45 API Gulf of Mexico Crude Oil and produced water. I shake it up and the emulsion resolves in less than 30 seconds back into oil and water. I then add 5 -10 ml of Demulsifier and Water Clarifier being used on the Platform. Shake this up and voila… instant chocolate milk emulsion. This emulsion will not resolve in days. How is the emulsion resolved? We send it to a heater treater. In class I use a coffee cup of hot water. Let it heat soak for a couple of minutes and the sample resolves into three phases as shown in Figure 1: Oil / a scrambled eggs rag layer (complex emulsion- reverse and normal) / Water. The rag layer is normally about 25% of the total sample. This rag layer is very stable, and I have had samples stay stable for over one year.

Figure 1. Oil water complex emulsion

Never send these skims back into your main process. Consider sending them directly to the sales oil LACT. Most contracts allow you 3-5% BS&W. Use the contract to your advantage. You will not be able to break these emulsions with your existing process and they will continue to build. Some operators send them to the beach as hazardous waste for further processing. Other operators have a separate slop oil system for treating with higher temperatures, and then send streams to the sales LACT (Lease Automatic Custody Transfer), but never back into the process.

Every process needs a trash can for off spec product. Offshore it’s the closed drain tank / open drain tank. Never recycle this material back into the main oil dehydration system. Why? Let’s look at what fluids enter the closed and open drain tanks?

• Engine Lube Oils – these contain polymers that will generate emulsions
• Oxygenated water from rain. Oxygen will corrode your main production system.
• Oily Deck Drains from skid pans

How to become an Expert?

Use sources such as SPE’s One Petro. Chances are that sometime, somewhere, someone has faced the same issue you are trying to solve.  In your company is it easy to publish a paper or are there controls and bureaucracy? In most instances, it’s not easy. What does it say to you about the person who has taken the time and written a paper. They want to communicate!  What do you think their reaction will be if you contact them about their paper to get further information? They usually will be very happy to discuss the paper and give you even more insights / tips / advice / recommendations for your situation. It’s a way of leveraging your time, and getting to solutions quickly.

I once made a trip to an FPSO Offshore Brazil that was having water treating problems. They made the same design mistakes discussed in this TOTM. I searched One Petro and found another FPSO Offshore Brazil that faced similar issues and how they were solved [1]. The paper is listed in the references of this TOTM. Here is the recommendation from SPE 90409 paper:

Oil Reject Skid. To provide a positive path for removing oily solids and chemically stabilized emulsions from the process, an oil reject skid was installed on 135 D to receive hydrocyclone reject liquids and skimming from the surge drum, as well as skimming from the sparger IGF vessels. In the oil reject vessel (Fig. 9), larger solids are removed from the cone bottom, while oily solids and chemically stabilized emulsion separates into an oil-continuous phase that is pumped off the platform without recycling back into the process. The volume of this emulsion is low, a few barrels per day, so the impact on the BS&W of crude leaving the platform is low, increasing it by approximately 0.05 %. The clarified water is returned to one of the degasser vessels, from which it reenters the water treatment process. The oil reject skid installation has been one of the major contributors to the ability of 135 D to reliably reduce the TOG of the produced water to < 20 mg/L.”

To learn more about similar cases and how to minimize operational problems, we suggest attending our G4 (Gas Conditioning and Processing), G5 (Practical Computer Simulation Applications in Gas Processing), PF3 (Concept Selection and Specification of Production Facilities in Field Development Projects), and PF49(Troubleshooting Oil & Gas Processing Facilities), courses.

Reference:

1. Chifon Yand, Michel Gabrun, and Ted Frankiewicz, “Identification and Resolution of Water Treatment Performance Issues on the 135 D Platform,” SPE 90409, SPE Annual Technical Conference and Exhibition, Houston, Texas, 26-29 September, 2004.

# Finding Opportunities Checklist

This Tip of the Month (TOTM) discusses places to look for opportunities to increase production quickly. I’ll discuss the concepts, techniques, and later where to look for and find opportunities….to be able to answer the Key Question: “Are we getting the most from our Asset?”

• Do you know how your asset makes money?  Is it simply oil price, and gas price?
• Do the prices of oil and gas change daily?
• Do you adjust your operating conditions based on the prices of oil and gas?
• Does fuel gas have any value?

BENCHMARKING AGAINST PHYSICS™

What are your process Key Performance Indicators?

• Energy Consumed per boe (barrel of oil equivalent) produced?
• Theoretical Energy Required per boe produced?
• Design Energy required per boe produced?

WHERE ARE THE GAPS?

How do you evaluate the performance of your:

• Pumps
• Compressors
• Processes
• Oil / Water Dehydration
• Gas Dehydration
• Gas Treating

Figure 1: Technical Limit Diagram or Choke Model

Looking at the Technical Limit Diagram (Choke Model) shown in Figure 1, where could there be opportunities?

• How can we use the current equipment to increase production?
• What’s the cost of one day of downtime?
• What’s the monetary value of the annual flare volume?
• How can we increase inflow from the wells to increase production?
• Can we reduce the inlet pressures to the facilities to increase reservoir inflow?
• Are we holding backpressure on the facilities, or are we floating the sales gas pipeline?
• Are there any excessive pressure drops in the flowlines/equipment?
• Scale
• Remove choke internals

COMPRESSORS

• Energy Efficiency:
• What’s the position of the recycle valve? Are you wasting energy?
• Reciprocating: Adjust Pockets / re-cylinder
• Centrifugal: Consider re-wheeling
• Can you reduce the suction temperature of the compressors to increase available HP
• Infinite Recycling of LPG
• Is this occurring in your compression system?
• What’s causing downtime of your machines?
• Could your upstream separators be carrying over liquids?

HEAT EXCHANGERS

• Have the overall heat transfer coefficients become lower?
• Have the pressure drops increased?

PUMPS

•  What’s the position of your centrifugal pump discharge control valve?
• Do you have too much HP, consider re-wheeling
• Are you shearing and creating a lot of emulsion requiring higher chemical costs?

SPECIFICATIONS

• Challenge sales specifications.
• Are we over treating?
• How’s our crude vapor pressure (RVP)?
• Are we over stabilizing?
• How’s our crude BS&W?
• Are we over treating?

REDUCE OPEX

• Chemical Costs: Demulsifier
• Are we over dosing?
• Are we adjusting the chemical injection rate base on changes in the inlet gross rate?
• Have we done a “shootout” with other vendors, and allowed treating to failure point?
• Are there recycle streams we can eliminate from the process and treat separately?
• Do we have an OPEX model?
• Have we identified our fixed and variable costs?
• What’s the cost of fuel?  Is fuel free?
• What’s the cost of flaring?
• Are there operating cost differences between “A crew” and “B crew”?
• Set up a competition between “A crew” and “B crew”.  Bbls produced, \$ energy used per bbl, \$ gas flared/bbl

DOWNTIME

• How many times have we repaired this pump this year? Or over its life to date?
• What’s the cost of downtime in \$/hr?  How many \$ in revenue has we lost this quarter?
• How long does it take to repair?  Do we need a new seal design?  More spare parts?

CAPITAL PROJECTS

What could we add to increase production?

• Is inlet compression profitable? (Lease / Purchase)

FLARE

Is the flare smokey?

• This means its rich gas containing propane / butanes worth more than methane.  It’s a place to look for process changes to prevent the loss of these higher valued components.

WELLS

• What’s the effect of increasing the tubing size?
• What’s the effect of optimizing the gas lift?
• Do all injection wells need the same maximum pressure for gas lift or water injection? Can we segregate the system?
• Do the wells need stimulation?
• Do the wells need water shutoff?
• Manifolds – Are there leaking check valves allowing backflow from an HP well into an LP well?

Case 1: Different Molecules have different values in the Gas and Oil.  Are you maximizing the value of your products?

Offshore in the Gulf of Mexico, some contracts allow higher vapor pressure in the sales crude oil during the winter months.

KEY QUESTION: How can you take advantage of this opportunity?

Generally, selling molecules as oil has been more valuable than selling the molecules as gas.  So how can you send more of smaller LPG molecules into the sales crude oil to increase the number of crude oil barrels sold?

As you learned about vapor pressure and phase diagrams in G4 (Gas Conditioning and Processing course) you simply have to increase the pressure of the final separation, and decrease its temperature.  In winter months by lowering the oil dehydration train temperature, and increasing its pressure you increase the vapor pressure in the sales oil tank, and increase the number of barrels sold.  You can generate millions of dollars per year, by simply adjusting a temperature control setpoint and a pressure control setpoint. For Zero CAPEX.

Case 2: High Gas Prices

For a short period in 2000 a unique opportunity presented itself.  Gas Prices Spiked!

KEY QUESTION: How do we take advantage of this opportunity?

Simply send your molecules into the gas sales by dropping the oil dehydration treater pressure and raising its temperature.  Many Operators in the GOM took advantage of this opportunity. Some just sat and watched!

To learn more about similar cases and how to minimize operational problems, we suggest attending our G4 (Gas Conditioning and Processing), G5 (Advanced Applications in Gas Processing), PF3 (Concept Selection and Specification of Production Facilities in Field Development Projects), and PF49 (Troubleshooting Oil & Gas Processing Facilities), courses.

By: James F Langer, P.E.

### 2 responses to “Get the most from your asset with this checklist”

1. James, thanks for the article.

I support the message you got.

For the wells part, don’t forget to open/remove well chokes as they are the biggest performance gap of all so far in the industry. The reservoir recovery will also go up, no worries.

The “can of beans” study clearly explains this: https://www.youtube.com/watch?v=RPrBpKXpcZk&t=8s

Thanks,
Mikhail

2. The couples who confront enemies can sometimes be the same couples who confront demons.