This tip is the follow up of the previous tips (April and May 2016) [1-2], which investigated the benefits of having a water-draw and its optimum location in a condensate stabilizer column [see chapter 16 of reference 3]. It will simulate the performance of an operating condensate stabilizer column equipped with side water-draw tray to remove liquid water. Recall from the April 2016 TOTM, water can become trapped internally within a condensate stabilizer. The column operating conditions result in water condensing within the column and becoming trapped.  The overhead temperature is too cool and the bottoms temperature is too hot to allow the water to leave the column in either of the product streams.  As a result, liquid water build-up will occur within the column reducing capacity, and depending upon composition, increasing corrosion.  Eventually the water build-up will cause the column to flood, and the major disruption in the tower operations allows the water to be removed.  After this event, the column will operate normally until sufficient time that enough water has accumulated to cause the column to flood once again.  A properly located water-draw off tray will allow for proper column operation and eliminate the operating problems associated with water build up.

In this case study, a stripping sweet gas stream is also utilized to achieve low H₂S content and stabilized condensate at a specified reboiler temperature. The tip will perform three-phase (vapor, liquid hydrocarbon, and aqueous phases) calculations on the trays with excessive/free water rates. Specifically, it will study possible locations of a water-draw tray based on the profiles for water partial pressure in the vapor phase and water rates in the light and heavy liquid phases. The tip will present a summary of the computer simulation results and the key diagrams for the same plant.

Case Study:

Table 1 presents the raw condensate and stripping gas compositions, rates and conditions. Figure 1 presents a simplified process flow diagram equipped with stripping gas and water-draw tray for stabilization of a raw condensate. The 3-phase separator upstream of the stabilizer column removes essentially all excess/free water. The tip utilizes the front mixer to recombine the light and heavy liquid (excess free water) streams feeding to the column for the simulation purpose only. Table 2 presents the stabilizer column specifications. While location of the water-draw tray is 7 in this figure, the tip also considered tray locations at 5, 8, 9, 17, and 18.

The stripping sweet gas stream lowers the H₂S content of the stabilized oil and achieves the desired condensate vapor pressure at the specified reboiler temperature. Table 2 presents the specified column variables. Stream 2 is the overhead vapor and stream 3 is the stabilized condensate.

Based on the data in Tables 1 and 2, and the process flow diagram of Figure 1, the tip performed simulation using the Soave-Redlich-Kwong (SRK) equation of state [4] in ProMax [5] software.

Table 1. Feed and stripping gas compositions, rates and conditions

Figure 1. A simplified non-refluxed stabilizer column with side water-draw and stripping gas

Table 2. Condensate stabilizer column specifications

Simulation Results:

The tip varied the boil-up ratio in the reboiler to match the stream 3 plant temperature of 482 °F (250 °C). The resulting boil up-ratio of 76.5 % is presented in Table 2 and Table 3 presents the comparison between simulation results of this work with plant data. Overall, a reasonable agreement is observed.

Table 3. Comparison of simulation results with plant data

Figure 2 presents the water partial pressure profile for cases of no water-draw and water-draw at either tray of 7, 8 or 9. In this figure, a large spike of water partial pressure is observed on tray 18 for the cases of no water-draw tray. For the case of no water-draw, a bump in water partial pressure is also observed at tray 10 due to the presence of water in the stripping gas that enter the column on tray 10.

Similarly Figures 3 and 4 present the water rate profiles in the light (liquid hydrocarbon) and heavy liquid (aqueous) phases, respectively. These figures show the water rate profiles for no water-draw and water-draw tray at either tray 7, 8, or 9. In these figures, a large spike of water rate profile is observed for the case of no water-draw tray.

Figure 4 indicates that below any of the water-draw trays the light (hydrocarbon) liquid phase is under-saturated with water and there is no free water (heavy liquid phase). For the case of no water-draw, the light liquid phase remains saturated with water along trays 1 through 18.

Figure 5 indicates that the presence of a water-draw tray has no significant impact on the column temperature profile.

In all cases the location of a water-draw tray has no impact on Reid Vapor Pressure (RVP) of neither condensate nor the reboiler duty. The calculated RVP for all cases was 8.2 psi (56.6 kPa) and the calculated reboiler duty for all cases was 18.378 MMBtu/hr (5.376 MW). Table 4 presents the impact of water-draw location on the rate of water removed. This table indicates that water rate at either trays of 5 through 9 practically is the same amount.

Figure 2. Water partial pressure profile in the stabilizer column for several cases

Figure 3. Water rate in light liquid phase in the stabilizer column for several cases

Figure 4. Water rate in heavy liquid phase in the stabilizer column for several cases

Figure 5. Temperature profiles in the stabilizer column for several cases

Table 5 presents the percent recovery (ratio of a component rate in the condensate to its rate in the feed stream) of selected components in the stabilized condensate. Practically, all ethane and lighter components (N₂, C₁, CO₂, and H₂S) leave in the column overhead. Table 5 indicates that the presence of a water-draw tray has some effect on propane and little effect on butane but no effect on other component recoveries.

Table 4. Impact of water-draw tray location on removal water rate

Table 5. Recovery of selected components in the stabilized condensate

Conclusions:

The tip investigated the location of side water-draw and its impact on the performance of the stabilization column. Based on the results obtained, this tip presents the following observations.

1. The water-draw rate at either trays 5 through 9 is the same.
2. The water draw tray location had no impact on the RVP of stabilized condensate.
3. The water draw tray location had no impact on the reboiler duty.
4. The water draw try improved the propane recovery.

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.

PetroSkills offers consulting expertise on this subject and many others. For more information about these services, visit our website at http://petroskills.com/consulting, or email us at consulting@PetroSkills.com.

By: Dr. Mahmood Moshfeghian

Reference:

1. Moshfeghian, M., April 2016 tip of the month, PetroSkills | John M. Campbell, 2016.
2. Moshfeghian, M., May 2016 tip of the month, PetroSkills | John M. Campbell, 2016.
3. Campbell, J.M., Gas Conditioning and Processing, Volume 2: The Equipment Modules, 9^th Edition, 2^nd Printing, Editors Hubbard, R. and Snow–McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.

1. Soave, G., Chem. Eng. Sci. 27, 1197-1203, 1972.

ProMax 4.0, Bryan Research and Engineering, Inc., Bryan, Texas, 2016.

The TEG (triethylene glycol) gas dehydration process removes a considerable amount of methanol from a wet gas stream. if the methanol content of the wet gas is high, the dry gas may still retain high methanol content and can cause operational troubles in the downstream processes.

Continuing the October 2010 tip of the month (TOTM), in this TOTM we will consider the presence of methanol in the produced oil/water/gas stream and determine the quantitative traces of methanol ending up in the TEG dehydrated gas. To achieve this, we simulated by computer an offshore production facility consisting of oil/water/gas multistage-separation, compression and TEG dehydration processes and determined the methanol concentration in the dried gas. We also studied the effect of wet gas temperature and pressure, the number of theoretical trays in the TEG contactor, the water content spec of dry gas, and lean TEG solution circulation rate on the dried gas methanol content. For this purpose, methanol content in the production stream was assumed to vary from zero to 350 PPM (V).

Based on the computer simulation results, the tip develops simple charts and correlations to estimate the methanol removal efficiency in a TEG contactor column under various operating conditions. These charts and correlations are accurate enough for facilities calculations.

Case Study:

The same case study presented in the October 2010 TOTM is used to study the methanol removal in a TEG contactor column. A simplified process flow diagram (PFD) for the offshore production facility is shown in Figure 1 [1]. The production stream (oil, water, gas, and methanol) was passed through the high pressure separator where free water and gas were separated and the oil was passed through the intermediate and low pressure separators for subsequent gas separation from oil. The separator’s off gas streams were recompressed and cooled to 4830 kPa and 35 °C (700 psia and 95 °F) before entering the TEG contactor for dehydration. The dried gas was compressed further (not shown in the PFD) to 23200 kPa (3365 psia) for reinjection or export purposes. To meet a water content spec of 32 mg/Sm³ (2 lb_m/MMscf) or lower, a lean TEG concentration of 99.95 weight percent was used in all of the simulation runs. This tip uses ProMax [2] simulation software with the “PR EOS” property package to perform all of the simulations.

To study the impact of methanol (MeOH) concentration and determine the traces in the TEG dehydrated gas, the MeOH content of the production stream feed to the high pressure separator was assumed to vary from 0 to 350 PPM (V). This variation of MeOH content was chosen due to the uncertainty of its concentration in the production stream. The wet compressed gas temperature is an important parameter in the operation of a TEG unit and affects the water content of dried gas and the required lean TEG solution circulation rate and/or the number of required theoretical trays in the contactor. Depending on the design and/or operational problem like scaling on the cooling side of the gas cooler, the wet gas temperature may be higher than 35 °C (95 °F). Therefore, the wet gas temperature was assumed to vary from 35 to 50 °C with 5 °C increments (95 to 122 °F and 9 °F increment). Depending on the requirement, 2 or 3 theroetical trays (xtheoreticalx) were (xwasx) used in the contactor unit. For each case the lean TEG solution rate was varied to meet the desired water content specification for each case.

To study the impact of pressure, in addition to pressure of 4830 kPa (700 psia), a wet gas pressure of 7000 kPa (1015 psia) was also used.

For each simulation run, the methanol removal efficiency (MRE) was calculated by the following equation.

Figure 1. Simple process flow diagram used in this case study [1]

Results and Discussions:

Table 1 shows sample calculation results for two theoretical trays and wet gas pressure of 4830 kPa (700 psia) and four temperatures. For each temperature the wet gas methanol content was varied in the range of 0 to 112 PPM on molar basis. In each case, the lean TEG solution circulation rate was adjusted to meet the dry gas water content of 16 mg/Sm³ (1 lb_m/MMSCF). Analysis of Table 1 indicates that for each wet gas temperature, the circulation ratio and methanol removal efficiency were independent of the wet gas methanol content. Therefore, for each wet gas temperature, the average circulation ratio and methanol removal efficiency were calculated and presented in Table 2. Similar to the results of tables 1 and 2, seven more tables were generated for 2 and 3 theoretical trays, dry gas water contents of 16 and 32 mg/Sm³ (1 and 2 lb_m/MMSCF), pressures of 4830 and 7000 kPa (700 and 1015 psia).

Table 1. Sample results for two theoretical trays and wet gas pressure of 4830 kPa (700 psia)

Table 2. Average results for two theoretical trays and wet gas pressure of 4830 kPa (700 psia)

The summary for all of the simulation results for methanol removal efficiency as a function of the lean TEG solution circulation ratio for 2 and 3 theoretical number of trays at two pressures, and two dry gas water content specifications are presented in Figures 2 and 3, respectively.

Analysis of Figures 2 and 3 indicates that for each pressure the results for dry gas water content of 16 and 32 mg/Sm³ (1 and 2 lb_m/MMSCF) specifications follow the same trend and can be represented by a single curve. Therefore, the methanol removal efficiency as a function of the lean TEG solution circulation ratio can be expressed by a single correlation for each pressure and number of theoretical trays independent of the wet gas methanol content and temperature.

Figure 2. Average methanol removal efficiency vs circulation ratio for 2 theoretical trays

Figure 3. Average methanol removal efficiency vs circulation ratio for 3 theoretical trays

A non-linear regression program was used to determine the parameters of the following correlation for the methanol removal efficiency (MRE) as a function of the lean TEG solution circulation ratio.

Where:

MRE         = Methanol Removal Efficiency on the mole basis, %

CR             = Circulation ratio, liter TEG/kg water (gallon TEG/lb_m water)

Table 3 presents the regressed parameters of “a” and “b” of Equation 1 for two and three theoretical trays and the wet gas pressures of 4830 and 7000 kPa (700 and 1015 psia). The last two rows in Table 3 present the Average Absolute Percent Error (AAPE) and the Maximum Absolute Percent Error (MAPE) for different units of lean TEG solution circulation rate.

Table 3. Parameters of Equation 1 for methanol removal efficiency

The MRE predictions by Equation 1 were added to Figures 2 and 3 and are presented in Figures 4 and 5. In these two figures the solid lines present the MRE prediction by Equation 1 and symbols represent simulation results. The filled symbols represent the dry gas water content of 16 mg/Sm³ (1 lb_m/MMSCF) and the no fill symbols represent the dry gas water content of 32 mg/Sm³ (32 lb_m/MMSCF). The analysis of Figures 4 and 5 and the calculated low values of AAPE and MAPE in Table 3 indicate that accuracy of the proposed correlations, compared to the simulation results, is good for estimation of methanol removal efficiency (MRE).

Conclusions:

Based on the results obtained for the considered case study, this TOTM presents the following conclusions:

1. The methanol removal efficiency is independent of the wet gas methanol content (Table 1).
2. As the wet gas temperature increases, the lean TEG solution circulation ratio increases; therefore, methanol removal efficiency increases (Table 2). The wet gas water content is a strong function of temperature. As temperature increases, the wet gas water content increases; therefore, for a fixed number of trays the required lean TEG solution rate increases.
3. As the wet gas pressure increases, the absorption of methanol increases; therefore, methanol removal efficiency increases (Figures 4 and 5). The wet gas water content is a function of pressure. As pressure increases, the wet gas water content decreases; therefore, for a fixed number of trays the required lean TEG solution rate decreases but this decrease in rate is offset by higher solubility of methanol at higher pressure.
4. For the same TEG contactor number of trays and pressure, the methanol removal efficiency as a function of circulation ratio for different dry gas water specifications follows the same trend (Figures 4 and 5).
5. The tip presents two simple charts (Figures 4-5) and a correlation (Equation 1) along with its parameters (Table 3) for estimating the average methanol removal efficiencies for 2 and 3 theoretical trays and pressures of 4830 and 7000 kPa (700 and 1015 psia), respectively.
6. Compared to the rigorous computer simulation results, the accuracy of the proposed correlations (Equation 1, and Table 3) to estimate the average methanol removal efficiency provides good agreement to simulation results. This correlation, and Figures 4 or 5 can be used to estimate MeOH removal performance in TEG facilities operating at similar conditions.
7.  The proposed correlations (Equation 1) and charts (Figures 4-5) are easy to use, and provides a simple approach to estimate MeOH removal efficiency in TEG units without access to a process simulator.

Figure 4. Average methanol removal efficiency vs circulation ratio for 2 theoretical trays

Figure 5. Average methanol removal efficiency vs circulation ratio for 3 theoretical trays

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

PetroSkills | Campbell offers consulting expertise on this subject and many others. For more information about these services, visit our website at http://petroskills.com/consulting, or email us at consulting@PetroSkills.com.

References:

1. Moshfeghian, M., October 2010 tip of the month, PetroSkills | John M. Campbell, 2010.
2. ProMax 4.0, Bryan Research and Engineering, Inc., Bryan, Texas, 2016.

Charts and Correlations for Estimating Methanol Removal in the Gas Sweetening Process

The gas-sweetening process by amines like methyldiethanolamine (MDEA) removes a considerable amount of methanol from a sour gas stream. Moreover, if the methanol content of the sour gas is high, the sweet gas may still retain high methanol content and can cause operational troubles in the downstream processes. Provisions of purging reflux (Water Draw) of the regenerator column and its replacement with “Fresh Water” can improve methanol recovery [1, 2].

The July 2016 tip of the month (TOTM) considered the presence of methanol in the sour gas stream and determined the quantitative traces of methanol ending up in the sweet gas, flash gas and acid gas streams [2]. It simulated a simplified MDEA gas-sweetening unit by computer and studied the effect of sour gas methanol content, and the rate of replacing condensed reflux with fresh water on the sweet gas methanol content. For the sour gas temperature of 43.3 and 32.2 °C (110 and 90 °F) the tip studied three inlet gas methanol contents of 50, 250, and 500 PPM on mole basis. In each case the tip varied the rate of fresh water replacement from 0 to 100 % by an increment of 20%.

The methanol removal efficiency (MRE) on the volume basis is defined by:

Table 1 presents the summary of calculated methanol removal efficiency (MRE) based on the simulation results of the July 2016 TOTM [2].

Table 1. The effect of purging and sour gas temperature on methanol removal efficiency [2]

In continuation of the July 2016 TOTM, this tip will consider the presence of methanol in the sour gas stream and determine the quantitative traces of methanol ending up in the sweet gas, flash gas and acid gas streams. This tip simulates a simplified MDEA gas-sweetening unit by computer simulation [3, 4]. This tip also studies the effect of sour gas methanol content, temperature and the rate of replacing condensed reflux with fresh water on the sweet gas methanol content.

For the sour gas temperatures of 43.3, 32.2 and 21.1 °C (110, 90, and 70 °F) the tip studies three inlet sour gas methanol contents of 50, 250, 500 PPM on mole basis. In each case the tip varies the rate of fresh water replacement from 0 to 100 % by an increment of 20%. Similar to the September 2016 TOTM [5] and based on the computer simulation results, the tip develops simple charts and correlations to estimate the methanol removal efficiency under various operating conditions. These charts and correlations are accurate enough for facilities calculations.

Case Study:

For the purpose of illustration, this tip considers sweetening of a sour gas stream saturated with water using the basic and modified MDEA processes as described in the July 2016 TOTM [2]. In addition to the two sour gas temperatures reported in the July TOTM, this tip also considers a sour gas temperature of 21.1 °C (70 °F). Table 2 presents its composition on the dry basis, gas standard volume rate, pressure, and temperatures. This tip uses ProMax [6] simulation software with the “Amine Sweetening – PR” property package to perform all of the simulations.

Results and Discussions:

Figures 1 through 3 present the calculated MRE as a function of the reflux rate replacement (RRR) with fresh water for the sour gas temperatures of 43.3, 32.2, and 21.1 °C (110, 90, and 70 °F), respectively. Each figure presents MRE vs replacement rate for the three sour gas methanol contents (50, 250, and 500 PPMV).

Table 2. Feed composition on the dry basis, volumetric flow rate and conditions [2]

Figure 1. Methanol removal efficiency vs reflux replacement for sour gas temperature of 43.3 °C (110 °F)

Figure 2. Methanol removal efficiency vs reflux replacement for sour gas temperature of 32.2 °C (90 °F)

Figure 3. Methanol removal efficiency vs reflux replacement for sour gas temperature of 21.1 °C (70 °F)

Since the three curves for different sour gas methanol contents on each figure are close, the effect of the sour gas methanol content on MRE can be neglected. For each sour gas temperature, the calculated arithmetic average of MRE of the three sour gas methanol content are provided in Figure 4. This figure indicates that as the sour gas temperatures decreases the impact of the reflux rate replacement with fresh water diminishes.

Figure 4. Average methanol removal efficiency vs reflux replacement

A non-linear regression program was used to determine the parameters of the following correlation for the methanol removal efficiency as a function of the reflux rate replacement % (RRR).

Where:

MRE = Methanol Removal Efficiency on the mole basis, %

RRR = Reflux Rate Replacement %

Table 3 presents the regressed parameters of A, B and C of Equation 1 for the three considered sour gas temperatures. The last two rows in Table 3 present the Average Absolute Percent Error (AAPE) and the Maximum Absolute Percent Error (MAPE), respectively.

A generalized form of this correlation to cover the temperature effect can be expressed as:

Where:

MRE   = Methanol removal efficiency on the weight basis

RRR    = Reflux Rate Replacement %

T          = Temperature, ºC (ºF)

Table 4 presents the regressed parameters of A₁, A₂, B₁, B₂, C₁ and C₂ of Equation 2 for temperatures in °C and °F. Similarly, the last two rows in Table 4 present the AAPE and the MAPE, respectively.

Table 3. Parameters of Equation 1 for methanol removal efficiency

Table 4. Parameters of Equation 1 for methanol removal efficiency

The MRE predictions by Equation 2 were added to Figure 4 and is presented as Figure 5. In this figure the solid lines present the MRE prediction by Equation 2 and dashed lines with the filled symbols represents simulation results. The analysis of Figures 5 and the calculated values of AAPE and MAPE in Table 4 indicate that accuracy of the proposed correlations, compared to the simulation results, is very good for estimation of methanol removal efficiency (MRE).

Figure 5. Comparison of model prediction of average methanol removal efficiency vs reflux replacement

Conclusions:

Based on the results obtained for the considered case study, this TOTM presents the following conclusions:

1. The impact of the sour gas methanol content on the methanol removal efficiency is small (Figures 1-3), overall only a minor impact, less than 0.5 % point.
2. As the sour gas temperature decreases, the methanol removal efficiency increases (Figures 1-5), overall only minor impact, less than 3 % points.
3. Methanol removal efficiency with MDEA sweetening can remove only 89-97% of the methanol in the sour gas feed.  This may still leave more methanol than the gas spec allows.  A separate water wash step may be required.  The fresh water used for the water wash could be recycled as MDEA reflux purge make-up.
4. The tip presents three simple charts (Figures 1-3) and two correlations (Equations 1 and 2) along with their parameters (Tables 3 and 4) for estimating the average methanol removal efficiencies for the sour gas temperatures of 43.3, 32.2, and 21.1 °C (110, 90, and 70 °F), respectively.
5. Compared to the rigorous computer simulation, the accuracy of the proposed correlations (Equations 1 and 2) to estimate the average methanol removal efficiency is very good (Tables 3 and 4 and Figure 5) and can be used for facilities calculations.
6. The proposed correlations (Equations 1 and 2) and charts (Figures 4-5) are easy to use.

To learn more about similar cases and how to minimize operational troubles, we suggest attending our G6 (Gas Treating and Sulfur Recovery), G4 (Gas Conditioning and Processing), G5 (Advanced Applications in Gas Processing), and PF4 (Oil Production and Processing Facilities) courses.

PetroSkills | Campbell offers consulting expertise on this subject and many others. For more information about these services, visit our website at http://petroskills.com/consulting, or email us at consulting@PetroSkills.com.

By: Dr. Mahmood Moshfeghian

References:

1. O’Brien, D., Mejorada, J., Addington, L., “Adjusting Gas Treatment Strategies to Resolve Methanol Issues,” Proceedings of Lawrence Reid Gas Conditioning Conference, Norman, Oklahoma, 2016.
2. Moshfeghian, M., July 2016 tip of the month, PetroSkills | John M. Campbell, 2016.
3. Maddox, R.N., and Morgan, D.J., Gas Conditioning and Processing, Volume 4: Gas treating and sulfur Recovery, Campbell Petroleum Series, Norman, Oklahoma, 1998.
4. Campbell, J.M., Gas Conditioning and Processing, Volume 2: The Equipment Modules, 9^th Edition, 1^st Printing, Editors Hubbard, R. and Snow –McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.
5. Moshfeghian, M., September 2016 tip of the month, PetroSkills | John M. Campbell, 2016.
6. ProMax 4.0, Bryan Research and Engineering, Inc., Bryan, Texas, 2016.

Similar to the gas-sweetening process, the methyldiethanolamine (MDEA) liquid-sweetening process removes a considerable amount of methanol from a sour NGL (Natural Gas Liquid) stream. Moreover, if the methanol content of the sour NGL is high, the sweetened NGL may still retain high methanol content and can cause operational troubles in the downstream processes. Provisions of purging reflux (Water Draw) of the regenerator column and its replacement with “Fresh Water” can improve methanol recovery [1, 2].

The August 2016 tip of the month (TOTM) considered the presence of methanol in the sour NGL stream and determined the quantitative traces of methanol ending up in the sweet NGL, flash gas and acid gas streams [2]. It simulated a simplified MDEA liquid-sweetening unit by computer and studied the effect of sour NGL methanol content, and the rate of replacing condensed reflux with fresh water on the sweet NGL methanol content. For the sour NGL temperature of 26.7 °C (80 °F) the tip studied five inlet NGL methanol contents of 50, 250, 500, 1000, and 1500 PPM on mole basis (30, 149, 298, 596, 894 PPMw, weight basis). In each case the tip varied the rate of fresh water replacement from 0 to 100 % by an increment of 20%. Table 1 presents the summary of calculated methanol removal efficiency (MRE).

Table 1. The effect of purging and circulation rate on the methanol removal efficiency [2]

In continuation of the August 2016 TOTM, this tip will consider the presence of methanol in the sour NGL stream and determine the quantitative traces of methanol ending up in the sweet NGL, flash gas and acid gas streams. This tip simulates a simplified MDEA liquid-sweetening unit by computer simulation [3, 4]. This tip also studies the effect of sour NGL methanol content, temperature and the rate of replacing condensed reflux with fresh water on the sweet NGL methanol content.

For the sour NGL temperatures of 21.1, 26.7, 37.8 °C (70, 80, 100 °F) the tip studies five inlet NGL methanol contents of 50, 250, 500, 1000, and 1500 PPM on mole basis (30, 149, 298, 596, 894 PPMw, weight basis). In each case the tip varies the rate of fresh water replacement from 0 to 100 % by an increment of 20%. Based on the computer simulation results, the tip develops simple charts and correlations to estimate the methanol removal efficiency under various operating conditions. These charts and correlations are accurate enough for facilities calculations.

Case Study:

For the purpose of illustration, this tip considers sweetening of a sour NGL stream using the basic and modified MDEA processes as described in the August 2016 TOTM [2]. Table 2 presents its composition, standard liquid volume rates, pressure, and temperatures. This tip uses ProMax [5] simulation software with the “Amine Sweetening – PR” property package to perform all of the simulations. Specifications/assumptions are also the same as in the August 2016 TOTM [2].

Table 2. Feed composition, volumetric flow rate and conditions [2]

Results and Discussions:

Figure 1 presents the calculated methanol removal efficiency as a function of the ratio of the lean MDEA rate to the sour NGL rate for the five sour NGL methanol contents (30, 149, 298, 596, 894 PPMw, weight basis). The sour NGL temperature is 26.7 °C (80 °F).

The methanol removal efficiency (MRE) on the weight basis is defined by:

Figure 1. Methanol removal efficiency vs circulation ratio of lean MDEA Sm3/h (sgpm) to sour NGL Sm3/h (sgpm) for sour NGL temperature of 26.7 °C (80 °F)

This figure indicates that as the percentage of purge increases the impact of the sour NGL methanol content diminishes. Similar diagrams were generated for sour NGL temperatures of 21.1 and 37.8 °C (70 and 100 °F). For simplicity, for each percent of purge the arithmetic average of each family of the curves was calculated and plotted in the subsequent figures.

For each sour NGL temperature, each percentage of reflux purge, and each lean MDEA rate, the arithmetic average of methanol removal efficiencies for the five sour NGL methanol content was calculated. Figures 2 through 4 present these calculated average methanol removal efficiencies as a function of the circulation ratio of the lean MDEA rate to the sour NGL rate for the sour NGL temperatures of 21.1, 26.7, and 37.8 °C (70, 80, and 100 °F), respectively. Each figure presents four curves for 0, 20, 50, and 100% reflux purge. The symbols in these figures present the arithmetic average of calculated methanol removal efficiency (MRE) by ProMax and all of the lines were generated by regression of the ProMax calculated MRE.

Figure 2. Average methanol removal efficiency vs circulation ratio of lean MDEA Sm3/h (sgpm) to sour NGL Sm3/h (sgpm) for sour NGL temperature of 21.1 °C (70 °F)

A non-linear regression program was used to determine the parameters of the following correlation for the methanol removal efficiency as a function of the circulation ratio (CR) and the reflux purge % (RP).

Where:

MRE         = Methanol removal efficiency on the weight basis

CR             = Circulation ratio, Sm³/h of MDEA / Sm³/h of sour NGL (sgpm/sgpm)

RP             = Reflux purge %

Table 3 presents the regressed parameters of A through F of Equation 1 for the three considered sour NGL temperatures. The last two rows in Table 3 present the Average Absolute Percent Error (AAPE) and the Maximum Absolute Percent Error (MAPE), respectively. The analysis of Figures 2 through 4 and the calculated values of AAPE and MAPE indicate that accuracy of the proposed correlations is very good for estimation of methanol removal efficiency (MRE).

Table 3. Parameters of Equation 1 for methanol removal efficiency

AAPE = Average Absolute Percent Error

MAPE = Maximum Absolute Percent Error

Figure 3. Average methanol removal efficiency vs circulation ratio of lean MDEA Sm3/h (sgpm) to sour NGL Sm3/h (sgpm) for sour NGL temperature of 26.7 °C (80 °F)

Figure 4. Average methanol removal efficiency vs ratio circulation of lean MDEA Sm3/h (sgpm) to sour NGL Sm3/h (sgpm) for sour NGL temperature of 37.8 °C (100 °F)

Conclusions:

Based on the results obtained for the considered case study, this TOTM presents the following conclusions:

1. As the circulation ratio increases, the impact on the methanol removal efficiency diminishes.  A ratio of about 0.5 appears to provide a reasonable breakpoint.
2. As the percentage of reflux purge increases, the impact of the sour NGL methanol content on the methanol removal efficiency diminishes (Figure 1), overall only a minor impact, 2 to 3% points.
3. As the sour NGL temperature increases, the methanol removal efficiency decreases (Figures 2-4), overall only minor impact, 2 to 3% points.
4. Methanol removal efficiency with MDEA sweetening can remove only 95-97% of the methanol in the sour NGL feed.  This may still leave more methanol than the NGL spec allows.  A separate water wash step may be required.  The fresh water used for the water wash could be recycled as MDEA reflux purge make-up.
5. The tip presents three simple charts (Figures 2-4) and a correlation (Equation 1) along with its parameters (Table 3) for estimating the average methanol removal efficiencies of the sour NGL temperatures of 21.1, 26.7, and 37.8 °C (70, 80, and 100 °F), respectively.
6. Compared to the rigorous computer simulation, the accuracy of the proposed correlation (Equation 1) to estimate the average methanol removal efficiency is very good (Table 3) and can be used for facilities calculations.
7. The proposed correlation (Equation 1) and charts (Figures 2-4) are easy to use.

To learn more about similar cases and how to minimize operational troubles, we suggest attending our G6 (Gas Treating and Sulfur Recovery), G4 (Gas Conditioning and Processing), G5 (Advanced Applications in Gas Processing), and PF4 (Oil Production and Processing Facilities) courses.

PetroSkills | Campbell offers consulting expertise on this subject and many others. For more information about these services, visit our website at http://petroskills.com/consulting, or email us at consulting@PetroSkills.com.

By: Dr. Mahmood Moshfeghian

References:

1. O’Brien, D., Mejorada, J., Addington, L., “Adjusting Gas Treatment Strategies to Resolve Methanol Issues,” Proceedings of Lawrence Reid Gas Conditioning Conference, Norman, Oklahoma, 2016.
2. Moshfeghian, M., August 2016 tip of the month, PetroSkills | John M. Campbell, 2016.
3. Maddox, R.N., and Morgan, D.J., Gas Conditioning and Processing, Volume 4: Gas treating and sulfur Recovery, Campbell Petroleum Series, Norman, Oklahoma, 1998.
4. Campbell, J.M., Gas Conditioning and Processing, Volume 2: The Equipment Modules, 9^th Edition, 1^st Printing, Editors Hubbard, R. and Snow –McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.

ProMax 4.0, Bryan Research and Engineering, Inc., Bryan, Texas, 2016.

Many materials may be added to water to depress both the hydrate and freezing temperatures. For many practical reasons, a thermodynamic hydrate inhibitor such as methanol or one of the glycols is injected, usually monoethylene glycol (MEG or EG). Solubility loss of MEG in the gas phase is negligible and loss to the liquid hydrocarbon phase is very low. However, methanol losses are more significant, particularly vapor phase losses. The methanol content of vapor and liquid hydrocarbon phases depend on temperature, pressure and composition.  Based on the GPA-Midstream RR 149 [1] the methanol content of the gas phase can be as high as 0.075 mole % (750 PPMV) and in the liquid hydrocarbon phase as high as 0.6 mole %. Depending on the solubility losses, chemical makeup requirements for methanol can be very large and expensive for both once-through systems and methanol recovery units.

The significant amount of methanol lost to the hydrocarbon phases may cause problems for refineries, petrochemical, LNG and gas plants downstream. In gas plants where there is propane recovery the methanol will follow the propane product and can be a potential cause for propane to go off specification. Methanol has also been known to cause premature failure in molecular sieves. In refineries the methanol must be washed out of the crude/condensate, where it presents a problem in wastewater treatment. In petrochemical plants methanol is also considered poison for certain catalysts. The readers can find more detail in reference [2].

The October 2010 tip of the month (TOTM) considered the presence of methanol in the produced oil/water/gas stream and determined the quantitative traces of methanol ending up in the TEG dehydrated gas [3]. The July 2016 TOTM considered the presence of methanol in the sour gas of a sweetening unit and determined the quantitative traces of methanol ending up in the sweet gas, flash gas and acid gas streams. That tip concluded that the methydeithanolamine (MDEA) sweetening process removes a considerable amount of methanol from feed sour gas. Moreover, if the methanol content of the sour gas is high, the sweetened gas may still retain high methanol content and can cause operational troubles in the downstream processes. A modified MDEA sweetening process with 100% purging of the reflux stream can reduce the sweet gas methanol content in the range of 92% to 95% [4].

Similar to the July 2016 TOTM, this tip will consider the presence of methanol in the sour NGL stream and determine the quantitative traces of methanol ending up in the sweet NGL, flash gas and acid gas streams. To achieve this, the tip simulates a simplified MDEA gas sweetening unit by computer [5, 6]. This tip also studies the effect of feed sour NGL methanol content, and the rate of replacing condensed reflux with fresh water on the sweet NGL methanol content. For the feed sour NGL temperature of 26.7 °C (80 °F) the tip studies five inlet NGL methanol contents of 50, 250, 500, 1000, and 1500 PPM on mole basis (30, 149, 298, 596, 894 PPMw, weight basis). In each case the tip varies the rate of fresh water replacement from 0 to 100 % by an increment of 20%. The simulated results are presented graphically.

Case Study:

For the purpose of illustration, this tip considers sweetening of a sour NGL stream using MDEA. Table 1 presents its composition, standard liquid volume rate, pressure, and temperature. This tip uses ProMax [7] simulation software with “Amine Sweetening – PR” property package to perform all of the simulations.

Table 1. Feed composition, volumetric flow rate and conditions

This tip used the same modified process flow diagram of Figure 1 in the July 2016 TOTM [4]. Note that the contactor is a liquid/liquid contactor rather than gas/liquid as in the July TOTM. A large fraction of methanol entering with the sour NGL leaves the sweetening unit via the treated NGL, flash gas and acid gas streams. However, some of the methanol is trapped and accumulates in the system and reaches its highest concentration in the regenerator reflux stream. In order to further lower the methanol concentration in the treated NGL, a fraction of reflux stream is purged via “Water Draw” stream and replaced with “Fresh Water.”

In Figure 1, the “Water Draw” stream removes a specified fraction of the condensed reflux (stream 10A) and the “Fresh Water” stream adds the same amount of fresh water to the process (stream 10B). To illustrate the effect of this water replacement on lowering the methanol content of the sweet gas, the fraction of condensed water removed is varied from 0 to 100% with an increment of 20% on the mole basis.

Figure 1. Schematic for replacement of a portion of reflux stream with fresh water

The following specifications/assumptions for the case study are considered:

Liquid/Liquid Contactor Column

1. Feed sour NGL is saturated with water
2. Number of theoretical stages = 4
3. Pressure drop = 20 kPag (3 psi)
4. Lean amine solution temperature = Sour NGL feed temperature 26.7 (80 )

Regenerator Column

1. Number of theoretical stages = 10 (excluding condenser and reboiler)
2. Rich solution feed temperature = 98.9 (210 )
3. Rich solution feed pressure = 414 kPa (60 psig)
4. Condenser temperature = 48.9 (120 )
5. Pressure drop = 28 kPa (4 psi)
6. Bottom pressure = 110 kPag (16 psig)Heat Exchangers

Reboiler duty = 132 kg of steam/m³ of amine solution (1.1 lb_m/gallon) times amine circulation rate

1. Lean amine cooler pressure drop = 35 kPa (5 psi)
2. Rich side pressure = 35 kPa (5 psi)
3. Lean side pressure = 35 kPa (5 psi)

Pump

1. Discharge Pressure = Feed sour NGL pressure + 35 kPa (5 psi)
2. Efficiency = 65 %

Lean Amine Concentration and Circulation Rate

1. MDEA concentration in lean amine and water solution = 50 weight %
2. Standard lean amine circulation rate = 11.36 Sm³/h (50 sgpm)

This rate resulted in a total acid gas loading of ~0.003 and ~ 0.15 mole acid gases/mole of amine in the lean amine and rich amine solutions, respectively. The corresponding H₂S and CO₂ loadings in the lean amine solution were 0.0022 and 0.0008 mole acid gas per mole amine, respectively.

Rich Amine Solution Expansion Valve

1. Flash tank pressure = 448 kPag (65 psig)

Results and Discussions:

Based on the description and specifications presented in the previous section, ProMax [7] is used to simulate the NGL treating process. For each simulation run, the following properties are reported:

Methanol concentration in:

1. Sweet NGL (PPMw)
2. Flash gas from the amine flash tank (PPMV)
3. Acid gas from regenerator (PPMV)

Methanol concentration (wt %) in:

1. Lean amine
2. Condensed reflux (stream 10)
3. Returned reflux (stream 11)

H₂S and CO₂ concentration in the sweet NGL.

The calculated H₂S and CO₂ concentrations in the sweet NGL were little changed by reflux methanol concentration. They were less than 1.5 and 0.2 PPMV for H₂S and CO₂, respectively. The presence of methanol slightly increases the H₂S content of sweet NGL.

To observe the impact of circulation rate on the level of NGL sweetening, three lean MDEA circulation rates of 5.68, 11.36, and 22.71 Sm³/h (25, 50, and 100 sgpm) were considered. The variation of sweet NGL methanol content as a function of the molar % of the reflux stream purged with fresh water is presented in Figures 2 through 4 for the sweet NGL, flash gas, and acid gas streams, respectively. These figures are for 11.36 Sm³/h (50 sgpm) lean MDEA rate. Similar diagrams were generated for the other two lean MDEA circulation rates.

Figure 2 presents the variation of the methanol content in the sweet NGL stream as a function of the reflux rate replacement with fresh water for five methanol contents (PPMw, weight basis) in the feed sour NGL. Note the y-axis is logarithmic.

Figure 2. Methanol content in the sweet NGL stream vs reflux rate replacement for five sour NGL methanol concentrations

Figure 3. Methanol content in the flash gas stream vs reflux rate replacement for five sour NGL methanol concentrations

Figure 4. Methanol content in the acid gas stream vs reflux rate replacement for five sour NGL methanol concentrations

Figure 2 indicates that as the percentage of purging the reflux stream with fresh water increases, the methanol content of sweet NGL decreases. Figure 3 presents a similar trend for methanol content in the flash gas stream. Figure 4 presents the variation of the methanol content in the acid gas stream as a function of the reflux rate replacement with fresh water.

To show the impact of the lean MDEA circulation rate quantitatively, the percent of methanol content reduction for several streams was calculated by the following equations for five sour NGL methanol contents.

or

Figures 2 through 4 and the calculation results indicate that the effect of sour NGL methanol contents on the percent of methanol reduction in different streams is small. For example, the sweet NGL methanol content reduction varied within 1.5 % (i.e. 59.9% to 61.4% for sour NGL methanol contents of 30 and 894 PPMw, respectively); therefore, Table 2 presents only the average percent reduction of the five sour NGL methanol contents for each lean MDEA circulation rate. Table 2 indicates that as the lean MDEA circulation rate increases, more methanol concentration reduction takes place in the listed streams. Note that the sweet NGL methanol content reductions are the same as the reductions in the lean amine stream. This is expected because the lean amine and sweet NGL streams are almost in equilibrium with each other.

Table 2. Average percent methanol content reduction in different streams for three lean MDEA circulation rates (*Fresh water free of methanol)

The variation of methanol content as a function of the molar % of the reflux stream replaced with the fresh water is presented in Figures 5 through 7 for the lean amine, purged reflux, and replaced reflux streams, respectively. These figures are for 11.36 Sm3/h (50 sgpm) lean MDEA rate. Similar diagrams were generated for the other two lean MDEA circulation rates.

Figure 5 indicates that as the percent of purging the reflux stream with the fresh water increases, the methanol content of the lean amine decreases. Figure 6 presents a similar trend for methanol content in the purge reflux stream. Figure 7 presents a different trend for methanol content in the returned reflux stream. For 100% purging, the reduction of methanol content is 100% for the five sour NGL methanol contents.

Figure 5. Methanol content in the lean amine stream vs reflux rate replacement for five sour NGL methanol concentrations

Figure 6. Methanol content in the purge reflux stream vs reflux rate replacement for five sour NGL methanol concentrations

Figure 7. Methanol content in the replaced reflux stream vs reflux rate replacement for five sour NGL methanol concentrations

Figures 8A and 8B present the methanol concentration profiles in the liquid streams leaving the stages in the regenerator column. These profiles are for lean MDEA circulation rate of 11.36 Sm³/h (50 sgpm), 0 and 100 % purge of reflux, and sour NGL methanol content of 30 and 894 PPMw. These figures indicate that the maximum methanol concentration occurs in the reflux stream with 0 % purging. With 100 % purging, the reflux stream contains no methanol. Similar profiles were observed for the two lower and higher lean MDEA circulation rates.

Figure 8A. Methanol content profile for liquid stream leaving the stages in the regenerator

Figure 8B. Methanol content profile for liquid stream leaving the stages in the regenerator

Conclusions:

Based on the results obtained for the considered case study, this TOTM presents the following conclusions:

1. Similar to the gas sweetening process, the MDEA liquid sweetening process removes a considerable amount of methanol from feed sour NGL. Moreover, if the methanol content of the sour NGL is high, the sweetened NGL may still retain high methanol content and can cause operational troubles in the downstream processes.
2. The highest concentration of methanol content due to entrapment of methanol in the system is in the condensed reflux stream 10 of Figure 1 (see also Figure 8).
3. Provisions of purging reflux (Water Draw) and its replacement with “Fresh Water” (Figure 1) can improve methanol recovery.
4. The effect of sour NGL methanol content on the percent of methanol reduction in different streams is small.
5. The basic MDEA sweetening process reduced the sweet NGL methanol content (PPMV) by ~60%, ~75% and ~80% for the lean MDEA circulation rate of 5.68, 11.36, and 22.71 Sm³/h (25, 50, and 100 sgpm), respectively.
6. The modified MDEA sweetening process with 100% purging of the reflux stream reduced the sweet NGL methanol content (PPMV) by ~75%, ~90% and ~95% for the lean MDEA circulation rates of 5.68, 11.36, 22.71 Sm³/h (25, 50, and 100 sgpm), respectively.
7. The purged reflux stream, which contains methanol should be disposed of properly or treated within the plant. The treated recovered water may be reused as fresh water in the sweetening process.
8. In NGL sweetening, the residual amine in the NGL can also be a problem.  The treated NGL usually goes through a water wash step.  This step would also remove MeOH in the treated NGL stream.  The wash water could be used as make-up in the regenerator purge loop.  Water wash of the NGL would have a major impact on NGL quality, but only minor impact of flash gas and acid gas.

Methanol is both a Hazardous Air Pollutant (HAP) and a Volatile Organic Compound (VOC).  It is regulated by the US EPA under the Clean Air Act.  Operators therefore need to make sure that it is disposed of properly when purged.  However, they must also consider its release into the atmosphere.  This means that if there is no sulfur present, the acid gas likely cannot be vented without exceeding HAP/VOC thresholds.  It must be sent to a control device, and even there, depending on the size of the plant, the operator may still bump into threshold limits.

To learn more about similar cases and how to minimize operational troubles, we suggest attending our G6 (Gas Treating and Sulfur Recovery), G4 (Gas Conditioning and Processing), G5 (Advanced Applications in Gas Processing), and PF4 (Oil Production and Processing Facilities) courses.

PetroSkills | Campbell offers consulting expertise on this subject and many others. For more information about these services, visit our website at http://petroskills.com/consulting, or email us at consulting@PetroSkills.com.

By: Dr. Mahmood Moshfeghian

References:

1. Gas Processors Association, “GPA RR-149: Vapor-Liquid and Vapor-Liquid-Liquid Methanol or Ethylene Glycol Solutions,” 1995. Equilibrium for H₂S, CO₂, Selected Light Hydrocarbons and a Gas Condensate in Aqueous
2. O’Brien, D., Mejorada, J., Addington, L., “Adjusting Gas Treatment Strategies to Resolve Methanol Issues,” Proceedings of Lawrence Reid Gas Conditioning Conference, Norman, Oklahoma, 2016.
3. Moshfeghian, M., October 2010 tip of the month, PetroSkills | John M. Campbell, 2010.
4. Moshfeghian, M., July 2016 tip of the month, PetroSkills | John M. Campbell, 2016.
5. Maddox, R.N., and Morgan, D.J., Gas Conditioning and Processing, Volume 4: Gas treating and sulfur Recovery, Campbell Petroleum Series, Norman, Oklahoma, 1998.
6. Campbell, J.M., Gas Conditioning and Processing, Volume 2: The Equipment Modules, 9^th Edition, 1^st Printing, Editors Hubbard, R. and Snow –McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.
7. ProMax 4.0, Bryan Research and Engineering, Inc., Bryan, Texas, 2016.

The best way to prevent hydrate formation (and corrosion) is to keep pipelines, tubing and equipment free of liquid water. There are occasions, right or wrong, when the decision is made to operate a line or process containing liquid water. If this decision is made, and the process temperature is below the hydrate point, inhibition of this water is necessary. This is of particular importance in gas gathering systems and subsea operations during normal production as well as during shutdown [1, 2].

Many materials may be added to water to depress both the hydrate and freezing temperatures. For many practical reasons, a thermodynamic hydrate inhibitor such as methanol or one of the glycols is injected, usually monoethylene glycol. All may be recovered and recirculated, but the economics of methanol recovery may not be favorable in many cases. Hydrate prevention with methanol and or glycols can be quite expensive because of the high effective dosage required (10 to 60 weight % of the water phase). Large concentrations of these solvents aggravate potential scale problems by lowering the solubility of scaling salts in water and precipitating most known scale inhibitors [2]. The total injection rate of inhibitor required is the amount/concentration of inhibitor in the liquid water phase for the desired hydrate temperature depression, plus the amount of inhibitor that will also distribute in the vapor and liquid hydrocarbon phases. Any inhibitor in the vapor phase or liquid hydrocarbon phase has little effect on hydrate formation conditions.

Solubility loss of MEG in the gas phase is negligible and loss to the liquid hydrocarbon phase is very low. However, methanol losses are more significant, particularly vapor phase losses.  The methanol content of vapor and liquid hydrocarbon phases depend on temperature, pressure and composition.  Based on the GPA-Midstream RR 149 [3] the methanol content of the gas phase can be as high as 0.075 mole % (750 PPMV) and in the liquid hydrocarbon phase as high as 0.6 mole %. Depending on the solubility losses, chemical makeup requirements for methanol can be very large and expensive for both once-through systems and methanol recovery units.

The significant amount of methanol lost to the hydrocarbon phases may cause problems for refineries, petrochemical, LNG and gas plants downstream. In gas plants where there is propane recovery the methanol will follow the propane product and be a potential cause for propane to go off specification. Methanol has also been known to cause premature failure in molecular sieves. In refineries the methanol must be washed out of the crude/condensate, where it presents a problem in wastewater treatment. In petrochemical plants methanol is also considered poison for certain catalysts. The readers can find more detail in reference [4].

The October 2010 tip of the month (TOTM) considered the presence of methanol in the produced oil/water/gas stream and determined the quantitative traces of methanol ending up in the TEG dehydrated gas [5]. That tip studied the effect of wet gas temperature, the number of theoretical trays in the TEG contactor, the water content specification of dry gas, and lean TEG circulation rate on the dried gas methanol content.

The July 2014 TOTM compared the performance of monoethanolamine (MEA), diethanolamine (DEA) and methydeithanolamine (MDEA) by simulation of a sweetening unit [6]. The H2S and CO2 concentration in the sweet gas, amine solution circulation rate, reboiler duty, amine losses, pump power, and lean-rich heat exchanger duty were calculated and plotted for a wide range of steam rates needed to regenerate the rich solution.

This tip will consider the presence of methanol in the sour gas stream and determine the quantitative traces of methanol ending up in the sweet gas, flash gas and acid gas streams. To achieve this, the tip simulates a simplified MDEA gas sweetening unit by computer [7, 8]. This tip also studies the effect of feed sour gas temperature, methanol content, and the rate of replacing condensed reflux with fresh water on the sweet gas methanol content. For the two feed sour gas temperatures of 32.2 and 43.3 °C (90 and 110 °F) the tip studies three inlet gas methanol contents of 50, 250, and 500 PPMV.  In each case the tip varies rate of fresh water replacement from 0 to 100 % by an increment of 20%. The simulated results are presented   graphically.

Case Study:

For the purpose of illustration, this tip considers sweetening of 2.832 x 10⁶ Sm³/d (100 MMscfd) of a sour natural gas using MDEA. Table 1 presents its composition, pressure, and temperature. This tip uses ProMax [9] simulation software with “Amine Sweetening – PR” property package to perform all of the simulations.

Table 1. Feed composition, volumetric flow rate and conditions

Figure 1 [9] presents a modified sweeting process flow diagram for the case study. A large fraction of methanol entering with the sour gas leaves the sweetening unit via streams 4 (Sweet Gas), 6 (Flash Gas) and 12 (Acid Gas). However, some of the methanol is trapped and accumulates in the system and reaches its highest concentration in stream 10 (reflux). In order to further lower the methanol concentration in the sweet gas, a fraction of reflux stream is purged via “Water Draw” stream and replaced with “Fresh Water”. Figure 2 presents the magnification of the upper right hand corner of Figure 1 showing the water draw and fresh water streams.

In Figure 2, the “Water Draw” stream removes a specified fraction of stream 10A (the condensed reflux) and the “Fresh Water” stream adds the same amount of fresh water to the process. To illustrate the effect of this water replacement on lowering the methanol content of the sweet gas, the fraction of condensed water removed is varied from 0 to 100% with an increment of 20% on the mole basis.

Figure 1. Simplified process flow diagram for an amine sweetening unit [9]

Figure 2. Schematic for replacement of a portion of reflux stream with fresh water

The following specifications/assumptions for the case study are considered:

Contactor Column

1. Feed sour gas is saturated with water
2. Number of theoretical stages = 7
3. Pressure drop = 20 kPa (3 psi)
4. Lean amine solution temperature  = Sour gas feed temperature + 5.5  (10 )

Regenerator Column

1. Number of theoretical stages = 10 (excluding condenser and reboiler)
2. Feed rich solution temperature = 98.9  (210 )
3. Feed rich solution pressure = 414 kPa (60 psig)
4. Condenser temperature = 48.9  (120 )
5. Pressure drop = 28 kPa (4 psi)
6. Bottom pressure = 110 kPag (16 psig)

Reboiler duty = 132 kg of steam/m³ of amine solution (1.1 lb_m/gallon) times amine circulation rate

Heat Exchangers

1. Lean amine cooler pressure drop  = 35 kPa  (5 psi)
2. Rich side pressure  = 35 kPa (5 psi)
3. Lean side pressure  = 35 kPa (5 psi)

Pump

1. Discharge Pressure = Feed sour gas pressure + 35 kPa (5 psi)
2. Efficiency = 65 %

Lean Amine Concentration and Circulation Rate

1. MDEA concentration in lean amine = 50 weight %
2. Standard lean amine circulation rate = 65.87 Sm³/h (290 sgpm)

(This rate resulted in a total gas loading in rich solution of ~0.40 mole acid gases/mole of amine)

Rich Solution Expansion Valve

1. Flash tank pressure = 448 kPag (65 psig)

Results and Discussions:

Based on the description and specifications presented in the previous section, ProMax [9] is used to simulate the process flow diagram in Figure 1. For each simulation run, the following properties are reported:

Methanol molar concentration (PPM) in

1. Sweet gas
2. Flash gas from the amine flash tank
3. Acid gas from regenerator

Methanol concentration (wt %) in

1. Lean amine
2. Condensed reflux (stream 10)
3. Returned reflux (stream 11)

H₂S and CO₂ concentration in the sweet gas.

The calculated H₂S concentrations in the sweet gas were little changed by reflux methanol concentration. The ranges were 3.92 to 3.61 PPMV and 1.64 to 1.81 PPMV for the sour gas temperatures of 43.3 and 32.2°C (110 and 90°F), respectively. The presence of methanol slightly increases the H₂S content of sweet gas. The calculated CO₂ concentrations in the sweet gas were 2.87 and 2.61 mole % for feed sour gas temperatures of 43.3 and 32.2°C (110 and 90°F), respectively. Therefore, the presence of methanol practically has no effect on the H₂S and CO₂ content in the sweet gas.

The variation of sweet gas methanol content as a function of the molar % of the reflux stream purged with fresh water is presented in Figures 3 through 5 for the sweet gas, flash gas, and acid gas streams, respectively. In all figures, the solid line and filed symbols present 43.3°C (110°F) and dashed lines and empty symbols present 32.2°C (90°F). The square, circle, and triangle symbols present the sour gas methanol content of 50, 250, and 500 PPMV, respectively.

Figure 3 presents the variation of the methanol content in the sweet gas stream as a function of the reflux rate replacement with fresh water for the two feed sour gas temperatures and three methanol contents (PPM) in the feed sour gas stream. The two temperatures are 43.3 and 32.2 °C (110 and 90 °F) and the three methanol contents of feed sour gas are 50, 250, and 500 PPMV. In Figures 3 through 8, PPM A and PPM B represent 43.3 and 32.2 °C (110 and 90 °F), respectively.

Figure 3.  Methanol content in the sweet gas stream vs reflux rate replacement

Figure 4. Methanol content in the flash gas stream vs reflux rate replacement

Figure 5. Methanol content in the acid gas stream vs reflux rate replacement

Figure 3 indicates that as the percent of purging the reflux stream with fresh water increases, the methanol content of sweet gas decreases. For 100% purging, the maximum methanol reduction is ~33% for the case of 43.3°C (110°F) and 500 PPMV and the minimum is ~30% for the case of 32.2°C (90°F) and 50 PPMV and.

Figure 4 presents a similar trend for methanol content in the flash gas stream. For 100% purging, the maximum methanol reduction is ~19.5% for the case of 43.3°C (110°F) and 500 PPMV and the minimum is ~17.5% for the case of 32.2°C (90°F) and 50 PPMV.

Figure 5 presents a different trend for methanol content in the acid gas stream. This figure indicates that the sour gas feed temperature has practically no effect on the acid gas stream methanol content. For 100% purging, the methanol content reductions were in the range of ~72% to ~73% for all cases of feed sour gas temperatures and methanol contents.

The variation of the methanol content as a function of the molar % of the reflux stream replaced with fresh water is presented in Figures 6 through 8 for the lean amine, purged reflux, and replaced reflux streams, respectively. In these three figures the effect of the feed sour gas temperature is practically negligible.

Figure 6. Methanol content in the lean amine stream vs reflux rate replacement

Figure 7. Methanol content in the purged reflux stream vs reflux rate replacement

Figure 6 indicates that as the reflux stream purging with fresh water increases, the methanol content of the lean amine decreases. For 100% purging, the maximum methanol reduction is ~33% for the case of 43.3°C (110°F) and 500 PPMV and the minimum is ~30% for the case of 32.2°C (90°F) and 50 PPMV and. These values are the same as those reported for the methanol content in the sweet gas. This is expected because the lean amine stream and sweet gas stream streams are in equilibrium with each other.

Figure 7 presents a similar trend for methanol content in the purged reflux stream. For 100% purging, the minimum reduction of methanol is ~71.2% for the case of 32.2°C (90°F) and 500 PPMV and maximum is ~73.5% for the case of 43.3°C (110°F) and 50 PPMV.

Figure 8 presents a different trend for methanol content in the acid gas stream. For 100% purging, the reduction of methanol content is 100% for both temperatures and the three methanol contents in feed sour gas.

Figure 8. Methanol content in the replaced reflux stream vs reflux rate replacement

Conclusions:

Based on the results obtained for the considered case study, this TOTM presents the following conclusions:

1. The MDEA sweetening process removes a considerable amount of methanol from feed sour gas. Moreover, if the methanol content of the sour gas is high, the sweetened gas may still retain high methanol content and can cause operational troubles in the downstream processes.
2. The highest concentration of methanol content due to entrapment of methanol in the system is in the condensed reflux stream 10.
3. Provisions of purging reflux (Water Draw) and its replacement with “Fresh Water” (Figures 1 and 2) can improve methanol recovery.
4. The basic MDEA sweetening process reduced the sweet gas methanol content (PPMV) by ~89% and ~92% for the cases of 43.3°C (110°F) and 32.2°C (90°F), respectively (Stream 4 in Figure 1).
5. The modified MDEA sweetening process with 100% purging of the reflux stream  reduced the sweet gas methanol content (PPMV) by ~92% and ~95% for the cases of 43.3°C (110°F) and 32.2°C (90°F), respectively (Stream 4 in Figure 1).
6. The purged reflux stream, which contains methanol should be disposed of properly or it may be treated within the plant. The treated recovered water may be reused as fresh water in the sweetening process.

Methanol is both a Hazardous Air Pollutant (HAP) and a Volatile Organic Compound (VOC).  It is regulated by the US EPA under the Clean Air Act.  Operators therefore need to make sure that it is disposed of properly when purged.  However, they must also consider its release into the atmosphere.  This means that if there is no sulfur present, the acid gas likely cannot be vented without exceeding HAP/VOC thresholds.  It must be sent to a control device, and even there, depending on the size of the plant, the operator may still bump into threshold limits.

To learn more about similar cases and how to minimize operational troubles, we suggest attending our G6 (Gas Treating and Sulfur Recovery), G4 (Gas Conditioning and Processing), G5 (Advanced Applications in Gas Processing), and PF4 (Oil Production and Processing Facilities) courses.

PetroSkills | Campbell offers consulting expertise on this subject and many others. For more information about these services, visit our website at http://petroskills.com/consulting, or email us at consulting@PetroSkills.com.

By: Dr. Mahmood Moshfeghian

References:

1. Bullin, K.A., Bullin, J.A., “Optimizing methanol usage for hydrate inhibition in a gas gathering system,” Presented at the 83^rd Annual GPA Convention – March 15, 2004.
2. Szymczak, S., Sanders, K., Pakulski, M., Higgins, T.; “Chemical Compromise: A Thermodynamic and Low-Dose Hydrate-Inhibitor Solution for Hydrate Control in the Gulf of Mexico,” SPE Projects, Facilities & Construction, Dec, 2006.
3. Gas Processors Association, “GPA RR-149: Vapor-Liquid and Vapor-Liquid-Liquid
   1. Equilibrium for H₂S, CO₂, Selected Light Hydrocarbons and a Gas Condensate in Aqueou
   2. Methanol or Ethylene Glycol Solutions,” 1995.
4. O’Brien, D., Mejorada, J., Addington, L., “Adjusting Gas Treatment Strategies to Resolve Methanol Issues,” Proceedings of Lawrence Reid Gas Conditioning Conference, Norman, Oklahoma, 2016.
5. Moshfeghian, M., October 2010 tip of the month, PetroSkills – John M. Campbell, 2010.
6. Moshfeghian, M., July 2014 tip of the month,  PetroSkills – John M. Campbell, 2014
7. Maddox, R.N., and Morgan, D.J., Gas Conditioning and Processing, Volume 4: Gas treating and sulfur Recovery, Campbell Petroleum Series, Norman, Oklahoma, 1998.
8. Campbell, J.M., Gas Conditioning and Processing, Volume 2: The Equipment Modules, 9^th Edition, 1^st Printing, Editors Hubbard, R. and Snow –McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.
9. ProMax 4.0, Bryan Research and Engineering, Inc., Bryan, Texas, 2016.

The May 2015 tip of the month (TOTM) [1] presented a method which allows the users to estimate the decline of their adsorbent based on only one performance test run (PTR) for molecular sieve dehydrators using low pressure regeneration. This permits early formulation of a credible action plan. Site-specific factors will determines an adsorption unit’s decline curve. Consequently, conducting more than PTR is highly recommended. A poorly performing inlet separator, for example, could result in a unit exhibiting a more pronounced decline than indicated by the generic performance decline curves.

One can utilize the May 2015 TOTM methodology effectively by developing a spreadsheet or a computer program. Therefore, based on this methodology, we have developed a computer module to perform all of the calculations. This computer module has been coupled with the PetroSkills | John M Campbell GCAP (Gas Conditioning and Processing Software) [2]. This tip presents this computer model’s numerical and graphical results for the same case study of May 2015 TOTM.

The cyclical heating/cooling of the adsorbent results in a capacity (mass of water per 100 mass of adsorbent) decline due to a gradual loss of crystalline structure and/or pore closure.  A more troublesome cause of capacity decline is contamination of the molecular sieves due to liquid carryover from the upstream separation equipment.

The molecular sieve capacity decline curve is an essential element of this methodology. Figure 18.8 in Gas Conditioning and Processing, Volume 2: The Equipment Modules (9^th Edition) [3], presents a generic molecular sieve capacity decline curves. An expanded form of Figure 18.8 with five curves is shown in Figure 1. Shown in this figure are “Good”, “Good-Average (G_A)”, “Average”, “Average-Poor (A_P)”, and “Poor” curves that are a function of site specific factors. The life of the adsorbent is a function of the number of cycles, not the elapsed calendar time. Locating one data point on Figure 1 from a performance test run (PTR) allows us to generate the decline curve of the unit in question. For computer programming purpose, we have developed a simple mathematical model. For more detail regarding adsorption dehydration process see references [1 and 3].

Figure 1. A generic molecular sieve capacity decline curves

Case Study:

If your regeneration circuit has excess capacity over the “normal design conditions”, i.e., a design factor, you have standby time. This excess capacity allows you to reduce your online adsorption time and “turn the beds around” faster by regenerating the beds in a shorter cycle time.   When you are involved in the design of an adsorption unit, it is recommended to add 10 – 20% excess regeneration capacity.

Because of the capacity decline curves flatten out, available standby time may be able to extend the life of a molecular sieve unit when your unit is operating on fixed cycle times.  Other operating options include: running each cycle to water breakthrough; and, reducing the cycle times in discreet steps throughout the life of the adsorbent.

To demonstrate application of the developed program and illustrate the benefits of standby time we considered the same case study as in the May 2015 TOTM [1]. As shown in Figure 2, a natural gas processing plant has commissioned a new 3 tower molecular sieve dehydration unit to process 11.3 x 10⁶ std m³/d (400 MMscfd) prior to flowing to a deep ethane recovery unit.  The unit is expected to run for 3 years before needing a recharge and the plant turnaround is based on this expectation.  The following assumptions are made:

• A 3 tower system (2 towers on adsorption, 1 on regeneration)
• External Insulation
• Tower ID = 2.9 m (9.5ft)
• Each tower contains 24630 kg (54300 lb_m) of Type 4A 4×8 mesh beads
• Regeneration circuit capable of handling an extra 15% of flow
• Available standby time 0.5 hour
• Unit is operated on fixed time cycles
• No step-change events such as liquid carryover, poor flow distribution, etc.
• Figure 2. Typical process flow diagram for a 3-tower adsorption dehydration system [3]

Figure 2. Typical process flow diagram for a 3-tower adsorption dehydration system [3]

The design basis and molecular sieve design summary are shown in Tables 1 and 2.  The additional 15% of flow from the regeneration gas heater is well below the point at which bed lifting will occur.

Table 1. Design basis for the case study [1]

Table 2. Design summary for the case study [1]

Using the concepts outlined in chapter 18 of reference [3], the calculated design life factor, L_F, is 0.60 after 3 years (Number Of Cycles, NOC = 1095) of operation at design conditions. This point lies slightly above the “average” life curve as seen in Figure 3. These calculated values will be presented in the computer output table on the following pages.

After 12 months of operation, a Performance Test Run (PTR) is conducted.  The results are shown in Table 3. The feed flow rate and temperature are slightly lower compared to the design values.  A water breakthrough time of 20.9 hours is recorded.

Table 3. Results of Performance Test Run (PTR) after 12 months of operation [1]

Figure 3. Design condition life factor (LF = 61.0 %) at NOC = 1095

Tables 4A and 4B present the input data for the developed program (GCAP Option 18F) in SI (System International) and FPS (foot-Pound-Second) systems of units, respectively. The input values for the saturation water content at operation and design conditions by default were zero. Therefore, the program predicted the water content and populated the corresponding input fields. Similarly, the program estimated the gas compressibility factors based on the gas relative density at the operation and design conditions. The program is capable of performing compound bed calculations. In this case study, only one size molecular sieve (MS) was specified; therefore, the mass and density of the second layer of MS are 0. As shown in Table 1, the current adsorption time is 16 hours; therefore, the step (total regeneration) time for this 3-tower system will be 8 hours.

Table 4A. GCAP Option 18F input data for the case study (SI units)

Table 4B. GCAP Option 18F input data for the case study (FPS units)

Tables 5A and 5B present the GCAP Option 18F numerical results for this case study in SI and FPS systems of units, respectively.

Table 5A. GCAP Option 18F numerical results for the case study (SI units)

Table 5B. GCAP Option 18F numerical results for the case study (FPS units)

The PTR L_F is determined (using the concepts in Chapter 18 [3]) to be 0.675 after 365 cycles (one year of operation). It is important and useful to understand the equation sequence of the concepts in Chapter 18 [3], as shown by Equations 18.5 through 18.10 to arrive at the cited value for LF. This data point is labeled “OP1” (see the legend on top) and shown in Figure 4 and is seen to lie just between the generic “Average” and “A_G) curves. Based on this data point and the built-in mathematical model, GCAP Option 18F generates a performance curve labeled “Operation” and is shown in Figure 5. Note that the slope of the curves are starting to flatten out. Since the generated PTR curve is lower than the design L_F curve, the molecular sieves will experience water breakthrough if operated at design conditions in less than three years.

Figure 4. Performance test run (PTR) life factor (LF = 67.5%, NOC = 365)

Figure 5. Projected life factor curve passing through PTR data point

Figure 6 shows the projected life factor, L_F, after 3 years (NOC = 1095) of service at design conditions.  From the projected curve, F_L =0.556 for NOC = 1095. This data point is labeled “OP2”. If the capacity decline continues to follow the same trend as seen from the PTR curve, water breakthrough will occur after 802 cycles or just a little over 2 years from startup if operation continues at design conditions of L_F = 0.589. This prediction compares favorably to the results of the May 2015 Tip of the Month. This data point is labeled “OP3” and shown in Figure 7.

Figure 6. Projected life factor at 3 years (NOC = 1095) running at design conditions which gives LF = 55.6 %

Figure 7. Projected life factor (LF = 58.9%) running at design conditions which gives NOC = 802

Because the unit has a regeneration circuit that can handle an additional 15% of flow, the complete regeneration cycle (heating, cooling, de-and re-pressurization and standby) can be reduced from 8.0 hours to 7.0 hours or an adsorption time of 14 hours instead of 16 hours.  This allows the beds to turn around faster. Tables 6A and 6B are the same as Tables 4A and 4B with a revealed field to specify the revised adsorption time of 14 hours. Table 7 presents the additional program numerical results for the revised adsorption time of 14 hours.

Table 6A. GCAP Option 18F input data with the revised adsorption time for the case study (SI units)

Table 6B. GCAP Option 18F input data with the revised adsorption time for the case study (FPS units)

Table 7. GCAP Option 18F program additional numerical results for the revised adsorption time of 14 hours

Using the reduced cycle time (the complete cycle time is now 21 hours vs the original 24 hours), we find an L_F = 0.543.  This is because less water is being adsorbed per cycle.  This occurs at the 1250 (NOC = 365 + 886.4 = 1251.4) cycles labeled as “ROP” and shown in Figure 8 below.  The May 2015 TOTM was based on visually interpolating the capacity decline curves.  That method resulted in an L_F = 0.53 which occurred around the 1500 cycle mark.

Figure 8. Projected life factor (LF = 54.3% and NOC = 1251.4) if standby time is used

If the plant elects to take advantage of the standby time and operate at reduced cycle time immediately following the PTR, the molecular sieves should last an additional 25.5 months (2.13 years), resulting in a total life of 3.12 years (the May 2015 TOTM methodology predicted a total life of 3.7 years).   In this case, standby time will allow the unit to operate until the scheduled plant turnaround.

The different estimates of total life between the two methods is due to the flattening out of the decay curves.  Very small changes in L_F result in large differences in total number of cycles.  There is inherent uncertainty in taking a data point from a curve using visual interpolation. GCAP eliminates this uncertainty.

For units where the estimation of total life is critical, it is recommended to run another PTR. For the Case Study under evaluation, this should occur approximately one year after the first PTR. 

A free copy of the GCAP program can be obtained by attending PetroSkills – John M Campbell G4 (Gas Conditioning and Processing) course.

The approach discussed in this Tip of the Month should help a facility engineer plan for the inevitable replacement of molecular sieves in their natural gas dehydration facility.

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.

PetroSkills offers consulting expertise on this subject and many others. For more information about these services, visit our website at http://petroskills.com/consulting, or email us at consulting@PetroSkills.com.

By: Mahmood Moshfeghian and Harvey M. Malino

References:

1. Malino, H.M., May 2015 tip of the month, PetroSkills – John M. Campbell, 2015
2. GCAP 9.2.1 Software, PetroSkills – John M Campbell “Gas Conditioning and Processing Computer Program,” Editor Moshfeghian, M., PetroSkills, Katy, Texas, 2016.
3. Campbell, J.M., “Gas Conditioning and Processing, Volume 2: The Equipment Modules,” 9^th Edition, 2^nd Printing, Editors Hubbard, R. and Snow–McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.

This tip is the follow up to the April 2016 Tip of the Month (TOTM) which investigated the benefits of having a water-draw in a condensate stabilizer column. It will use a commercial simulation software to simulate the performance of an operating stabilizer. In order to take into account the non-ideality of water, the tip will perform three-phase (vapor, liquid hydrocarbon, and aqueous phases) calculations on the trays with excessive water rates. Specifically, it will study the influence of the column temperature profile and water partial pressure profile on the optimum location of water-draw tray in the column. It will also study the impact of the upstream 3-phase separator temperature on the reboiler, condenser, feed-stabilized condensate heat exchanger duties, and the reflux pump power. The tip will present a summary of the computer simulation results and the key diagrams for the same case study.

Case Study

Table 1 presents the compositions (mol %) of a raw condensate mixture studied. This table also presents the required heavy end properties (Molecular Weight, Specific Gravity, and Volume Average Boiling Point) and the conditions of the feed stream.

Figure 1 presents a simplified process flow diagram for the case study. The tip utilizes the front mixer to vary the feed water rate for the simulation purpose only. The use of the heat exchanger (HEX) will lower the reboiler and condenser duties and reflux pump power. The addition of a 3-phase separator upstream of the HEX removes essentially all excess water. It also allows investigating the impact of feed temperature on the performance of the column. Table 2 presents the stabilizer column specifications. Note the difference between water draw from within the column and water drain from the V-4 reflux drum. Reference [1] presents a good overview of a water-draw in a condensate stabilizer column.

Figure 1. A simplified stabilizer column with side water-draw

Based on the data in Tables 1 and 2, and the process flow diagram of Figure 1, the tip performed simulation using the Soave-Redlich-Kwong (SRK) equation of state [2] in ProMax [3] software.

Simulation Results – Water Partial Pressure and Temperature Profiles:

Figures 2a and 2b present the water partial pressure profile for two feed water flow rates of 1200 and 1500 lbmole/d (545 and 681 kmol/d), respectively. Both figures present water partial pressure for cases of no water-draw and water-draw at tray of 7 or 8. In these figures, a large spike of water partial pressure is observed for the cases of no water-draw tray.

For the lower water flow rate (Figure 2a), draw tray 8 still shows a smaller spike of water partial pressure indicating draw tray 8 in not the optimum choice. The water partial pressure profile is smooth for draw tray 7 indicating draw tray 7 is the optimum location for this flow rate.

For the higher water flow rate (Figure 2b), draw tray 7 still shows a smaller spike of water partial pressure indicating draw tray 7 in not the optimum choice. The water partial pressure profile is smooth for draw tray 8 indicating draw tray 8 is the optimum location for this flow rate. Analyzing these two figures indicates that water partial pressure profile is a handy tool in locating the optimum water-draw tray.

Figure 2a. Water partial pressure profile in the stabilizer column for three cases

Figure 2b. Water partial pressure profile in the stabilizer column for three cases

Similarly, Figures 3a and 3b present the column temperature profile for two feed water flow rates of 1200 and 1500 lbmole/d (545 and 681 kmol/d), respectively. Both figures show the column temperature profile for no water-draw and water-draw tray of 7 or 8. In these figures, a large spike of temperature profile is observed for the cases of no water-draw tray. These spikes are not as large as the ones observed for water partial pressure.

For the lower water flow rate (Figure 3a), draw tray 8 still shows a smaller spike of the column temperature indicating draw tray 8 is not the optimum choice. While the column temperature profile is smooth for draw tray 7 indicating this draw tray 7 is the optimum location for this flow rate.

For the higher water flow rate (Figure 3b), draw tray 7 still shows a much smaller spike of the column temperature indicating draw tray 7 is not the optimum choice. The column temperature profile is smoother for draw tray 8 indicating draw tray 8 is the optimum location for this flow rate. Analysis of these two figures indicates that the column temperature profile is also a handy tool in locating the optimum of the optimum water-draw tray. These four figures also confirm the optimum locations of draw trays reported in the previous tip.

Figure 3a. Temperature profile in the stabilizer column with and without side water-draw tray

Figure 3b. Temperature profile in the stabilizer column with and without side water-draw tray

Simulation Results – Impact of Raw Condensate Feed Temperature:

 Normally, an upstream three-phase separator as shown in Figure 1 is used to remove light gases and free water from the condensate to minimize the reboiler, condenser, the feed-stabilized condensate heat exchanger (HEX) duties, and the reflux pump power. A properly sized separator may also eliminate the need for a water-draw tray.

To investigate the impact of feed temperature on the performance of the column, the tip performed simulation for feed temperature from 70 to 120°F (21 to 49°C) with an increment of 10°F (5.5°C).  Tables 3a and 3b present the simulation results based on the input data of Tables 1 and 2.

Table 3a and Figure 4 indicate clearly that as the feed temperature increases, the dissolved water in the un-stabilized condensate increases. Most of the feed water leaves the column with light gases from top of the column and a small amount with the stabilized condensate from the bottom. No water leaves from water-draw tray. With the exception of high feed temperature (120°F=48.9°C), no water leaves the column by the water drain from the top of the column.

Figures 5 through 7 present the impact of feed temperature on the stabilized condensate Reid vapor pressure (RVP), heat the transfer equipment duties, and the reflux pump power requirement.

Figure 4. Feed water rate as a function of 3-phase separator temperature

Figure 5. Stabilized condensate RVP as a function of 3-phase separator temperature

Figure 6. Heat exchange duties as a function of 3-phase separator temperature

Figure 7. Reflux pump power as a function of 3-phase separator temperature

With exception of the HEX duty, in all cases the increase in feed temperature increases the stabilized condensate RVP, the reboiler and condenser duties and the reflux pump power requirement.

 Conclusions:

The simulation results for the case studies demonstrated the effectiveness of side water-draw and the importance of water draw location in the column. Based on the results obtained, this tip presents the following observations.

1. Water partial pressure profile in the column is an excellent tool for determining the optimum location of water-draw.
2. Column temperature profile can also provide guidance for the optimum location of water-draw tray.
3. The previous tip determined the optimum location of water-draw try by maximizing liquid water removal and minimizing the reboiler and condenser duties. This tip confirms the reported optimum location of water-draw tray of the previous tip by plotting the water partial pressure and column temperature profile.
4. Installing a properly sized free water knockout drum (three-phase separator) minimizes the feed water rate to the stabilizer column. This ensures easier/less troublesome operation with lower utility (reboiler and condenser duties and reflux pump power) cost.
5. Installing properly sized free water knockout (three phase separator) separator may also eliminate the need for water-draw. In this case most of water leaves with light gases from top of column. Only small amount of water leaves with the stabilized condensate from the bottom of column.
6. As the feed temperature increases the dissolved water in the raw condensate increases. The increase in feed water rate increases the reboiler and condenser duties, the reflux pump power, and the stabilized condensate RVP. This is important for sizing the equipment and flexibility of operation.
7. As the feed temperature increases the HEX duty decreases.

Part 3 (follow-up of this tip) will investigate the performance of a non-refluxed stabilizer column.

By: Dr. Mahmood Moshfeghian

Reference:

1. Campbell, J.M., Gas Conditioning and Processing, Volume 2: The Equipment Modules, 9^th Edition, 2^nd Printing, Editors Hubbard, R. and Snow–McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.
2. Soave, G., Chem. Eng. Sci. 27, 1197-1203, 1972.
3. ProMax 3.2, Bryan Research and Engineering, Inc., Bryan, Texas, 2016.

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), PF81 (CO₂ Surface Facilities), and PF4 (Oil Production and Processing Facilities), courses.

 PetroSkills offers consulting expertise on this subject and many others. For more information about these services, visit our website at http://petroskills.com/consulting, or email us at consulting@PetroSkills.com

This tip will investigate the benefits of having a water-draw in a condensate stabilizer. It will use a commercial simulation software to simulate the performance of an operating stabilizer. In order to take into account the non-ideality of water, the tip will perform three-phase (vapor, liquid hydrocarbon, and aqueous phases) calculations on the trays with excessive water rates. Specifically, it will study the impact of feed water rate in the raw condensate stream on the reboiler and condenser duties. It will also study water removal by water-draw pan, and the optimum location of water-draw tray in the column. For a case study the tip will determine the optimum location of water-Draw tray by maximizing water removal from water-draw tray and minimizing the reboiler and condenser duties.

If the vapor – liquid equilibrium conditions in the distillation tower allow the water entering the column with the feed to leave in either the bottom product or in the overhead distillate product, then no special provisions are needed to remove the water from the fractionator. A key exception here is the probability of free water accompanying the feed stream due a malfunctioning upstream three-phase feed separator. If the distillate product is a liquid and the water condenses along with the distillate and reflux streams then the overhead accumulator can be configured as a three-phase separator. A more difficult situation exists if the water condenses within the tower because the overhead temperature is too cool and the bottoms temperature is too hot to allow the water to leave in the product streams. The most common example of this condition is found in the condensate stabilizer.

Liquid water build-up can reduce capacity and, depending on the fluid composition, promote corrosion. Eventually the water build-up will cause the tower to flood and a major disruption in tower operation results as the water leaves the column. Once the water has left the column, operation will return to normal until the cycle repeats and the water build-up once again produces a flooding condition. The time between cycles can be anywhere from hours to weeks depending on the amount of water entering the stabilizer.

One solution to the water build-up condition is to provide a water draw pan on the trays where liquid water is expected to condense. Figure 1 [1] is an example of a water draw for a tray-distillation column.  The water draw pan is not sized to provide a good separation between water and hydrocarbon liquid so the fluid leaving the column is routed to an adequately sized liquid-liquid separator where the water is removed for further processing and the hydrocarbon liquid is routed back to the distillation column [2].

Figure 1. Water Draw Tray Arrangement [1]

Case Study

Table 1 presents the compositions (mol %) of a raw condensate mixture studied. This table also presents the required heavy end properties (Molecular Weight, Specific Gravity, and Volume Average Boiling Point) and the conditions of the feed stream.

Figure 2 presents a simplified process flow diagram for the case study. The tip utilized the front mixer to vary the feed water rate for the simulation purpose only. The use of the heat exchanger (HEX) will lower the reboiler and condenser duties. Table 2 presents the stabilizer column specifications. Note the difference between water draw from within the column and water drain from the V-4 reflux drum.

Figure 2. A simplified stabilizer column with side water-draw

Based on the information in Tables 1 and 2, and the process flow diagram of Figure 2, the tip performed simulation using the Soave-Redlich-Kwong (SRK) equation of state [3] in ProMax [4] software.

Simulation Results:

Figure 3 present the simulation results for the base case without side water-draw. The total water rate on the x-axis represents the sum of water rates in the vapor, light liquid (mostly hydrocarbons), and heavy liquid (mostly water) phases at any given tray in the column. The feed water range is from 940 to 1500 lbmole/d (427 to 1500 kmol/d). If the feed water is less than 940 lbmole (427 kmol/d) no heavy liquid (aqueous) phase is formed inside the column and water side draw rate will be zero.  Figure 3 indicates if the feed water rate increases above 1200 lbmole/d (545 kmol/d), the maximum total water rate location shifts from tray 11 down to 18. In an actual plant a free water knockout drum (three-phase separator) ahead of the stabilizer removes the excess water to minimize the heating requirement. The feed water rate above 1200 lbmole/d (545 kmol/d) to the stabilizer column is unrealistic and shown here only for demonstration purposes.

In addition to the base case, the tip simulated two cases with the side water-draw located at tray number 7 or 8. Table 3 presents the summary of simulation results for the base case and the two cases with side water-draw. For the base case without the water draw, at higher feed water rate some of the water leaves with stabilized condensate (C₅₊).

Figure 3. Total water molar rate profile in the stabilizer column without side water-draw as a function water rate in the feed

Figure 4a indicates that the presence of side water-draw at tray 7 shifts the maximum total water rate from tray 10 (Figure 3) to 6 for lower feed water rates and from tray 18 (Figure 3) to 10 for higher feed water rates, respectively. Figures 4a and 4b also indicate that the side water-draw at tray 7 removes water effectively for low feed water rates. As shown in Table 3, at higher feed water rate, the reboiler and condenser duties decrease considerably compared to the base case. Table 3 also indicates that the HEX (feed-bottoms exchanger) duty remains the same for all three cases because there was no material change in its flows and temperatures.

Figure 4a. Total water molar rate profile in the stabilizer column with side water-draw at tray 7 as a function water rate in the feed (full range)

Figure 4b. Total water molar rate profile in the stabilizer column with side water-draw at tray 7 as a function water rate in the feed (lower range)

In order to maximize water removal for higher feed water rate, the tip moved the side water-draw from tray 7 to 8. Table 3 clearly indicates that water-draw at tray 7 give higher water recovery percent for lower feed water rates up to 1200 lbmole/d (545 kmol/d) and water-draw at tray 8 give higher water recovery for higher feed water rate.  Figure 5 presents the total water flow rate profile within the column with side water-draw at tray 8 as a function of feed water rate. This figure demonstrates the effectiveness of the side water-draw.

Figure 5. Total water molar rate profile in the stabilizer column with side water-draw at tray 8 as a function water rate in the feed (higher range)

Figure 6 presents the water recovery percent of the feed water as a function of the feed water rate for the three cases considered.  For the base case without the side water-draw some of the excess water leaves the column with the C₅₊ stream. For this case, the excess feed water rate also increases the reboiler and condenser duties. These increases are indicative of the increased internal vapor traffic necessary to carry the water vapor out of the tower.

Like Figures 7 and 8, Figure 6 also shows the effectiveness of side water-draw and the impact of side water-draw location.

Figure 6. Water recovery (%) as a function of the feed water rate

Figure 7. Reboiler duty as a function of the feed water rate

Figure 8. Condenser duty as a function of the feed water rate

Conclusions:

The simulation results for the three case studies demonstrated the effectiveness of side water-draw and the importance of water draw location in the column. Based on the results obtained, this tip presents the following observations.

1. Commercial simulators using special convergence algorithms and thermodynamic packages are able to predict the presence of two liquid phases within distillation columns. The calculations are difficult to converge and it is difficult to predict the exact location of the liquid water phase. Therefore, it is advisable to install liquid water draw trays in two or three locations around the tray predicted by the simulator.
2. Install properly sized free water knockout (three phase separator) separator to minimize the feed water rate to the stabilizer column. This assures easier/less troublesome operation with lower utility (reboiler and condenser duties) cost.
3. Side water-draw removes water/aqueous phase effectively and reduces the reboiler duty and condenser duty.
4. The optimum location of the side-draw depends on the feed water rate.
5. This tip determined the optimum location of water-draw try by maximizing liquid water removal and minimizing the reboiler and condenser duties.
6. The side water-draw has no impact on the heat exchanger upstream of the stabilizer column.
7. As shown In Table 3, the topmost condenser duties for the three cases are 14.67, 9.00 and 8.49 MMBtu/hr (4.3, 2.64, and 2.49 MW), respectively.  Since fundamentally at a fixed overhead product rate, condenser pressure and temperature the water vapor content is fixed.  Thus a greater total overhead flow is needed to transport water as vapor out of the column to be condensed into the reflux drum and removed.  Greater total overhead means larger condenser duty.  It also requires a commensurately larger reboiler duty.  With a lot of water entering the tower the condenser and reboiler might not be big enough to do the job.

Part 2 (follow-up of this tip) will investigate the variation of water partial pressure along the column and the changes in operating variables.

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), P81 (CO₂ Surface Facilities), and PF4 (Oil Production and Processing Facilities), courses.

PetroSkills offers consulting expertise on this subject and many others. For more information about these services, visit our website at http://petroskills.com/consulting, or email us at consulting@PetroSkills.com.

By: Dr. Mahmood Moshfeghian

Reference:

1. Campbell, J.M., Gas Conditioning and Processing, Volume 2: The Equipment Modules, 9^th Edition, 2^nd Printing, Editors Hubbard, R. and Snow–McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.
2. Lieberman, N. P. ; “Troubleshooting Process Operation – 13,” Oil and Gas Journal, p. 100– 102, Feb 16, 1981.
3. Soave, G., Chem. Eng. Sci. 27, 1197-1203, 1972.
4. ProMax 3.2, Bryan Research and Engineering, Inc, Bryan, Texas, 2016.

The December 2012 [1] and January 2016 [2] Tips of the Month (TOTM) discussed the hydrate phase behavior of natural gas mixtures containing high content hydrogen sulfide, carbon dioxide, or nitrogen. Specifically, it showed nitrogen and carbon dioxide inhibit the hydrate formation slightly while hydrogen sulfide enhances hydrate formation considerably. This tip will extend the previous studies on the natural gas hydrate formation phase behavior. Specifically, it will study the impact of light hydrocarbons on the formation of hydrate in a natural gas mixture.

The hydrate formation temperature of a gas depends on the system pressure and composition. There are several methods of calculating the hydrate formation conditions of natural gases [3-6]. References [3-4] present rigorous methods while [5-6] present the shortcut methods suitable for hand calculations. This study uses a rigorous method using the Soave-Redlich-Kwong (SRK) equation of state [7] in ProMax [8] software.

Table 1 presents the compositions (mol %) of the gas mixtures studied. Notice that for non-hydrocarbons (gases B, C, and D) about 18 mol % of methane is replaced with about 20 mol % of either nitrogen, carbon dioxide or hydrogen sulfide. These compositions are for a gas stream leaving a separator at 100 °F and 1000 psia (37.8 °C and 6900 kPaa) saturated with water.

Table 1. Water-saturated compositions (mol %) of gas mixtures studied

Figure 1 presents the calculated hydrate formation and the dew point portion of the phase envelope (continuous curves) of a sweet natural gas (gas E of Table 1) containing 0 mol % C₂H₆. Figure 1 also presents the dew point and hydrate formation (broken curves) for gas F of Table 1 containing 17.8 mol % C₂H₆.

Figure 1. The impact of C₂H₆ on the hydrocarbon dew point and hydrate formation curves

Figure 1 indicates that the presence of 17.8 mol % C₂H₆ has a negligible effect on the hydrate formation curve. Note that the points to the left and above the hydrate curves represent the hydrate formation region. From an operational point of view, this region should be avoided. This figure also indicates that the presence of C₂H₆ decreases the cricondenbar pressure and the cricondentherm temperature; therefore, the two-phase (gas + liquid) region within the envelope shrinks.

Figure 2 presents the calculated hydrate formation and the dew point portion of the phase envelope (continuous curves) of a sweet natural gas (gas G of Table 1) containing 0 mol % C₃H₈. Figure 2 also presents the dew point and hydrate formation curves (broken curves) for gas H of Table 1 containing 12.7 mol % C₃H₈. Figure 2 indicates that the presence of 12.7 mol % C₃H₈ shifts the hydrate formation curve to the right promoting the hydrate formation condition. This figure also indicates that the presence of C₃H₈ decreases the cricondenbar pressure while having little effect on the cricondentherm temperature; the two-phase (gas + liquid) region within the envelope shrinks.

Similarly, Figure 3 presents the impact of 12.7 mol % iC₄H₁₀ on the dew point and hydrate formation curves for gases I and J of Table 1. This figure indicates that iC₄H₁₀ like C₃H₈ is a hydrate promotor and shifts the hydrate curve to the right.

Figure 2. The impact of C₃H₈ on the hydrocarbon dew point and hydrate formation curves

Figure 3. The impact of iC₄H₁₀ on the hydrocarbon dew point and hydrate formation curves

Similarly, Figure 4 presents the impact of 11.4 mol % nC₄H₁₀ on the dew point and hydrate formation curves for gases K and L of Table 1. This figure indicates that contrary to iC₄H₁₀, nC₄H₁₀ is a hydrate inhibitor and shifts the hydrate curve to the left. Both iC₄H₁₀ and nC₄H₁₀ lower the cricondentherm temperature and increase the cricondenbar pressure.

Figure 4. The impact of nC₄H₁₀ on the hydrocarbon dew point and hydrate formation curves.

Figure 5 presents a summary of the calculated hydrate formation curves for sweet gas A of Table 1 (Continuous curve), and gases B (20 mol % H₂S), gas C (20 mol % CO₂), gas D (20 mol % N₂), gas F (17.8 mol % C₂H₆), gas H (12.7 mol % C₃H₈), gas J (12.7 mol % iC₄H₁₀), gas L (11.4 mol % nC₄H₁₀) (broken curves). For the cases studied, this figure clearly indicates that the impact of N₂ is much less than of H₂S and slightly less than of CO₂. Nitrogen, carbon dioxide, and nC₄H₁₀, depress the hydrate formation condition (shift the hydrate curves to the left). Between these three components, nC₄H₁₀ has the larger depression effect even though its mol % is smaller. While C₂H₆ has the same effect as CH₄ on the hydrate formation condition (no shift on the hydrate formation curve), C₃H₈, iC₄H₁₀, and H₂S promotes hydrate formation condition. Among these hydrate promotors, H₂S has the largest contribution even for only 10 mol %. Note that “Sweet Gas” refers to gas A in Table 1.

Figure 5. The impact of nitrogen, acid gases and light hydrocarbon gases on the sweet gas hydrate formation curve.

Conclusions:

All of the molecules studied in this tip are hydrate formers. Some enhances hydrate formation of methane and some lowers hydrate formation of methane. Katz and co-workers [9] developed a set of vapor-solid equilibrium constants (K_v-s) values for hydrate prediction. In the Katz method as described on page 161 of Chapter 6 of reference [7] “nitrogen is a hydrate former, and it is likely that some nitrogen may end up in the hydrate lattice in typical natural gas production systems. However, it is not a factor in determining hydrate formation conditions unless you are working with mixtures of nitrogen and methane which are sometimes found in coalbed methane production. In these cases the N₂-CH₄ mixture will have a lower hydrate formation temperature than pure methane. As a practical matter using K_v-s = (infinity) for nitrogen gives satisfactory results for typical natural gas mixtures”.

This study has shown that while C₂H₆ has the same effect as CH₄; N₂, CO₂, nC₄H₁₀ have the opposite effect on hydrate formation of sweet gas compared to light hydrocarbon gases of C₃H₈, iC₄H₁₀, and H₂S. While the impact of N₂, CO₂, and nC₄H₁₀ is small in the same direction, C₃H₈, iC₄H₁₀, and H₂S have considerable impact on the hydrate formation condition. For the composition and condition (Table 1) studied, N₂, nC₄H₁₀, and CO₂ slightly depresses hydrate formation (shifts the hydrate curve to the left) while C₃H₈, iC₄H₁₀, and H₂S shift the hydrate curve to the right considerably, promoting hydrate formation conditions, and may cause severe operational problems. Table 1 also indicates that the predicted water content of sweet gases (Gases A, and D through L) is practically independent of gas composition. These results are not in complete agreement with the curves shown in the Trekell-Campbell method [5] which show the contribution of these components to the pure methane hydrate formation curve.

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), P81 (CO₂ Surface Facilities), and PF4 (Oil Production and Processing Facilities), courses.

PetroSkills offers consulting expertise on this subject and many others. For more information about these services, visit our website at http://petroskills.com/consulting, or email us at consulting@PetroSkills.com.

By: Dr. Mahmood Moshfeghian

Reference:

1. Moshfeghian, M., http://www.jmcampbell.com/tip-of-the-month/2012/12/sour-gas-hydrate-formation-phase-behavior/
2. Moshfeghian, M., http://www.jmcampbell.com/tip-of-the-month/2016/01/what-is-the-impact-of-nitrogen-on-the-natural-gas-hydrate-formation-conditions/
3. Parrish, W.R., and J.M. Prausnitz, “Dissociation pressures of gas hydrates formed by gas mixtures,” Ind. Eng. Chem. Proc. Dev. 11: 26, 1972.
4. Holder, G. D., Gorbin, G. and Papadopoulo, K.D, “Thermodynamic and molecular properties of gas hydrates from mixtures containing methane. argon, and krypton,” Ind. Eng. Chem. Fund. 19(3): 282, 1980.
5. Campbell, J.M., Gas Conditioning and Processing, Volume 1: The Basic Principles, 9^th Edition, 2^nd Printing, Editors Hubbard, R. and Snow–McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.
6. Gas Processors Suppliers Association; “ENGINEERING DATA BOOK” 13^th Edition – FPS; Tulsa, Oklahoma, USA, 2012.

1. G. Soave, Chem. Eng. Sci. 27, 1197-1203, 1972.

1. ProMax 3.2, Bryan Research and Engineering, Inc, Bryan, Texas, 2015.
2. Carson, D. B. and D. L. Katz, Trans. AIME, Vol. 146, p. 150, 1942.