Sloshing Impact on Gas Pretreatment for LNG ... - ACS Publications

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Cite This: Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

Sloshing Impact on Gas Pretreatment for LNG Plants Located in a Stranded Offshore Location Muhammad A. Mahmud,† Mozammel Mazumder,† Qiang Xu,*,† and Raifiqul I. Khan‡ †

Department of Chemical Engineering, Lamar University, Beaumont, Texas 77710, United States Process Systems Technology Center, Cameron Corporation, Houston, Texas 77041, United States

‡

ABSTRACT: Sloshing behaviors in liquid containers have been thoroughly studied for several decades by both experiments and numerical simulations. However, very few efforts are devoted to address the performance of gas pretreatment system of FLNG (floating liquefied natural gas) plants, particularly for the liquid entrainment estimation in the gas phase of multiphase separators. In this work, a multiscale simulation method was performed to study the sloshing impact on gas pretreatment for FLNG plants. First, computational fluid dynamics (CFD) simulations were performed to quantify liquid entrainment for oil−gas separator under sloshing. Next, CFD results were utilized by the gas pretreatment process modeling, where flow maldistribution in the oil−gas separator and absorption column due to sloshing was coupled with steady-state process simulations. Results show that the sloshing behavior increases the amount of liquid carryover into the gas phase substantially, while the performance of the gas pretreatment system decreases consequently.

1. INTRODUCTION The ever-increasing world population is driving industries to explore new energy sources as well as improving production from existing ones. The liquefied natural gas (LNG) from remote offshore locations offers an alternative way to satisfy this growing worldwide demand of energy. New ways to harness and monetize this resource on ship based floating structure has been subject of great interest lately. There are several floating liquefied natural gas (FLNG) facilities in operation as of today, e.g., Shell Prelude FLNG and Petronas FLNG 1 projects. Research works on the design and optimization of FLNG process systems have been studied by both academia and industry to a great extent.1−5 Particularly, there has been plethora of research works conducted in LNG for both onshore and offshore locations, which are available in open literature. For instance, Air Products Inc. has done extensive works on liquefaction cycle of FLNG.6 This work includes mechanical analysis, process, and computational fluid dynamics (CFD) simulation. CFD simulation was done to take the wave motion into account in this research. Unfortunately, it has also been noted that the gas pretreatment for FLNG has not been thoroughly studied like that of the liquefaction systems. Because the success of liquefaction operation depends on the feed gas quality to a great extent, the preparation of natural gas feed streams for refrigeration cycle is of the utmost importance. Meanwhile, extra constraints for FLNG systems should be addressed, e.g., the impact from wave motions. To properly design the gas pretreatment system for FLNG, different types of simulations could help. For example, microscopic CFD simulations could estimate liquid entrainment, wave effects, and flow maldistribution, etc. on component level, while large-scale process simulations will be best suitable for the process design, equipment sizing, and optimization of the overall © XXXX American Chemical Society

system. Plenty of research works regarding these two types of simulations have been performed as standalone fashions up until now. However, the research works coupling both CFD and process simulations for the study of gas pretreatment FLNG system is still lacking. In reality, feed gases to the liquefaction section of FLNG start with multiphase separators. These separators experience external disturbances in the form of liquid sloshing that is not present in onshore locations. Standalone large-scale process simulations cannot address the effect of wave motions on these separators, as well as the liquid carryover or gas carryunder to their downstream. Therefore, the need for microscopic simulation using CFD modeling is essential. There are many studies available in open literature for multiphase separators in this regard.7−12 Recently, Total, Prosernat, and IFPEN have performed experimental study of static and motion tests for gas purification systems for FLNG. It shows the impact of wave motions on tower efficiency and the corresponding tower oversizing.13 Several other researches pointed out the similar impact of wave on absorption column performance.14−16 The study of acid gas pretreatment for a FLNG facility by Petronus has shown that rocking motion generates liquid maldistribution inside a absorption column. The liquid moves toward one side of the column creating gas/liquid flow imbalance as a result.17 In addition, a slight increase in the maldistribution will create Special Issue: PSE Advances in Natural Gas Value Chain Received: Revised: Accepted: Published: A

August 31, 2017 January 31, 2018 February 2, 2018 February 2, 2018 DOI: 10.1021/acs.iecr.7b03631 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research

Figure 1. Comparison of cross sectional velocity among different mesh sizes.

holdup decreases by 10% for 3° static tilt and 4.5° rolling motion. Consequently, effective interfacial area and CO2 removal efficiency decreased. Bagul et al. conducted an excellent review of liquid carryover for multiphase separator.25 They found that the carryover estimation was largely based on empirical correlations developed from experimental data. Furthermore, these estimations covered mostly air−water systems. Their findings match with our conclusion that CFD is relatively new and had not yet been extensively applied to carryover phenomenon simulations especially for offshore location. Among the limited CFD studies available in published literature, numerical simulations using combination of volume of fluid (VOF), and discrete phase method (DPM) method were performed to measure liquid entrainment in gas phase.26 They have studied the drop size distribution and residence time for the oil−gas separator. In addition, the effects of coalescence and breakup of oil droplets on separation efficiency were also investigated. Similar type of simulation work was performed by Lu et al.27 The purpose of this study was to compare two vessels with different internals for the reduction of carryover. In summary, all the above works are carried out in standalone simulation mode. In other words, microscopic components level results from CFD simulation were not integrated with macroscopic system level (i.e., process simulation). For current commercial FLNG applications, the gas pretreatment facilities are generally overdesigned to minimize the sloshing impact, such that both capital and operating costs are expected to be significantly increased. Furthermore, few experimental works have been reported to quantitatively minimize liquid carryover due to sloshing impact. Therefore, the purpose of this study is to bridge this gap in knowledge. This goal was achieved by quantifying liquid entrainment for oil−gas separator in the presence of sloshing using CFD simulation and then integrating the findings with the process simulation for the gas pretreatment of FLNG, where the flow maldistribution in the oil−gas separator and absorption column due to sloshing was coupled with steadystate HYSYS simulations. This new approach was adopted to ascertain the performance of the gas pretreatment system for FLNG. It should be clearly mentioned that some detailed oil−gas multiphase separator internals were neglected in our CFD modeling studies, such as the demister or coalesce, due to the extreme modeling complexity and the lack of industrial data support. Thus, the study results could be referenced as rough estimations under severe/abnormal operating conditions.

significant increase in CO2 slip. Process simulations using HYSYS for the mixed amine solvent of methyl diethanol-amine (MDEA) and diethyl amine (DEA) for acid gas removal have been carried out recently.18 The effects of acid gas load, amine solvent ratio, absorption pressure, absorption temperature, top reflux ratio, and remaining acid gas load were analyzed for the offshore pilot gas field in their work. Similar type process simulation for natural gas sweetening was performed through HYSYS software by other.19 This work was performed for Khurmala gas field in Kurdistan, Iraq, and optimization of the process was examined by varying amine types, concentration, flow rate, and blends. The dynamic simulation and optimization of CO2 removal in acid gas absorber was performed recently with HYSYS.20 The work was carried out for a commercial plant, which showed that the column performance is significantly influenced by the temperature and volumetric flow rate. The CFD simulation of gas sweetening in hollow-fiber membrane contactor (HFMC) was studied by Rezakazemi et al.21 Chemical absorption of acid gas CO2 and H2S from natural gas was investigated through 2D mathematical model using MDEA as absorbent. The CO2 removal efficiency from flue gas of a pilot-scale amine absorber with structured packing was simulated through CFD modeling; meanwhile, simulation results were compared with experimental values. The effects of the four modification factors of the Ergun coefficients on liquid holdup and pressure drop was investigated by Kim et al. for acid gas absorption column.22 The good agreement of CFD results with that of experimental values of liquid holdup, wet pressure drop, and CO2 removal efficiency was found for these four adjusted factors. Very recently, Zhang et al. have studied acid gas absorption in randomly packed columns for FLNG gas pretreatment system using CFD simulations.23 There were respectively deviations of 7.8% and 8.3% for liquid relative velocity and pressure drop per unit length when CFD results were compared with those from experiments. Sloshing simulations with varying tilt angles and column aspect ratios were also performed to ascertain flow maldistributions in their work. Results showed that the flow maldistribution became more severe when the tilt angles increased. In addition, both bottom and top sections encountered most of this disturbance. CFD simulation for absorption column with structured packing for CO2 removal from natural gas stream was developed by Pham et al.24 They used monoethanol-amine (MEA) as solvent and Mellapak 500.X as the packing material. The static and roll motions were included in this investigation for three-dimensional absorption column. They observed that the uniformity of liquid B

DOI: 10.1021/acs.iecr.7b03631 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research Because the published data on liquid carry over for FLNG is lacking, the study results would still be beneficial for future further investigations.

2. METHODOLOGY FRAMEWORK The methodology framework of this study includes two major stages of work. First, liquid entrainment in the gas stream was estimated based on CFD simulations of a typical offshore multiphase oil−gas separator. Second, the obtained flow rate and compositions of feed gas from CFD simulations were input into steady-state process simulations to the gas pretreatment system of FLNG plants based on HYSYS. Meanwhile, the maldistribution of gas−liquid flow inside absorption/desorption columns due to sloshing was modeled by varying liquid/gas holdup for each stage. The flow maldistribution profile for acid gas column was obtained from Zhang et al.23 and used in the way in the proportional ratio. Finally, the following two simulation scenarios for the gas pretreatment of FLNG plants are conducted and analyzed: 1. Process simulation without any liquid entrainment in separator and sloshing in the acid gas removal and dehydration systems (base case). 2. Process simulation with the average of liquid entrainment from separator and the flow maldistribution in absorption columns (sloshing case).

Figure 2. Geometry and boundary conditions for three-phase separator for CFD simulation.

separator was performed using Eulerian multifluid volume of fluid (EMVOF) method. It is based on finite volume method (FVM) for representing and evaluating partial differential equations. Transient simulation of this sloshing was performed with first-order implicit scheme with time step size of 0.001 second. The Phase Coupled Simple (PC-SIMPLE) scheme was used for pressure velocity coupling, while the Realizable k-ε model was selected for turbulence calculation. The drag forces experienced by bubbles were modeled through symmetric drag correlation. The standard wall function was used for fluid and wall interaction modeling. The interface between oil−water, gas−oil, and water−oil were captured through the COMPRESSIVE scheme. Mass flow inlet boundary conditions are used at the inlet with pressure outlet for the gas flow and velocity outlets for both oil and water outlets (see Figure 2). Oil was considered as the primary phase while secondary phases volume fractions of 0.011 and 0.96 for water and gas, respectively, were used at the inlet boundary. The physical properties of materials used for CFD simulations are shown in Table 1. Wave motion of roll 10°,

3. MESH INDEPENDENT STUDY A grid independent study has been performed to identify the optimum mesh size for the full scale three-phase oil−gas separator. Three cases with the total computational cells of half million, slight above one million, and two million were considered for this purpose. Figure 1 shows the comparison of these cases for cross sectional velocity measured against time. It can be seen that the cases with 1182k cells and 2024k cells have similar values for velocities. The maximum deviation for these two cases is less than 10% compared with the value from 500k cells. Hence, the mesh grid with 1182k computational cells was employed for all the CFD simulation in this work. Assembly meshing with Cutcell method was performed using ANSYS workbench meshing tool for this study. In addition, structured hexahedral mesh with orthogonal quality of 0.98 was obtained from this process. Note that the input conditions and the geometry information for the separator were obtained from Lee et al.9

Table 1. Properties of Three Phases Used for CFD Simulation

4. MODELING AND RESULTS In this study, CFD simulations with the Eulerian numerical schemes were performed to estimate the liquid carryover (entrainment) in the gas phase. Then, data obtained from this simulation were integrated with the process simulation with HYSYS. The goal of this work is to understand effects of liquid carryover and flow maldistribution on the gas pretreatment process system. The results are presented in this sequence for discussion in the following sections. 4.1. CFD Study. An offshore three-phase separator with the length of 10.4 m, and the diameter of 4.0 m is used for the CFD analysis. The inlet diameter is 32 in., gas outlet diameter is 26 in., and the oil, water outlet diameters are 16 in. each (see, Figure 2). The separator’s geometry and operating conditions were obtained from Lee et al.9 The convergence criteria for all the equations solved in CFD simulations was set to the value of residuals less or equal to 10−3. Sloshing calculations for this

pitch 3°, and period (T) 10 s was imposed for this simulation. The center of rotation is 19 m in the X-direction, 53 m in the Ydirection, and 23 m in the Z direction from the center of the vessel. This wave motion is modeled after actual field data obtained from Cameron Corporation. Most of the liquid entrainment studies by CFD modeling was done using the VOF method. The VOF method treats the phases as immisible, and no interphase mass transfer takes place as a result. To estimate the liquid carryover in the gas phase, separate numerical scheme is used in addition to VOF.26,27 Liquid particles are injected to a converged VOF simulation to achieve the carryover. The most widely used scheme is (DPM) for this purpose. Liquid carryover in the gas phase for oil−gas separator with droplets coalescence due to vessel internal was investigated by Lu et. Al.27 They employed VOF and DPM multiphase Euler−Lagrange nuerical schemes to observe this on high pressure (HP) and low pressure (LP) separators. A total of 426

phases/imterphase oil phase water phase gas phase water−oil oil−gas water−gas

C

density (kg/m3)

viscosity (poise)

870 1100 4.136

0.69 0.00698 0.00012

surface tension (dyn/cm)

30 25 70


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Figure 3. Contour plots of gas, oil, and water phases inside the separator corresponding to (a) no sloshing, (b) average carryover, and (c) maximum carryover.

Figure 4. Liquid carryover in terms of volume fraction at the gas outlet.

population balance method (PBM) with Rosin−Rammler size distribution to incorporate a range of droplet sizes in their CFD simulation. Their finding was in good agreement with scarce field data available. However, this simulation is computationally expensive as it could easily take a month of high performance cluster (HPC) running time. To overcome the above drawback, CFD simulations of the three-phase separator in the presence of wave motion were performed using EMVOF method. In this numerical scheme, the phases are treated as inter penetrating and inter phase mass transfers take place as a result. The governing equations for EMVOF method28 are given below: Continuity equation:

liquid droplets were released from inlet device with particles diameter ranging from 10 to 60 μm. Results showed that droplets size greater than 40 μm were not carried over to the gas outlet for both HP and LP separators. They also tracked the number of injected particles escaped to the gas phase to quantify liquid carryover. The number of injected oil particles escaped to the gas outlet for HP were 327, 157, and 28 for the droplets size of 10, 20, and 30 μm, respectively. Similar trends were observed for LP separators. Qaroot et. al have deployed DPM with VOF multiphase modeling to study the effect of coalescence and breakup of oil droplets to analyze flow behavior and separator performance.26 They found that DPM simulations without the coalescence and breakup exhibit better separation efficiency compared to the case when these factors are included. Howerver, the separation efficiency did not decrease substantially for the cases which includes coalescence and breakup. They attributed this result to the additional separator internals such as Schoepentoeter. Droplet sizes at various location in the gas phase was also monitored in this investigation. Results showed that the added vessel’s internal had positive outcome on the separator performance as these helped coalesce liquid droplets into bigger sizes. As evident from these results, the VOF method in combination of DPM can only give some qualitative estimates of carryover. Furthermore, this data is not adequate to incorporate into process simulation software such as HYSYS. Other notable studies for the liquid entrainment in the gas phase for onshore oil gas separator was performed by Kharoua et al.10 They used

⎯→ ⎯ ∂ (αqρq ) + ∇·(αqρq vq ) = ∂t

∑ (mpq − mqp),

p = 1, ..., n (1)

Momentum equation: ⎯→ ⎯ ⎯→ ⎯ ⎯→ ⎯ ∂ (αqρq vq ) + ∇·(αqρq vq vq ) ∂t ⎯→ ⎯

= −αq∇p + μ∇2 vq + αqρq g n

+

⎯→ ⎯

∑ (K pq( vp −

⎯→ ⎯ vq )

⎯→ ⎯

+ (ṁ pq − ṁqp)) + ( Fq ) (2)

p=1

where Fq⃗ is the external body force, Kpq is the interphase momentum exchange coefficient and defined by K pq = D

αqαpρq f τq

, f is


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Figure 5. Comparison of liquid carryover at gas outlet (a) without sloshing and (b) with sloshing.

the drag function and defined by f = relaxation time and defined by τq =

ρq dq2 18μq

C DRe , 24

carried to the gas outlet was about 9.5% volume of the outlet. The average and minimum values were found to be 5.26% and 3.19% volume of the gas outlet. The liquid carryover due to sloshing and no sloshing conditions were compared with scarce field data available in open literature. The maximum amount of liquid carryover at the gas outlet for no sloshing condition was 0.06 L/MMSCF (million standard cubic feet). This value is about 60% of onshore carryover field data10 (Figure 5a). For the CFD sloshing case, the maximum liquid carryover was 97 L/MMSCF, the minimum was 4 L/MMSCF, and the average value was 52 L/MMSCF (Figure 5b) at the gas outlet. These values are much higher in comparison to the onshore field data.10 These differences were expected as the onshore oil−gas separator did not experience sloshing. However, when these values were compared with data obtained from North Western Australian offshore gas field, the average value of carryover matches the field data (see, Table 2). For comparison with scarce offshore field data (Table 2), the volumetric flow rate was converted to mass fraction. Therefore the results obtained from CFD simulations can be used with confidence. Another point to note is that although the carryover amount due to sloshing may be only a small fraction of total gas flow rate, this amount still has a high impact on a gas

τq is particle

, ρ is density of the

mixture and defined by ρ = ∑αqρq, μ is viscosity of the mixture and defined by μ = ∑αqμq, αq volume fraction phase q and ∑qn = 1 αq = 1, ρq is density of phase q, and vq⃗ is velocity of the qth phase. The wave load of 10° of roll and 3° of pitch was applied to this system along with same operating and boundary conditions. The actual CPU time to carry out 3.5 s of this simulation took 15 days of continuous run of a workstation with eight processors and 16 GB RAM. The velocity field and flow conditions were modeled in such way that there was negligible liquid carryover without deploying the various separator’s internals such as baffles, demister. Figure 3 shows contour plots of gas, oil, and water phases inside the separator, where Figure 3a shows the contour plot without sloshing impact; parts b and c of Figure 3 show contour plots under the average and maximum liquid carryover due to sloshing, respectively. The amount of liquid carryover in terms of volume fraction was monitored for every 0.1 s at the gas outlet. Figure 4 shows the data for volume fraction monitoring of this estimation for sloshing condition. As seen from the chart, the maximum liquid E


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(HYSYS) as the “SOUR GAS”. This stream goes to a feedwater knockout drum (FWKO) to get rid of condensate. The vapor from this unit goes to acid gas removal unit (AGRU), where it reacts with DEA to remove CO2 and H2S. The rich amine from the bottom of this column is then processed through a regeneration cycle. Meanwhile, the “SWEET GAS” coming out from top of AGRU is introduced into the dehydration system. The main objective of this simulation is the ascertain the performance of gas pretreatment system in terms of flow rate and composition of treated gas in the presence of sloshing. The duties of process equipment were not considered for this present study. 4.2.1. Acid Gas Removal Unit. Three steady-state simulation cases were performed for AGRU process to observe the influence of liquid carryover and maldistribution of flow inside the absorption tower due to sloshing. A converted DBR amine package was used as the thermodynamic property package, which is best suited for this simulation. The absorber column had 20 stages with Pall rings as packing material. For the amine regeneration tower, the same thermodynamic property package was used and the number of stages was seven. The flow maldistribution inside the absorption tower was modeled after recently published CFD simulation results from Zhang et al.23 for a pilot-scale absorption column for an acid gas removal unit. The column height considered in their studies was 1.8 m. Both static and rolling motion were applied to the column. For the maximum angular displacement (tilt) of 9°, they observed that the top of the column occupies only 5% liquid volume flow while bottom of the column occupies 56%. The middle section experiences liquid volume fractions of 0.25 through 0.39. Assuming this flow profile will be the same when the column dimension increases, this maldistribution of flow profile was deployed for acid gas removal unit in this study. The absorption column is subjected to two directional angular displacement, 10° about the Y axis (roll) and 3° about the X-axis (pitch). The resultant angular displacement (tilt) is 10.42°. Hence, the maximum tilt in this study was in the proximity of maximum tilt investigated by Zhang et al.23

Table 2. Liquid Carryover Comparison for Offshore Multiphase Separators mass percentage (%)

description

14.58 23.9 0.0127 15.42

CFD average CFD maximum CFD minimum field data (offshore)

pretreatment system’s performance. Commercial enterprises like Cameron Corporation and Sulzer Inc. have set the limit of 0.1 US gallon per MMSCF (0.378 L per MMSCF) liquid carryover for their process equipment due to the compressor requirement. In addition, the maximum limit recommended by Society of Petroleum Engineers (SPE) for the mist eliminator is 0.1 US gallon per MMSCF in this regard. However, this recommended carryover limit is for onshore locations or normal operations in calm offshore conditions only, and for high storm conditions the demisting device cannot effectively control the liquid carryover to such low level. Because the purpose of this study is to determine FLNG gas pretreatment system performance during severe/abnormal operating condition, the higher liquid carryover flow condition is used to understand how that effects the downstream gas processing. Results from CFD studies for the three-phase oil−gas separator also show that liquid carryover at the gas outlet can be estimated by EMVOF model more accurately than VOF model. Although VOF results can be utilized to design vessel internals such as baffle spacing and demister configuration, the liquid entrainment estimated through volume, mole, and mass fractions can be only performed with EMVOF model. Furthermore, these results can be used to determine the feed stream conditions for process simulations. 4.2. Process Simulation. To identify the impact of sloshing on the gas pretreatment of FLNG liquefaction systems, process simulations using HYSYS software were respectively performed with and without liquid carryover in the gas phase. The gas stream coming from multiphase separator (i.e., the CFD simulation data) was introduced into the process simulator

Figure 6. Process flow diagram of the AGRU system for the base case. F


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Industrial & Engineering Chemistry Research Table 3. Acid Gas Removal Performance for the Base Case component (mol %)

sour gas

gas to contactor

DEA to contactor

sweet gas

rich DEA

flash vapor

acid gas

nitrogen CO2 H2S methane ethane propane i-butane n-butane i-pentane n-pentane n-hexane n-heptane H2O DEA

0.07 3.6 0.78 76.67 11.41 4.03 0.92 1.21 0.42 0.32 0.58 0 0 0

0.07 3.6 0.78 76.67 11.41 4.03 0.92 1.21 0.42 0.32 0.58 0 0 0

0 0.05 0 0 0 0 0 0 0 0 0 0 93.75 6.2

0.07 0.01 0 80.03 11.91 4.21 0.96 1.26 0.44 0.33 0.59 0 0.19 0

0 2.35 0.51 0.09 0.01 0 0 0 0 0 0.01 0 91.0 6.03

0.03 3.45 1.27 76.57 11.07 2.92 0.11 0.23 0.42 0.34 0.52 0 3.06 0

0 59.22 12.92 0.17 0.03 0.01 0 0 0.04 0.04 0.2 0 27.39 0

Table 4. Acid Gas Removal Performance for the Sloshing Case component (mol %)

sour gas

gas to contactor

DEA to contactor

sweet gas

rich DEA

flash vapor

acid gas

nitrogen CO2 H2S methane ethane propane i-butane n-butane i-pentane n-pentane n-hexane n-heptane H2O DEA

0.09 4.88 1.04 59.26 12.58 9.36 2.08 1.6 0.56 0.43 4.87 3.26 0 0

0.12 5.34 0.95 70.29 12.35 7.22 1.23 0.85 0.21 0.15 0.92 0.35 0 0

0 0.04 0.01 0 0 0 0 0 0 0 0 0 93.75 6.20

0.12 4.43 0.52 71.15 12.50 7.32 1.25 0.86 0.21 0.15 0.92 0.35 0.2 0

0 0.52 0.22 0.09 0.01 0.01 0 0 0 0 0.01 0 92.98 6.16

0.07 0.02 0.05 78.93 12.06 5.24 0.19 0.18 0.25 0.18 1.07 0.35 1.4 0

0 48.43 21.72 1.04 0.21 0.09 0 0 0.04 0.03 0.61 0.44 27.38 0

The maldistribution of flow in the column was implemented by varying flows in top four and bottom four stages in accordance with the maldistribution trend identified from this literature. A steady-state process simulation using HYSYS V8.8 was performed with the gas stream compositions modeled with onshore gas field data and no flow maldistribution in the absorption column. This simulation was called the “base case” for both acid gas removal and natural gas dehydration systems. Figure 6 shows the process flow diagram of the base case for acid gas removal systems. 25 MMSCFD of natural gas (SOUR GAS) with less liquid carryover (i.e., onshore field composition) entered the system as “SOUR GAS” into FWKO. The purpose of this unit was to remove condensate from gas stream. For the base case, all of the 25 MMSCFD gas (GAS TO CONTACTOR) flows to acid gas removal column as there was an insignificant amount of condensate present in the stream. The gas stream then reacts with DEA in the absorption column. The following reactions take place inside the column to remove CO2 and H2S from the gas stream.29,30 (C2H5O)2 NH + H 2O → (C2H5O)2 NH+2 + OH−

(3)

H 2O → H+ + OH−

(4)

CO2 (vap) → CO2 (aq)

(5)

CO2 (aq) + H2O → H+ + HCO−3

(6)

(C2H5O)2 NH + H+ + HCO−3 → (C2H5O)2 NHCOOH+ + OH−

(7)

H 2S + (C2H5O)2 NH → [(C2H5O)2 NH]H+ + HS−

(8)

HS− → S2 − + H+

(9)

The amount of sweet gas coming out from top of the column (SWEET GAS) was 23.9 MMSCFD, while the DEA fed to the column (DEA TO CONT) was 6498 barrel/day. The rich amine solution coming out from the bottom of the absorption column (RICH DEA) was 6,81 barrel/day. This DEA then goes to the regeneration cycle, where it gets rid of acid gases. The combined amount of acid gas leaves the “flash tank” and “regeneration column” was 1.556 MMSCFD (ACID GAS). The makeup water flow rate (MAKEUP H2O) was 62.66 barrel/day for this system. Table 3 shows the acid gas removal unit’s performance under no sloshing condition. The methane mol % was 76.67 in “SOUR GAS”, which then increased to 80% in the “SWEET GAS”. The mole percentage of CO2 and H2S were 3.6 and 0.78 in “SOUR GAS” and 0.01 and 0 in the “SWEET GAS,” respectively. Hence, the gas stream is almost free of acid gases and the removal efficiencies of 99.7% for CO2 and 100% for H2S were achieved. The compositions of other streams also show reasonable values. A simple novel approach was used to implement the maldistribution inside the acid gas column. First, HYSYS simulation of acid gas column was performed without taking G


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Figure 7. Process flow diagram of AGRU system for the sloshing case.

into consideration the liquid carryover and flow maldistribution. The flow profiles of gas and liquid in each stage (plate) were monitored. The liquid gas flow rates (hold up) were recorded when the simulation converged. This flow profile was then used as base case without sloshing. Sloshing in the absorption column disrupts this flow profile and ratio of gas flow and liquid flow at each stage changes consequently. A recently published paper has delineated this maldistribution for pilot scale AGRU system through CFD simulation.23 As shown in this paper, the top stages of the column experiences liquid volume fraction of 5% while bottom stages of 56%. Midsection of the column has 25% liquid volume fraction. This pattern of flow rates was implemented inside the column by manually varying these flow rates for each stage in HYSYS steady state simulation. The results from this simulation is shown in Table 4. This table provides the compositions of the streams when the incoming “SOUR GAS” stream contains significant amount of liquid carryover, and the acid gas absorption column experiences the flow maldistribution due to sloshing. As seen from the Table 4, the mol % of methane decreases to 59.26 due to the significant amount of liquid carryover of heavier hydrocarbon components in the gas phase. The compositions of acid gas were 4.88 and 1.04 mol % for CO2 and H2S, respectively. Once this gas stream passes through FWKO drum, the composition of gas stream has been improved significantly. The gas stream entering absorption column contains 70.29 mol % of methane, 5.34 mol % of CO2, and 0.95 mol % of H2S. The effects of sloshing on the gas stream composition can be highlighted by comparing compositions from Tables 3 and 4. The mol % of methane in “SWEET GAS” is 71.15% under sloshing conditions vs 80% under no sloshing conditions. The removal efficiencies of CO2 and H2S decreased to 11.3% and 50%, respectively, from 100% due to the flow maldistribution inside the column. Figure 7 depicts the process flow diagram for AGRU system with the average liquid carryover and column flow maldistribution due to sloshing. As seen from Figure 7, the amount of gas entering (SOUR GAS) the system was the same 25 MMSCFD like the “base case” without sloshing. However, the volumetric flow rate of gas entering the AGRU unit (GAS TO

CONTACTOR) decreased to 18.77 MMSCFD when keeping all operating conditions the same. The rest of “SOUR GAS” flowed down from the FWKO. The sweet gas coming from top of absorption column (SWEET GAS) has decreased to 18.5 MMSCFD. This gas production rate is due to liquid carryover in the multiphase separators and sloshing in the AGRU unit. The amount of gas flow from the regeneration unit (ACID GAS) decreased substantially from 1.514 MMSCFD to 0.377 MMSCFD. The requirement for makeup H2O (MAKE UP H20) was also decreased to 19.22 barrel/day. All operating conditions were kept the same for both simulation cases. If the flow maldistribution inside the absorption column is not considered, this performance will improve substantially in terms of quality of treated gas. An additional HYSYS simulation case was performed without the flow maldistribution in the absorption column and the results are shown in Table 5. The Table 5. Acid Gas Column Performance at Average Carryover and without Flow Maldistribution streams

feed gas

lean amine

rich amine

sweet gas

H2S composition (ppm) CO2 composition (mol %)

9957.74 5.06

22.48 0.0526

5416.41 2.789

0.0857 0.0078

removal efficiencies for both acid gases were almost 100% comparing the feed gas to sweet gas. The amount of CO2 is decreased to 0.0078 mol % from 5.06 mol %. The amount of H2S is dropped for 9958 ppm to 0.0857 ppm. Hence, the sloshing in the AGRU is responsible for the decrease of removal efficiencies of CO2 and H2S to 11.3% and 50%, respectively. Furthermore, if only the liquid carryover due to sloshing in multiphase separators is considered, the sweet gas production rate is 18.5 MMCFD.31−33 4.2.2. Dehydration Unit. Two process simulation cases were performed to reduce the water content in the “Sweet Gas” coming out from acid gas removal system using HYSYS V8.8. The first simulation case was based on the flow rate and composition of sweet gas in the absence of sloshing (i.e., onshore field data) as the “base case”. The second case was performed H


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Figure 8. Process flow diagram of the dehydration system for the Base Case.

Table 6. Natural Gas Dehydration Performance for the Base Case component (mol %)

inlet gas

dry gas

sales gas

TEG feed

makeup TEG

rich TEG

acid gas

nitrogen CO2 H2S methane ethane propane i-butane n-butane i-pentane n-pentane TEGlycol H2O n-hexane n-heptane

0.07 0.01 0 80.08 11.91 4.18 0.95 1.25 0.43 0.33 0 0.19 0.59 0

0.07 0.01 0 80.22 11.94 4.19 0.95 1.25 0.43 0.33 0 0.01 0.59 0

0.07 0.01 0 80.22 11.94 4.19 0.95 1.25 0.43 0.33 0 0.01 0.59 0

0 0 0 0 0 0 0 0 0 0 0.9248 0.0752 0 0

0 0 0 0 0 0 0 0 0 0 99.0 1.0 0 0

0.01 0 0 1.28 0.44 0.21 0.02 0.03 0.01 0.01 57.95 40.04 0.01 0

0.02 0.01 0 3.42 1.18 0.57 0.05 0.08 0.02 0.01 0.03 94.58 0.02 0

Table 7. Natural Gas Dehydration Performance for the Sloshing Case component (mol %)

inlet gas

dry gas

sales gas

TEG feed

makeup TEG

rich TEG

acid gas

nitrogen CO2 H2S methane ethane propane i-butane n-butane i-pentane n-pentane TEGlycol H2O n-hexane n-heptane

0.12 4.43 0.52 71.15 12.5 7.32 1.25 0.86 0.21 0.15 0 0.22 0.92 0.35

0.12 4.43 0.52 71.31 12.53 7.33 1.25 0.86 0.21 0.15 0 0.01 0.92 0.35

0.12 4.43 0.52 71.31 12.53 7.33 1.25 0.86 0.21 0.15 0 0.01 0.92 0.35

0 0 0 0 0 0 0 0 0 0 92.49 7.51 0 0

0 0 0 0 0 0 0 0 0 0 99.0 1.0 0 0

0.01 1.04 0.46 1.29 0.51 0.41 0.03 0.02 0 0 58.47 37.73 0.01 0

0.03 2.84 1.24 3.52 1.39 1.11 0.08 0.06 0.01 0.01 0.04 89.63 0.03 0.01

with the composition and flow rate of the average liquid carryover in the gas stream together with the maldistribution of flows in absorption column. The flow maldistribution for dehydration column was not considered for any of the cases

because the liquid flow inside the column was very small compared to gas flow (i.e., 2−191 GPM). The thermodynamic property package of Peng−Robinson was used for the gas I


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Figure 9. Process flow diagram of the dehydration system for the sloshing case.

acid gas absorption column. The amount of inlet “Sweet Gas” flow rate is 18.5 MMSCFD, the flow rate of “Sales Gas” is 18.46 MMSCFD. The amount of “Makeup TEG” required for this simulation is 0.042 barrel/day, and the “Sour Gas” coming from the TEG regeneration unit is 0.043MMSCFD, which contains mainly water vapor (98.7%). Table 8 shows the overall flow rates comparison for combined gas pretreatment processes. The simulation case (HYSYS) where

dehydration process simulations. A packed column consists of 14 stages with Pall rings as packing materials was used in this regard. Figure 8 shows the process flow diagram along with streamflow rates for the base case natural gas dehydration system. “Sweet Gas” of 23.9 MMSCFD coming from the top of acid gas removal unit enters the bottom of tower T-100. The liquid desiccant of triethyl glycol (TEG) (TEG Feed) flows downward from the top of this column. TEG is widely used dehydration solvent for natural gas. The “Dry Gas” of 23.85 MMSCFD from top of T-100 is then passed through the heat exchanger E-101 for further heat treatment. The final gas stream is labeled as “Sales Gas”. The amount of “Sour Gas” coming out of regeneration unit is 0.044 MMSCFD which mainly consists of water vapor (about 98.7%) and the “Makeup TEG” flow rate is 0.0275 barrel/day for the whole dehydration process. Table 6 shows the composition of gas and liquid streams for base case dehydration system. The amount of water in the inlet “Sweet Gas” stream is about 0.2 mol %, and this amount is further reduced to 0.1 mol % after dehydration. There is no presence of H2S in both inlet and outlet “Sales Gas”. However, there is trace amount (0.01 mol %) of CO2 present in the final “Sales Gas.” The amount of methane gas available in the “Dry Gas” is 80.22 mol %. The amount of heavier hydrocarbons in the form of hexane and heptane is very low (0.6 mol %) in the “Sales Gas”. The compositions of other streams seem very reasonable. The composition of streams in the dehydration system for the case of average liquid carryover and flow maldistribution in the absorption column is shown in Table 7. The amount of water in the final “Sales Gas” stream is found to be 0.01 mol %, whereas it is 0.22 mol % water in the inlet “Sweet Gas”. This value is same as in the base case dehydration. However, the methane mol % is 71.31, where it is 80 for the base case. In addition, the acid gas compositions have increased to 4.43 mol % and 0.52 mol % for CO2 and H2S, respectively. The amount of heavier hydrocarbons in the form of hexane and heptane now equals to 1.27 mol %. The other streams show reasonable compositions. Figure 9 shows the process flow diagram along with flow rates for the natural gas dehydration simulation case with the average value of liquid carryover together with flow maldistribution in the

Table 8. Production Comparison between Base Case and Sloshing Case sour gas FWKO gas TO AGRU DEA TO AGRU sweet gas flash vapor acid gas from regen makeup H2O inlet gas to dehydration dry gas sales gas sour gas from regen TEG feed makeup TEG

base case

sloshing case

unit

25 0 25 6498 23.9 0.04168 1.514 62.66 23.9 23.85 23.85 0.04359 70.76 0.02747

25 4530 18.77 6500 18.5 0.04073 0.377 19.2 18.5 18.46 18.46 0.04256 70.76 0.04201

MMSCFD barrel/day MMSCFD barrel/day MMSCFD MMSCFD MMSCFD barrel/day MMSCFD MMSCFD MMSCFD MMSCFD barrel/day barrel/day

liquid carryover and flow maldistribution in the absorption column are not considered (base case). HYSYS simulation is the case where both flow maldistribution and liquid carryover are included (sloshing case). As seen from Table 8, both cases have the same inlet gas flow rates to the FWKO (SOUR GAS). The flow rate to the acid gas absorption column decreased for gas stream with liquid carryover. The loss of “SOUR GAS” flow to the acid gas removal unit can be attributed to the bottom stream flow rate of 4530 barrel/day of the FWKO unit. The amount of “Sweet Gas” and “Sales Gas” produced in the sloshing case has been dropped from 23.9 to 18.5 MMSCFD and from 23.85 to J


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18.46 MMSCFD, respectively. The requirement for makeup water flow rate dropped for this pretreatment system from 62.66 to 19.2 barrel/day for the sloshing case. There is also a drop in “Acid Gas” production from the DEA regeneration column (1.514−0.377 MMSCFD). The changes of flow rates for other streams are not significant.

5. CONCLUSION Disturbances due to external forces in the FLNG process causes the loss of operating efficiency in the process equipment. Sloshing impact was observed in both multiphase separators and acid gas absorption column in the FLNG gas pretreatment system. It affects the performance of all types of process operations such as separation, absorption, and desorption. In this paper, the influence of sloshing impact on performance of the FLNG gas pretreatment system was investigated. The sloshing phenomenon has been predicted via the integration of CFD modeling and process simulations with HYSYS. This approach is different from previous CFD investigations in this regard. Quantitative results show that sloshing impacts the performance of the FLNG gas pretreatment system adversely. In addition, the composition of gas streams obtained from this study demonstrates the good agreement between field data and simulation results. However, some CFD simulations of the acid gas column and various boundary conditions such as baffles, bubble breakup, and coalescence were excluded in this present study due to computational resource constraints. In terms of case setup of CFD, the population balance method (PBM) to account for various sizes of diameter, user defined function (UDF), and various turbulence and mixing models were also not considered. Future works will address these topics more thoroughly.

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AUTHOR INFORMATION

Corresponding Author

*Phone: (409) 880-7818. Fax: (409) 880-2197. E-mail: Qiang. [email protected]. ORCID

Qiang Xu: 0000-0002-2252-0838 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was partially supported by the Center for Advances in Port Management, President Visionary Project, and Anita Riddle Faculty Fellowship from Lamar University.

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REFERENCES

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