Bingcheng Liu1, Xuan Yang 1, Ting Wang1, Mengmeng Zhang1, Pen-Chi Chiang2

Qingdao University of Science and Technology, Qingdao 266061, China
Carbon Cycle Research Center, National Taiwan University, Taipei 10672, Taiwan


Received: October 21, 2019
Revised: November 4, 2019
Accepted: November 8, 2019
Download Citation: ||https://doi.org/10.4209/aaqr.2019.10.0519  

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Cite this article:

Liu, B., Yang, X., Wang, T., Zhang, M. and Chiang, P.C. (2019). CO2 Separation by Using a Three-stage Membrane Process. Aerosol Air Qual. Res. 19: 2917-2928. https://doi.org/10.4209/aaqr.2019.10.0519


Highlights

  • A new membrane process of CO2 capture from CO2-EOR extraction gas was displayed.
  • Matlab software used to simulate the new membrane process.
  • The important parameters of the system are obtained.
 

ABSTRACT


In this work, a three-stage membrane process for CO2 separation was proposed and optimized. The results of this study revealed that the proposed technology is a suitable process for the CO2 separation at higher concentrations. In addition, MATLAB was used to simulate and obtain the optimal operational parameters for a three-stage membrane process. A partial cycle was established, and the CO2 was recovered from the permeation side of the second-stage membrane, which enhanced the purity of the CO2 gas stream. The results of this study indicated that when the CO2 concentration was higher than 50% at a flow rate of 100000 Nm3 d–1, CO2 separation could be achieved under optimal operating conditions. Under conditions where the membrane areas were 2400, 3800, and 1800 m2 for the first-, second-, and third-stage membranes, respectively, and where the operational pressure at the first- and third stage membranes were 3.0 and 2.5 MPa, respectively, the CO2 separation fraction was higher than 90%, and the CH4 loss rate was less than 5%. The results of this study indicate a high potential for practical application.


Keywords: Optimal design; CO2-EOR extraction gas; CO2 capture; Multi-stage membrane separator.


INTRODUCTION


As the pace of oil exploitation was accelerated due to the importance of oil, more and more oilfields became less permeable due to mining and for geological reasons. Generally, the recovery efficiency of low permeability reservoirs is only 20 to 25% in oilfields, and the proportion of low permeability reservoirs in proven oil reserves is increasing annually (Wei et al., 2018). There are many flooding patterns, among which CO2-EOR is more available than is the case for water flooding, nitrogen, air and flue gas, and also has the advantages of being low cost and having high natural gas quality (Booran et al., 2016; Bender and Akin, 2017; Wang et al., 2017; Wang et al., 2018). However, CO2-EOR flooding leads to a more CO2 (about 40 to 60% of the injected gas) spilling out of the ground along with the gas produced during oil recovery (hereinafter referred to as the extraction gas). Meanwhile, with continuous exploration, a number of oilfields with higher CO2 content are being discovered. For example, the CO2 concentration in extraction gas fields in Malaysia ranges from 28% to 87% (Tan et al., 2012b; Jean et al., 2016; Xie et al., 2017; Yang et al., 2019). Large amounts of CO2 discharged directly into the atmosphere not only causes serious climate problems, but also can be harmful to human health (Ping et al., 2018; Shiue et al., 2018; Tsai et al., 2018). Therefore, it is a serious issue to find a means by which to capture CO2 capture from extraction gas.

In recent decades, several CO2 capture technologies have been developed, including as absorption, adsorption, membranes, and cryogenic technologies (Sreedhar et al., 2017; Vinoba et al., 2017). The chemical absorption method removes CO2 from the extraction gas through the convection contact between the feed gas and the chemical solvent in the packing column, with the usual solvents being monoethanolamine (MEA), diethanolamine (DEA), and methyldiethanolamine (MDEA), among others (Tan et al., 2012a; Li et al., 2016). However, a number of drawbacks have been revealed using this method, including a large volume occupancy and some operational problems such as flooding, channeling, entrainment and foaming (Ghasem et al., 2012a). Chemical absorption technology is usually used to process extraction gas within a relatively narrow feed range (Fu et al., 2012). Therefore, in the case of high CO2 concentrations (approximately 60% or more) at 0.3–0.6 MPa, the chemical method may not be applicable due to excessive circulating amounts and poor absorption effects. Holmes and Ryan (1982) first invented cryogenic distillation for natural gas purification, which also can be used for CO2 capture. However, due to the high energy consumption of this technology, which accounts for about 50% of the total energy, this technology has not been widely used in CO2 capture from extraction gas (Ebrahimzadeh et al., 2016).

In recent years, membranes for CO2 separation are receiving growing attention for application in the field of CO2 capture and storage (CCS) (Boot-Handford M et al., 2014; Roussanaly S et al., 2016). Compared with chemical absorption, membrane-based separation is more attractive due to its easy installation, a minimal influence of SOx and NOx on membrane materials, and avoidance of regeneration energy consumption (Merkel et al., 2010; Rufford et al., 2012). To achieve good development prospects, the membrane-based method must develop “good” membrane modules and membrane materials. Robeson (2008) has identified the upper bound on membrane material selectivity and permeability in many gas separation systems, including CO2/N2, O2/N2, CO2/CH4 and H2/CH4, etc. In the membrane separation process, the membrane material is the first element because the selectivity and permeability of the membrane directly determine the separation efficiency. It is well known that the performance of polymeric membranes is characterized by an ‘upper bound’ that correlates with permeability and selectivity (Robeson, 2008). However, in recent years, many new materials, such as MOFs and ssz-13, have also been applied in the membrane separation field, with good performance in terms of separation performance and permeability (Rodenas et al., 2015; Chisholm et al., 2018). Gas permeability through a polymer membrane depends on the solution-diffusion mechanism, in which the rate of gas movement correlates with the ratio between the gas molecules and the membrane material and the diffusion rate (Rufford et al., 2012). Polyimide is a very attractive polymer that can be used in membrane technology, due to having high selectivity and high permeability, as well as the fact that it can be used for various applications such as gas and liquid separation (Favvas et al., 2017).

In order to obtain high quality product features, a multi-stage membrane separation device was proposed to multi-separate the product gas and in turn improve product purity rather than a single-stage membrane device, which is inexpensive but preforms poorly. Experiments capturing CO2 from natural gas in a single-stage membrane device were conducted under high pressure conditions or efficient absorbents in order to study the influence of membrane area, membrane pressure, and feed gas flow rate on CO2 removal rate (Kang et al., 2017). Few studies have been done on multi-stage membrane devices. These studies include separation of O2 from air, CH4 from biogases and landfills, CO2 from coal flue gases, and H2 from H2/CO mixtures (Rautenbach et al., 1987; Bhide et al., 1991; Xu et al., 1996; Zhao et al., 2011). Ohs et al. (2016) recently applied a superstructure method to remove N2/CH4 from natural gas in order to identify the optimal processes and structural parameters. In addition to not fully considering the membrane separation structure and overall operation parameter optimization, they also did not have an overall process design for the CO2/CH4 system. Chong et al. (2017) proposed a polymeric membranes for O2/N2 gas separation through using N,N-dimethylacetamide (DMAc) and tetrahydrofuran (THF) and ethanol as additives, where a polysulfone (PSF) hollow fiber membrane was created. This membrane can be used to achieve a better O2/N2 separation rate.

We proposed a three-stage membrane separation process based on single-stage membranes and the literature on this topic. In this study, the CO2 capture performance of the membrane separator was investigated using extraction gas with high concentrations of CO2 (60%) as feed. A mathematical model was established and introduced into MATLAB for numerical simulation of the membrane separation. The effects of the operating pressure and membrane area on the CO2 recovery fraction and CH4 loss rate were discussed in regard to the optimal parameters. This investigation will provide guidance for the application of multi-stage membrane separators in the CO2 capture of extraction gas.


METHODOLOGY



Extraction Gas

We have been injecting CO2 into the underground oil layer since 2012. In the subsequent six years, the changes in CO2 concentrations over time in the Shengli oilfield and the CO2 concentrations were continuously monitored in the extraction gas, as shown in Fig. 1. As shown in Fig. 1, in the entire oil recovery process after the CO2 injection, the CO2 content in the extracted gas increased from the original 1.5% to above 90%. The CO2 content in Well89 1–7 increased sharply in the initial phase and quickly rose in the second phase, while Well89 S1 remained stable at a low content for a long time in the initial phase. However, after a period of time, the CO2 concentration in both wells rose rapidly in the third phase, where the concentration range was stable at 60%–90%. After a few years, the total gas volume may increase tenfold compared to the gas injection, causing significant fluctuations in CO2 gas, which will result in technical difficulties related to separation and further treatment.


Fig. 1. CO2 extraction gas concentrations in Well-89 in the Shengli oilfield.Fig. 1. CO2 extraction gas concentrations in Well-89 in the Shengli oilfield.

Results related to heavy hydrocarbon components are demonstrated in Fig. 2, where it can been seen that heavy hydrocarbon content of C5+ is relatively stable, at about 2%–3%, but the content of C3+ is volatile, as high as 15%. Therefore, it is necessary to design a special pretreatment module to remove these compounds. The C5+ content may contaminate membrane devices and in turn cause membrane material poisoning. Therefore, a special pretreatment module should be designed to remove heavy hydrocarbons, which will be carried out in the future work. 


Fig. 2. Pie diagrams of extraction gas component.Fig. 2. Pie diagrams of extraction gas component.

According to the CO2 content shown in Fig. 1, we divided the produced gas into area Ⅰ (CO2 concentration< 30 mol%), area Ⅱ (30 mol% < CO2 concentration < 60 mol%), and area Ⅲ (CO2 concentration > 60 mol%). In conclusion, the extraction gas in area III has the following characteristics: large gas flow, high CO2 partial pressure, high CO2 concentrations (60% or greater), and the main components are CO2 and CH4. For CO2 concentrations above 60%, our primary work and that of Kang et al. (2017) recommend membrane separation, which is also a key part of this work.


Process Description

The process of membrane-based separation was displayed in Fig. 3. The extraction gas is first processed through the pretreatment module, in which the liquid water, heavy hydrocarbons, and solid particles carried in the EOR extraction gas are removed. Otherwise, the membrane components will be blocked, and the membrane materials will be contaminated, which will affect the normal operation of the membrane system. Since the research on the pretreatment process is not mature, the design was not discussed in this paper. After processing through thee pretreatment module, the gas (material 1) that is passed through the pretreatment system was then compressed into the first-stage membrane device for gas separation. Furthermore, the gas was split into two streams, one of which was permeate gas loaded with CO2 (material 2), and the other of which was entrapped gas loaded with CH4 (material 3). The former entered the third-stage membrane separator after being pressurized in compressor for further purification, and the latter directly entered the second-stage membrane for purification of CH4 gas. The permeate gas stream treated by the third-stage membrane separator was the CO2 product gas (material 4) while the stream generated by the second-stage membrane was the CH4 product gas (material 5). However, the permeate gas from the second-stage membrane contained in the CO2 (material 6) was designed to mix with the inlet gas to carry out a partial circulation because the concentration of CO2 was similar to that of the feed gas. The entrapment side of the third-stage membrane was discharged as exhaust gas (material 7). The module used in the design was a hollow fiber which is equivalent to the mass transfer of a shell and tube heat exchanger (Mat et al., 2014). This type of assembly can significantly improve the performance of the membrane by increasing the chemical potential difference across the membrane. A polyimide membrane was selected as the membrane material, and the separator parameters followed Robeson (2008). The design parameters were selected as shown in Table 1


Fig. 3. Process description of membrane separation.Fig. 3. Process description of membrane separation.


Table 1. Design Parameters.

In the case of the membrane-based capture, there are two main factors that affect the CO2 recovery fraction and CH4 loss rate in the entire process. One is the membrane area, and the other is the membrane pressure, which are also the two objects we discussed herein. The membrane areas comprised the first- second- and third-stage membrane areas. The CO2 concentration in the purified gas was mainly affected by the second-stage membrane area, while that in the captured gas was mainly affected by the third-stage membrane area. There was no required connection between the second-stage membrane and the third-stage membrane. Therefore, the second- and third-stage membrane areas were tentatively determined to optimize the first-stage membrane area. After analyzing the influence of first-stage membrane area on the CO2 concentration in purified gas and the concentration of the CO2 product gas, the first-stage membrane area was obtained, and then the second-stage membrane area and the third-stage membrane area were optimized. The operating pressure was the outlet pressure of the compressor, which directly affected the pressure of the feed gas, where if the pressure of the feed gas was increased, the gas passed more quickly through the membrane, which increased the CO2 recovery fraction and decreased the membrane area.


Process Simulation


Membrane Unit Model

As shown in Fig. 4, a counter-current flow pattern was developed in this study utilizing the tank-in-series concept (Huang et al., 2018; Lee et al., 2018). This ideal model did not take into account the pressure drop, concentration polarization, or scaling on the residual side. Simulation optimization conditions were achieved using the Simulink component optimization in MATLAB, which is a reliable calculation method.

Fig. 4. The separation module with a counter-current flow pattern.Fig. 4. The separation module with a counter-current flow pattern.

Mass differential equation:

Differential equation of flow:

Differential equation for change in CO2 concentration: 

Differential equation for change in CH4 concentration: 

where U is the flow of feed gas, Nm3 h1; V is flow of permeate gas, Nm3 h1; X is the concentration of CO2 in the feed gas; Y is the concentration of CO2 in the permeate gas; Ph is the pressure of the feed gas, MPa; Pl is the permeate pressure, MPa; and A is membrane area, m2.

With boundary conditions: l = 0; U = U0; x = x0; l = L; V = 0; xL = yL.

The following is the integral from the entry (l = 0) of the separator to any section of Eq. (3):

Using Eq. (3), the permeate gas concentration of each cross section in fiber bundles (l ≠ L) can be obtained. Because when L = l, V = 0, the permeation gas concentration of yL cannot be directly obtained from Eq. (3). Therefore, yL is now defined as:

When l  L, yL, is defined as:

The simulation results can be obtained by means of differential equations and boundary conditions using MATLAB.


Mass Balance Equations for the Three-stage Membrane Process

Binary variables are used in this study to represent the presence or absence of any structural options in this optimization. Additionally, a genetic algorithm (GA) is applied in the simulation, which can easily obtain the variable calculation results in the MATLAB simulation environment (Lee et al., 2018). The mass equilibrium and composition equilibrium based on binary variables are defined as follows:

The flow rate mass balance for the first membrane stage is:

The flow rate mass balance for the second- and third-stage membrane stage is:

where F1 is the flow rate, Nm3 h1; Ffeed is the flow rate of feed gas, Nm3 h1; Fe is the flow rate on the entrapped side, Nmh1; Fp is the flow rate on the permeate side, Nm3 h1; s is splitter numbers; n is the stage number of the membranes; Sp is the binary variable for flow connections on the permeate side; Se is the binary variable for flow connections on the entrapped side, and N is the overall number of membrane stages.

The composition balance for the first membrane stage is:

Composition balance for the second- and third- membrane stage is:

where fi is the mole fraction of the component; ffeed is the mole fraction of each component at the overall feed flow rate; fe is the mole fraction of the entrapped side component, and fp is the mole fraction of the permeate side component.


Power Consumption

Power consumption is an important parameter for evaluating CO2 capture performance. However, the power requirement of the three-stage membrane process is due to the compressor, so the calculation of power consumption is shown as follows (Song et al., 2017):


RESULTS AND DISCUSSION



Effects of Membrane Area


First-stage Membrane Area

The optimal first-stage membrane area was obtained by changing the membrane area from 2300 to 2700 m2, obtaining the CO2 concentration in the outlet gas stream, and measuring the CO2 recovery fraction and the CH4 loss rate. Based on previous studies, the second- and third- stage membrane areas were 3500 and 2000 m2, respectively.

In Figs. 5 and 6, it can be seen that an increase in the first-stage membrane area affected the separation efficiency of CO2/CH4. It was negatively correlated with the CO2 recovery fraction and CO2 concentration and was positively correlated with the CH4 loss rate. The above results indicated that an increase in the membrane area hindered the separation of CO2 and CH4


Fig. 5. CO2 concentration along with the change in the first-stage membrane area.Fig. 5. CO2 concentration along with the change in the first-stage membrane area. 


Fig. 6. CO2 recovery fraction and CH4 loss rate along with the change in the first-stage membrane area.Fig. 6. CO2 recovery fraction and CH4 loss rate along with the change in the first-stage membrane area.

When the first-stage membrane area was greater than 2500 m2, the CH4 loss rate was as high as 5%. In order to lower the of CH4 loss rate, the first-stage membrane area needed to be less than 2500 m2. However, if considering both the CO2 recovery fraction and CH4 loss rate, the first-stage membrane area was selected to be 2400 m2, which resulted in a 98.6% CO2 recovery efficiency and a 4.2% CH4 loss rate.


Second-stage Membrane Area

After the first-stage membrane, the CO2 concentration had to be further purified. If the first- and third-stage membrane areas were selected to be 2400 and 3000 m2, respectively, the second-stage membrane area was varied from 2000 to 4000 m2 for the purpose of obtaining an optimal second-stage membrane area.

The main purpose of the second-stage membrane was to obtain a higher concentration of CH4 gas. Therefore, a lower CO2 permeate concentration was better. In Fig. 7 shows that a higher second-stage membrane area did decrease the permeate CO2 concentration from 3% to less than 0.5%. In order to ensure that permeate CO2 concentration be less than 2%, the second-stage membrane area was set to be 3800 m2

Fig. 7. CO2 concentrations in the outlet gas stream along with changes in the membrane area.Fig. 7. CO2 concentrations in the outlet gas stream along with changes in the membrane area.


Third-stage Membrane Area

When the first- and second-stage membrane area were selected to be 2400 and 3800 m2, respectively, the optimal membrane area of the third-stage was determined by looking at the CO2 recovery fraction and CH4 loss rate data.

Fig. 8 shows that an increase in the third-stage membrane area resulted in an increase in the CO2 recovery fraction, which rose from 50% to higher than 95% and finally became stable.

When the third-stage membrane area was higher than 2000 m2, the CO2 recovery fraction and CH4 loss rate were both stable and at around 97% and 4.5%, respectively. However, when the membrane area was greater than 2000 m2, the CH4 loss rate declined both linearly and rapidly. Under conditions where the third-stage membrane area was 1800 m2, the CO2 recovery fraction and CH4 loss rate reached 90.5% and 4.45%, respectively.

Fig. 8. CO2 recovery fraction and CH4 loss rate along with changes in the membrane area.


Effects of Operating Pressure


Operating Pressure for the First-stage Membrane

When the CO2 concentrations in the inlet gas stream were 0.5, 0.6, 0.7, and 0.8 and the operating pressure at first-stage membrane was set at 1.5, 2.0, 2.5, 3.0, and 3.5 MPa, respectively, the variations in the CO2 recovery fraction and CH4 loss rate for the first-stage membrane were calculated and analyzed.

In Fig. 9 shows that as the operating pressure for the first-stage membrane continued to rise, both the CO2 recovery fraction and CH4 loss rate were increased. When the operating pressure for the first-stage membrane pressure was 3 MPa, the CO2 recovery fraction was over 90%, and CH4 loss rate was less than 5%. Obviously, a high pressure did increase the flux of CO2 gas through the membrane. According to the curve in Fig. 10, it can be seen that excessive pressure lead to a reduction in the CO2 recovery fraction. 


Fig. 9. CO2 recovery fraction and CH4 loss along with changes in the operating pressure.
Fig. 9. CO2 recovery fraction and CH4 loss along with changes in the operating pressure.

Fig. 10. Power consumption with changes in the first-stage pressure.Fig. 10. Power consumption with changes in the first-stage pressure.

A proper membrane operating pressure lead to a good gas separation effect and also improved CO2 recovery efficiency. Therefore, the operating pressure was setting to range from 2 to 4 MPa. According to Fig. 10, when the optimal pressure was 3 MPa, the power consumption was 115.4 kW.


Operating Pressure for the Third-stage Membrane

The operating pressure for the first-stage membrane was fixed at 3 MPa, and those for the third-stage membrane were set at 1.0, 1.5, 2.0, and 3.0 MPa, respectively. This made it possible to obtain the optimal pressure for the third-stage membrane can be obtained.

As shown in Fig. 11, both the CO2 recovery fraction and CH4 loss rate increased with increases in the operating pressure. When the CO2 concentration in the input gas stream was either 0.5 or 0.6, the operating pressure for the third-stage membrane was 2.0 MPa; the CO2 recovery fraction was higher than 90%, and the CH4 loss rate was less than 5%. When the CO2 concentration in the input gas stream was either 0.7 or 0.8, the operating pressure for the third-stage membrane was 2.5 MPa, and both a high CO2 recovery fraction and a low CH4 loss rate can also be obtained. The driving force required for a low CO2 concentration was lower than that for a high one. Therefore, from the perspective of saving energy, a different operating pressure could be adopted for CO2 separation for different CO2 input concentrations. A data analysis indicated that the operating pressure for the third-stage membrane should be set at 2.5 MPa. 


Fig. 11. CO2 recovery fraction and CH4 loss along with changes in the operating pressure.Fig. 11. CO2 recovery fraction and CH4 loss along with changes in the operating pressure.

Under conditions where the first-, second- and third-stage membrane areas were 2400, 3800 and 1800 m2, respectively, and the operating pressure for the first- and third stage membrane was 3.0 and 2.5 MPa respectively, the simulation results are shown in Table. 2, which indicates that the CO2 recovery fraction was over 90%; the CH4 loss rate was less than 5%, and the power required was 203.4 kW (Fig. 12). By contrast, Song et al. (2017) obtained a CO2 recovery fraction of 84.6%, and the power required was 2.8 MJ kg–1. The three-stage membrane process used in the current study can thus improve power consumption by 4% power consumption and can achieve a higher CO2 recovery fraction. 


Fig. 12. Power consumption with changes in the third-stage pressure.Fig. 12. Power consumption with changes in the third-stage pressure. 



Table 2. Summary of three-stage membrane process. 


CONCLUSIONS


  1. Membrane technology is more suitable for the CO2 separation at higher concentrations.

  2. In this study, MATLAB was used to simulate and obtain the optimal operational parameters for the three-stage membrane process. This work established a partial cycle and recovered the CO2 from the permeation side of a second-stage membrane, thus improving the purity CO2 of the gas stream.

  3. The results of this study indicated that when the CO2 concentration is higher than 50% and at a flow rate of 100000 Nm3 d1, CO2 separation can be achieved under optimal operating conditions. Under conditions where the membrane areas were 2400, 3800, and 1800 m2 for the first-, second-, and third-stage membrane, respectively, and the operating pressure for the first- and third stage membranes was0 and 2.5 MPa, respectively, the CO2 separation fraction was higher than 90%, and the CH4 loss rate was less than 5%.

  4. The results of this study can be applied in practical engineering applications.


ACKNOWLEDGMENTS


This work was supported by Department of Science & Technology of Shandong Province (No. ZR2018LB025).



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