Acid Gas Extraction for Disposal and Related Topics

By Ying Wu and John J. Carroll

This is the fifth volume in a series of books focusing on natural gas engineering, focusing on the extraction and disposal of acid gas. This volume includes information for both upstream and downstream operations, including chapters on modeling, carbon capture, chemical and thermodynamic models, and much more.

Written by some of the most well-known and respected chemical and process engineers working with natural gas today, the chapters in this important volume represent the most cutting-edge and state-of-the-art processes and operations being used in the field. Not available anywhere else, this volume is a must-have for any chemical engineer, chemist, or process engineer working with natural gas.

There are updates of new technologies in other related areas of natural gas, in addition to the extraction and disposal of acid gas, including testing, reservoir simulations, acid gas injection, and natural gas hydrate formations.  Advances in Natural Gas Engineering is an ongoing series of books meant to form the basis for the working library of any engineer working in natural gas today. Every volume is a must-have for any engineer or library.

• Language: English
• Publisher: Wiley
• Release date: Feb 2, 2016
• ISBN: 9781118938621

Book preview

Preface

The fifth in the series of Symposia on the injection of gases for disposal and enhanced recovery was held in Banff, Canada, in May 2015. This volume contains select papers that were presented at the Symposium. In addition, some papers were backups and they too are included here.

The keynote presentation, and Chapter 1 in this book, was on the modelling of processes for removing CO2 from gas streams. This is followed by several chapters on acid gas removal technology, including data and correlation. This includes several interesting papers on hydrates.

The final chapters discuss the reservoir aspects of gas injection. Included in these sections are papers on acid gas injection and CO2 for enhanced oil recovery.

YW, JJC, & WZ

May 2015

Chapter 1

Rate-Base Simulations of Absorption Processes; Fata Morgana or Panacea?

P.J.G. Huttenhuis and G.F. Versteeg

Procede Gas Treating BV, Enschede, The Netherlands

Abstract

The design and simulation of separation processes have been traditionally handled using the concept of ideal stages and efficiencies. The growing importance of chemically based separation processes, such as the use of alkanolamines for gas processing and now carbon capture underline the importance of proper modeling of coupled mass transfer and chemical kinetics in multiphase systems.

In the present study it will be demonstrated by means of various (real-life) cases that rate-based simulation can be a beautiful tool to improve on the process performance and develop new insights in gas-liquid processes accompanied by complex chemical reactions. But also in this rate-based approach the user should fully understand the mechanisms behind the phenomena occurring. Otherwise, this approach can lead to erroneous results.

1.1 Introduction

The design of absorption processes based on complex aqueous chemical reactions such as CO2-capture, selective H2S-removal as well as rate limited physical separations like LNG pre-treatment are neither simple nor straightforward. Reaction kinetics, mass transfer rates and thermodynamics are coupled and their effects must be taken into account simultaneously. The development of sound simulation models is dependent on algorithms, which take into account the aforementioned phenomena in a rigorous and consistent manner.

How the mass transfer parameters collectively affect the results, is an important part of the training required by a process engineer to become proficient in using this type of technology.

In this paper a high pressure CO2 capture case is simulated with a rate based simulator. The impact of the several mass transfer parameters on the absorption performance is presented and it is shown that knowledge of these parameters is required to obtain reliable and correct results from the simulator.

1.2 Procede Process Simulator (PPS)

The simulations described in this paper have been carried out with the Procede Process Simulator. Procede Process Simulations developed a new flowsheeting tool, Procede Process Simulator (PPS), specifically designed for steady-state simulations of acid gas treating processes [1]. The process models include all features relevant for the design, optimization, and analysis of acid gas treating processes, like selective H2S removal, post combustion CO2 capture or CO2 removal with a physical solvent. The simulator consists of a user-friendly graphical user interface and a powerful numerical solver that handles the rigorous simultaneous solution of thermodynamics, kinetics and mass transfer equations (this combination usually called a rate-based model). PPS also supports the main unit operations relevant for gas treating plants like absorbers, strippers, flash drums, heaters, pumps, compressors, mixers and splitters as well, as novel unit operations designed to make the process engineer’s work more productive such as automatic ways to calculate water and solvent makeup. PPS has been extensively validated and used for several carbon capture projects [2–4]. A thorough and systematic comparison between the equilibrium based and rate based modeling approaches using the absorption of CO2 from flue gas produced by a coal-fired power plant into an aqueous MEA solution as a benchmark was presented in [5].

The Procede Process Simulator includes an extensive, carefully evaluated database of thermodynamic model parameters, binary interaction parameters, kinetics constants, chemical equilibrium constants, diffusivities and other required physical properties. The physical property model parameters were optimized to accurately predict the vapour-liquid equilibria (VLE), thermodynamic and physical properties, and the kinetically enhanced mass transfer behavior of acid gases in amine-based capturing processes. Several models for hydrodynamics and mass transfer such as the Higbie penetration model [6] are available.

The thermodynamic model combines consistent liquid activity coefficient models derived from a Gibbs excess function with the necessary modifications to handle ions in aqueous solutions with a cubic equation of state for the gas phase. For the convenient prediction of column performance, the program also includes an extensive database of various tray types as well as a large collection of both random and structured packing data. Several mass transfer (kG, kL and a) and hydrodynamic models were implemented that benefit from accurate physical property models for density, viscosity, surface tension, diffusivity and thermal conductivity specifically selected and validated for acid gas treating applications.

This attention to detail allowed for the construction of a simulator able to describe complete acid gas treating processes, including complex processes with multiple (mixed or hybrid) solvent loops. This simulator provides significant understanding of the performance of potential new solvents, current operations and an environment to better understand current operations.

1.3 Mass Transfer Fundamentals

Most important part of the Procede Process Simulator is the mass transfer module. In this module the mass transfer from gas phase to liquid phase and vice versa is calculated.

In the example described below gaseous component A (=CO2) is transported to the liquid phase (B), were the reaction takes place.

(1.1) equation

The reaction rate can be calculated from the reaction rate constant k1,1 and the concentration A and B in the liquid phase:

(1.2) equation

where: ri = reaction rate of component i

            k1,1 = the kinetic rate constant of the reaction between A and B

            Ci = concentration of component i

A commonly used fundamental mass transfer model to describe this absorption process quantitatively is the stagnant film model. In this stagnant film model the fluid (in this case both gas and liquid phase) are divided in two different zones: a stagnant film of thickness δ (gas and liquid) near the interface and a well-mixed bulk (gas and liquid) behind it, in which no concentration gradients occur. A schematic representation of the absorption process according the stagnant film model is presented in Figure 1.1.

Figure 1.1 Driving force for a gas – liquid process according to the film model.

In Figure 1.1 the parameters (according the film model) for the driving force in a countercurrent gas-liquid system with and without chemical reaction are shown:

Gas and liquid resistances are determined by the diffusion coefficients and the film thickness in both phases. In the film model it is assumed that equilibrium exists at the gas-liquid interface. For an acid gas – solvent system, where a chemical reaction takes place in the liquid, mass transfer in the liquid may be enhanced by the chemical reaction as can be seen in Figure 1.1.

Depending on the values of the stated variables in the reaction rate equations, several limiting conditions can be identified. If one assumes a negligible gas phase resistance (high kG; in most CO2 capture absorption processes kG is not limiting) the following absorption rate for component A (=CO2) can be developed:

(1.3) equation

where: rA = absorption rate of component A [mol. s−1.m−3 reactor]

            mA = physical solubility of component A in the solvent, -

            kL = liquid side mass transfer coefficient, m.s−1

            a = effective gas-liquid area, m².m−3 reactor

            E = chemical enhancement factor, -

            CA,G = concentration of component A in gas phase, mol.m−3

E is the enhancement factor, which is the ratio of the flux with reaction and the flux without reaction at identical driving forces. For non-reactive systems the enhancement factor is by definition equal to one. To calculate the CO2 flux, the chemical enhancement should be determined and for this calculation the definition of the Hatta number (Ha) is introduced. The dimensionless number Hatta number compares the maximum chemical conversion in the mass transfer film to the maximum diffusion flux through the film. For the example described above, the Hatta number is defined as follows:

(1.4) equation

where: k1,1 = the reaction rate constant;

            CB = concentration of reactant (=B) in the liquid phase;

            DA = diffusion coefficient of component A in the solvent;

            kL = liquid side mass transfer coefficient.

Dependent of the value of the Hatta number the several reaction regimes can be identified. For CO2 capture at low pressure in general the pseudo first order regime can be identified (Ha >> 2) and in this case the Enhancement factor (E) is equal to the Hatta number. In this case the absorption rate can be calculated as follows:

(1.5)

equation

So when thermodynamic (m), kinetic (k1,1) and mass transfer information (a) and physical properties (D) are available the absorption rate of CO2 into the liquid phase can be determined. Under these conditions, the mass transfer of CO2 is independent of the liquid side mass transfer coefficient kL.

In this case the reaction between CO2 and the solvent takes place at the gas liquid interface and in the bulk of the liquid no CO2 is present anymore; i.e. it is converted to ionic species completely.

In PPS the Higbie penetration model is used to calculate the mass transfer instead of the above described film model. In contrast to the above described film model the Higbie Penetration Model can be used for a wide range of conditions, the entire range of Hatta numbers, (semi-) batch reactors, multiple complex reactions and equilibrium reactions, components with different diffusion coefficients and also for systems with more than one gas phase component. However, the principles as discussed above are identical.

For rate based modelling of absorbers and regenerators the contactor is discretized into a series of mass transfer units as shown in Figure 1.2. In counter-current operation the input of each transfer unit is the liquid from above and the vapour from below the unit. The output is the liquid to the unit below and the vapour to the unit above. The resulting number of transfer units (NTU) and the physical appearance (e.g. sieve trays, random packing, etc.) of these units are completely different depending on the way the model is constructed. Nevertheless the model is completely general in the sense that it captures all the essential phenomena happening in reality – thermodynamic driving forces, effective areas and rates for mass transfer, chemical kinetics and limited residence time.

Figure 1.2 General mass transfer model for vapours and liquids.

In rate based modelling the gas and liquid phases are separated by an interface, the gas and liquid phases have different temperatures and the mass and heat transfer rates between the two phases are determined by the driving force between the two phases, the contact area, and the mass and heat transfer coefficients. The amount of mass transfer area is determined by the desired quality of the separation. The mole fractions of the gas (y) and liquid (x) phase are calculated by integration of the differential mass balance equations (1) and (2) across the height of the column (h).

(1.6) equation

(1.7) equation

where L is the total mole flow of the liquid phase and G is the total mole flow of the gas phase, i is the component index. V is the total volume of the segment. The effective interfacial area for mass transfer (ae) depends on the packing type or other mass transfer area present in the contactor such as the specific area for mass transfer used to model tray columns or bubble interfacial area present in a bubble tower. The mass flux (J) in moles /(area * time) is calculated based on the driving force. If the driving force is defined as the concentration difference between the gas and liquid phase the flux is expressed as in Eqn 1.8.

(1.8) equation

where m is the distribution coefficient based on the ratio of liquid and gas concentrations. If the integration of this set of equations is done numerically the height of one transfer unit depends on the numerical discretization used for integration. In the case of a packed column, with negligible axial dispersion, the NTU is set at a value that results in plug flow. In case of trays, with the assumption that at each tray the liquid and gas phase are ideally mixed, the NTU can be set equal to the number of trays. This results in less plug flow due to axial dispersion. It should be noticed that in this way the axial dispersion is described by ideally mixed contactors in series.

In case of chemical absorption and the driving force is concentration based, the overall mass transfer coefficient kov is a function of the mass transfer coefficient of the gas phase (kG) and liquid phase (kL), the distribution coefficient based on concentrations (m). E is the enhancement factor as discussed before.

(1.9) equation

Details related to the construction of empirically determined mass transfer parameters are important since the interactions between their different governing equations and equation parameters are not always intuitive. For example, in physical separation processes only the product of mass transfer coefficient and specific interfacial area for the gas and liquid mass transfer is required (kGae and kLae), because this product determines the absorption rate. For chemically reactive, mass transfer limited separation processes the individual values of mass transfer coefficients and specific mass transfer areas (kG, kL, ae) are required for the gas and liquid phases. A significant amount of experimental studies related to predict these mass transfer parameters in absorption columns have been carried out. From these studies several empirical or semi-empirical correlations are derived by regression of the correlations with the experimental (pilot) data or correlations are derived from theoretical hydraulic models. In general overall or volumetric mass transfer coefficients are determined from these experiments; however, a distinction between mass transfer coefficient (kL and kG) and effective interfacial area (ae) is basically not possible.

1.4 CO2 Capture Case

A high pressure (60 bar) CO2 capture plant was simulated based on real plant data and the process flow scheme of the simulated plant is presented below:

In Figure 1.3 a flow scheme of a standard CO2 capture plant is presented containing an absorber and desorber, flash vessel and various heat exchangers and solvent circulation pumps. The CO2 is removed with an activated MDEA solution, i.e. a commonly used solvent containing MDEA and piperazine. The absorber is equipped with 20 valve trays. Geometric details of the valves, like weir height and tray spacing have been incorporated in the simulation. The in-house developed correlations have been used to calculate the various mass transfer parameters (kG, kL and ae). The gas stream is a hydrocarbon stream containing mainly methane and 3.0 vol. % CO2. With the default simulation the following mass transfer parameters were calculated using the default correlations implemented in the simulator:

kG = 2.6.10−3 m.s−1

kL = 2.6.10−4 m.s−1

ae= 38 m².m−3

Figure 1.3 Process flow sheet of the simulated CO2 capture plant.

Note that the mass transfer parameters are calculated for every tray, so the above presented data are average values over the whole column.

With these settings a CO2 capture of 75 % was calculated with the simulator. In reality a slightly higher (few percent) capture was measured and by the execution of a sensitivity study with the three mass transfer parameters, it was studied how this capture can be influenced. As described above the physical and chemical properties of the solvent-gas mixture are rigorous implemented into PPS and the most difficult parameters to predict are the mass transfer parameters kG, kL and a.

In Figure 1.4 the influence of the effective interfacial area (ae) on the calculated CO2 outlet concentration is presented. The area has been varied between values of 10% and 500 % of the original number dervied from the default correlation (= 38 m².m−3).

Figure 1.4 Influence of effective interfacial area on the calculated CO2 outlet concentration.

From Figure 1.4 it can be concluded that the CO2 capture rate is very dependent on the value of the effective interfacial area. Especially, a reduction of area does have a drastic effect on the overall CO2 capture. The reason for this large effect is that the CO2 capture is more or less linear dependent on the CO2 absorption in the liquid phase, so lowering the area will result in lower absorption. When the effective area calculated with the default correlation was increased with 22% to 46 m².m−3, the CO2 concentration predicted by the simulator was inline with the capture measured in the field.

An increment in area does result in increased CO2 capture, however, the effect is less pronounced as for reduced effective area. Especially at very high effective areas (> 100 m².m−3), a further increase in area does not result in the same increase in CO2 capture. The reason for this lower impact of area on the capture is, that at these high capture rates, the driving force for mass transfer, i.e. the concentration difference between gas and (corrected) liquid phase is decreasing with increasing CO2 capture. In Figure 1.5 the gas phase concentration and (corrected) liquid phase concentration is presented as function of tray number for the default case (ae = 38 m².m−3). The corrected liquid concentration is the gas phase concentration which is in equilibrium with the liquid phase. The difference between these two lines is the driving force for mass transfer.

Figure 1.5 Gas phase concentration (green triangles) and (corrected) liquid concentration of CO2 (blue dots) as function of tray number for the interfacial area of 38 m².m−3.

From Figure 1.5 it be seen that the gas phase concentration is reduced from around 3 mol% (in the top) to around 0.7 mol% in the bottom of the absorber. It can also be concluded that the driving force is lower in the middle of the column. This can be explained when the temperature profile in the column is studied in more detail. In Figure 1.6 this liquid temperature in the absorber is presented for three different interfacial areas and it can be seen that in the middle of the column the temperature is increased to more than 80 °C (for ae = 38 m².m−3). At this high temperature the equilibrium partial pressure CO2 is much higher than at lower temperature, i.e. the capacity of the solvent for CO2 capture is decreased. Due to this reduced driving force, the CO2 mass transfer from gas to liquid phase will be reduced.

Figure 1.6 Temperature profile in the absorber for three different effective areas (ae = 7.6, 38 and 190 m².m−3; default value multiplied by factor of 0.2, 1 and 5).

When the effective area is decreased with a factor 5 to 7.6 m².m−3 a significant lower CO2 capture is established (refer to Figure 1.4). When the area is increased with a factor 5 to 190 m².m−3, the CO2 capture is increased, however, the increment is significant lower than expected. The reason for this limited increment can be explained when the driving force between gas and liquid phase is studied for this simulation (Figure 1.7).

Figure 1.7 Gasphase concentration (green triangles) and (corrected) liquid concentration of CO2 (blue dots) as function of tray number for the interfacial area of 190 m².m−3 (factor = 5).

From Figure 1.7 it can be concluded that almost no driving force for mass transfer is available in approximately 50 % of the column, i.e. between tray 8 and 15. Due to the high CO2 capture the temperature is increased in the absorber (Figure 1.6) to approximately 85 °C and at this high temperature no absorption can take place anymore, due to the high equilibrium CO2 pressure. From this figure it can be concluded that the addition of more trays (or more interfacial area) will not result in more CO2 capture. The overall CO2 capture can be increased by applying inter stage cooling in the middle of the column or increase the solvent circulation rate.

In Figure 1.8 the influence of the liquid side mass transfer coefficient on the calculated CO2 outlet concentration is presented graphically.

Figure 1.8 Influence of liquid side mass transfer coefficient on the calculated CO2 outlet concentration.

From Figure 1.8 it can be concluded that both for low and for high values of the liquid side mass transfer coefficient, the impact on the CO2 capture is much lower than for the interfacial area. The reason for this relatively low influence is that the reaction does take place in the pseudo first order regime. As discussed in the former chapter, when the reaction is fast compared to mass transfer, the absorption rate is not influenced by the value of the liquid side mass transfer coefficient. In Figure 1.9 the calculated chemical enhancement in the absorber is calculated for three different values for the liquid side mass transfer coefficient (kL = 5.2.10−5, 2.6.10−4 and 1.3.10−3 m.s−1, i.e. the default value is multiplied with respectively a factor 0.2, 1 and 5).

Figure 1.9 Chemical enhancement for three different liquid side mass transfer coefficients (default value multiplied by factor of 0.2, 1 and 5).

From this Figure 1.9 can be seen that for most of the conditions the enhancement >> 1 and for this conditions the absorption rate is not dependent on kL. For the lower values of kL in the bottom of the column, the chemical enhancement is approaching the value 1 and in this case, the CO2 capture becomes dependent on the value of kL.

In Figure 1.10 the temperature profile in the column is presented for the three different kL values. From this figure it can be concluded that this parameter has a low impact on the temperature in the absorber.

Figure 1.10 Temperature profile in the absorber for three different liquid side mass transfer coefficients (default value multiplied by factor of 0.2, 1 and 5).

In Figure 1.11 the influence of the gas side mass transfer coefficient (kG) on the calculated CO2 outlet concentration is presented graphically.

Figure 1.11 Influence of gas side mass transfer coefficient on the calculated CO2 outlet concentration.

From Figure 1.11 it can be concluded that the value of the gas side mass transfer coefficient is not limiting the overall CO2 capture in the range presented in Figure 1.11. The reason for this is that the mass transfer is limited by the resistance in the liquid phase as discussed in the former chapter.

In Figure 1.12 the temperature in the absorber is presented graphically for three different values of kG (kG = 5.2.10−4, 2.6.10−3 and 1.3.10−2 m.s−1, i.e. the default value is multiplied with respectively a factor 0.2, 1 and 5.

Figure 1.12 Temperature profile in the absorber for three different gas side mass transfer coefficients (default value multiplied by factor of 0.2, 1 and 5).

Form Figure 1.12 it can be seen that the value of kG has a huge impact on the temperature profile in the absorber. The CO2 capture for the three different cases is more or less the same, so the different temperature profiles cannot be caused by the increased CO2 capture and related exothermic reaction. The reason for this different temperature profiles is that not only the kG for CO2 is changed, but also the kG for the other components present in the solvent, i.e. water. The value of the kG for water has a large impact on the evaporation of water in the column. The higher the kG value, the more mass transfer of water can take place and this has a large impact on the temperature profile in the absorber.

The default CO2 absorption case as simulated in PPS has been compared with a field test and it appeared that the calculated CO2 capture was 1.8% lower than the field case. To match the CO2 capture calculated by the model with the capture measured in the field, the calculated effective area in the model was increased with 22% (case 1). As discussed before, it is more efficient for this case to fit the effective area than the other mass transfer parameters. With this (slightly) adjusted effective area correlation, three other field cases were calculated (case 2–4) and the comparison between model and field data are presented in Figure 1.13.

Figure 1.13 Comparison between PPS model and field data.

From this figure it can be concluded that the predicted CO2 capture rate by the simulator is rather in line with the field data for all cases.

1.5 Conclusions and Recommendations

In this paper the impact on the various mass transfer parameters (ae, kG, and kL) on the mass transfer parameters is studied with a rate based simulator and compared with a field case. From the simulations described in this work it can be concluded that knowledge of the individual mass transfer parameters is essential to describe the CO2 capture process correctly. The performance of the CO2 capture can be tuned with the individual mass transfer parameters, however, the impact on the overall performance is different for every parameter. If the wrong mass transfer parameter is tuned, extrapolation to other process conditions may lead to erroneous simulation results. In this paper a CO2 capture process is described. In case a H2S capture process is discussed, the results will be completely different, due to the very fast reaction rate between H2S and amines. In case H2S and CO2 are both present in the gas phase the complexity increases significantly and rate based simulation is the only way to make a reliable design. From the simulations described in this paper may be concluded, that rate based simulation is a very powerful tool to describe the complex gas treating processes, however, a sound knowledge of the underlying fundamentals, i.e. the mass transfer parameters, is essential.

References

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