A construction method of a coalbed methane enrichment model based on Aspen adsorption

Abstract

The present invention provides a method for constructing a coalbed methane concentration model based on Aspen adsorption, including the establishment of a coalbed methane concentration adsorption bed equilibrium model, such as the establishment of a thermodynamic model for adsorbing coalbed methane and a micropore & macropore diffusion kinetics model; the establishment of an adsorption bed model for coalbed methane concentration; the solution of the coalbed methane concentration model and the optimization of the coalbed methane concentration process. By means of the custom function feature in Aspen software, the present invention establishes a micropore & macropore diffusion mass transfer model, which makes up for the disadvantage that there is a certain error between the solution result of the lumped resistance mass transfer model default in the system and the experimental value; it can obtain data such as the gas phase concentration and solid phase loading distribution in the adsorption bed layer at any time, which are difficult to directly measure through experiments. In addition, the shape factor of the material is considered during modeling, so as to obtain a more accurate coalbed methane concentration model that is more in line with the actual test results. A model for accurately predicting the coalbed methane concentration process is established, laying a theoretical foundation for the optimized design of the adsorption fixed bed reactor.

Description

Technical Field

[0001] The present invention belongs to the technical field of low-concentration coalbed methane enrichment, and particularly relates to a method for constructing a coalbed methane enrichment model based on Aspen adsorption. Background Art

[0002] Coalbed methane is a gas resource associated with and coexisting with coal, referring to hydrocarbon gases stored in coal seams and belonging to unconventional natural gas. Taking the coalbed methane extracted from underground as the main part, most of the low-concentration coalbed methane is discharged into the atmosphere. Methane among it is an important clean energy source, and directly discharging this high-calorie carbon energy source is a huge waste. In addition, methane also causes great damage to the ecological environment, and its greenhouse effect is about 21 times that of carbon dioxide. At present, the main reason for the low utilization rate of coalbed methane in coal mining enterprises is that low-concentration coalbed methane is difficult to be directly utilized, and there is an urgent need for coalbed methane concentration technology to realize the enrichment of methane in low-concentration coalbed methane. Currently, mainly cryogenic distillation separation technology, membrane separation technology, pressure swing adsorption separation technology, etc. can be used for the enrichment of low-concentration coalbed methane.

[0003] Adsorption technology is a newly emerging gas separation technology in industry in recent years. Due to its advantages such as low equipment cost, simple operation, low running energy consumption, and flexible scale adjustment, it has great development prospects, and has been applied in the fields of hydrogen recovery and purification, air separation, etc., and is considered to be the most likely industrial gas separation technology to realize coalbed methane concentration.

[0004] Starting from the enrichment of low-concentration coalbed methane, some inventors have explored in the material field and tried to innovate from the perspective of low-concentration coalbed methane adsorption materials. For example, in the patent document CN107400542A, the low-concentration coalbed methane adsorption method and the hydrate method are combined to obtain an innovative porous graphite nanofluid through mechanical stirring and ultrasonic dispersion, which can significantly improve the utilization efficiency of coalbed methane. By increasing the gas-liquid contact area, strengthening the adsorption of methane in coalbed methane, enhancing the heat and mass transfer in the coalbed methane purification process, and promoting the formation of gas hydrates, the gas storage rate of methane in the hydrate phase is greatly increased, and the recovery rate and separation efficiency of methane (CH4) are improved. The patent document CN108057420A proposes a preparation method of a coconut shell charcoal adsorbent for the purification of low-concentration coalbed methane. The fruit shell-based activated carbon obtained through the three-step process of carbonization - shaping - carbonization has the advantages of low pressure drop, high strength, and regular shape. It is more practical in the pressure swing adsorption working conditions with large gas flow and high pressure difference. In the patent document CN109179415A, methane deposition agent is deposited on coal-based activated carbon to obtain coal-based carbon molecular sieve. This material has a high nitrogen adsorption capacity and a low methane adsorption capacity, which is beneficial to the kinetic separation of nitrogen and methane. The patent document CN113041998A uses polystyrene and polyamide as raw materials to prepare an anti-static carbon molecular sieve with a resistance of 1500 - 50000Ω through methods such as carbonization - shaping - carbonization - activation - deposition. The preparation method has the advantages of low raw material cost and high material strength, and largely avoids the generation of static electricity during the pressure swing adsorption process, effectively preventing accidents such as deflagration. However, the technical solutions disclosed in the above patent documents are only innovations in the material synthesis perspective and do not evaluate the performance of the materials in the actual adsorption and enrichment process. Such technical solutions will face great challenges in the actual production process because the excessive pursuit of high-separation-performance materials is likely to lead to a wrong understanding of the process. Although the material capture ability increases, the process energy consumption also increases greatly, resulting in an increase rather than a decrease in production costs.

[0005] The patent document CN114214096A proposes a method for concentrating and separating ultra-low-concentration coalbed methane. Through two-stage pressure swing adsorption and using only one type of carbon molecular sieve, the removal of oxygen and the concentration of methane in coalbed methane can be achieved. The patent document CN114317052A proposes a method for efficiently separating and purifying low-concentration coalbed methane. The raw material first removes most of the nitrogen and oxygen through evacuated pressure swing adsorption, and then purifies methane through displacement pressure swing adsorption. The patent document CN110860184A discloses a six-column process. Through the cyclic operation of three groups of adsorption columns, the system pressure fluctuation is stabilized, solving the pressure fluctuation problems at the fan outlet and the vacuum pump. At the same time, it also has characteristics such as low energy consumption, low noise, small vibration, and high recovery rate. However, the technical solutions disclosed in the above patent documents are only discussions on the results under certain fixed materials and fixed conditions. If the materials and test conditions are changed, a large amount of experimental data support is required, and a large amount of resources and time are needed.

[0006] Pressure swing adsorption is a periodic dynamic separation process, which is suitable for evaluating the actual application effect of adsorbents. Considering that a large amount of resources and time are required for real pressure swing adsorption experiments, process simulation is a powerful tool for optimizing energy requirements and process performance and reducing the required experimental work.

[0007] The basis of the simulation study of the adsorption process is the selection and establishment of the adsorption mechanism model and the mathematical model. Their selection fundamentally determines whether the simulation results are reliable.

[0008] According to the basic principles of adsorption, its mass transfer rate model and two-phase equilibrium model are determined. The mass transfer model and the equilibrium model are coupled with the adsorption bed model to obtain the adsorption fixed bed model to reflect the gas-solid two-phase mass transfer, realizing accurate simulation and optimization of the adsorption process. The lumped resistance model given by Aspen adsorption is an idealized model, which does not conform to the actual situation. If this model is simply adopted, it will lead to inconsistent simulation results with actual tests, reducing the accuracy and credibility of the model.

[0009] In summary, there is a need to propose an optimized simulation model for the coalbed methane concentration process to make reliable predictions for the experimental results under different materials and different test conditions. Summary of the Invention

[0010] In view of the prior art, the present invention provides a method for constructing a coalbed methane concentration model based on Aspen adsorption. By means of the custom function feature in Aspen software, a micropore & macropore diffusion mass transfer model is established, which makes up for the drawback that there is a certain error between the solution result of the lumped resistance mass transfer model default in the system and the experimental value. In addition, the molecular transport dynamics in porous media is directly related to pore geometry, tortuosity, connectivity, etc. For different micro-morphology materials (spherical, flaky, fibrous, etc.), the shape factor of the material is considered during modeling, so as to obtain a more accurate coalbed methane concentration model that is more in line with the actual test results.

[0011] A method for constructing a coalbed methane concentration model based on Aspen adsorption proposed by the present invention mainly includes the establishment of a coalbed methane concentration adsorption bed equilibrium model such as the thermodynamics of adsorbed coalbed methane, a micropore & macropore diffusion kinetics model, and an adsorption bed model; constructing a fixed bed model for adsorbing coalbed methane with activated carbon of different micro-morphologies. By comparing the solution results using the lumped resistance model, it is confirmed that the change of the outlet gas concentration during the adsorption process solved by the micropore & macropore diffusion mass transfer model is more consistent with the measured value, and at the same time, data such as the gas phase concentration and solid phase loading distribution in the adsorption bed, which are difficult to directly measure experimentally, can be obtained.

[0012] The specific steps are as follows:

[0013] Step 1: Establishment of the coalbed methane concentration adsorption bed equilibrium model

[0014] ① First, make some assumptions for the model, including: the adsorbent material is uniformly filled in the adsorption bed and its physical properties are constant; the gas to be adsorbed is an ideal gas; the gas flow through the adsorbent material area is laminar;

[0015] ② Use Aspen adsorption to perform numerical simulation on the coalbed methane concentration model, and establish the mass conservation equation, momentum conservation equation, and energy conservation equation:

[0016] Mass conservation equation:

[0017] The overall mass balance of the multi-component gas phase and solid phase is given by the following formula:

[0018]

[0019] Mass balance of each component in the gas phase:

[0020]

[0021] In the above formula: ρ g is the gas density, kg / m 3 ; v g is the apparent gas velocity, m / s; z is the axial coordinate, m; ρs is the adsorbent density, kg / m 3 ; w k is the adsorption capacity, kmol / kg; t is the time, s; ε i is the bed void fraction; E z，k is the axial dispersion coefficient; E r，k is the radial dispersion coefficient; c k is the molar concentration of component k, kmol / m 3 ; r is the radial coordinate, m; J k is the adsorption mass transfer rate;

[0022] The adsorption mass transfer rate is expressed by the micropore & macropore diffusion model as follows:

[0023]

[0024]

[0025] In the formula is the total gas-phase equilibrium adsorption capacity, kmol / kg; is the macropore gas-phase equilibrium adsorption capacity, kmol / kg; K mic is the micropore mass transfer coefficient, K mac is the macropore mass transfer coefficient, and the calculation formula is:

[0026]

[0027]

[0028] In the formula D efc is the micropore diffusion coefficient; D efp is the macropore diffusion coefficient; r c is the particle radius, m; r p is the pellet radius, m; The relationship between the adsorption capacity and the micropore diffusion coefficient is obtained through Fick's law:

[0029]

[0030] In the formula, is the equilibrium adsorption capacity, kmol / kg, and the adsorption equilibrium model is as follows:

[0031]

[0032] In the formula, P k is the partial pressure of component k, bar; IP1, IP2 are the adsorption constants of the adsorption model; i is the number of components;

[0033] Momentum conservation equation:

[0034]

[0035] In the formula, r p is the particle radius, m; ψ is the particle shape factor; μ is the kinematic viscosity, Ns / m 2 ; M is the molecular mass, kg / kmol;

[0036] Energy conservation equation:

[0037] Gas-phase energy balance equation:

[0038]

[0039] Solid-phase energy balance equation:

[0040]

[0041] In the formula, k ga is the axial gas-phase thermal conductivity, MW / m / K; k sa is the axial solid-phase thermal conductivity, MW / m / K; k sr is the radial solid-phase thermal conductivity, MW / m / K; T g is the gas-phase temperature, K; T s is the solid-phase temperature, K; C vg is the specific heat capacity of the gas mixture at constant volume, MJ / kmol / K; HTC is the gas-solid heat transfer coefficient, MJ / m 2 / s; a p is the particle specific surface area, m 2 / m 3 ; H w is the heat transfer coefficient between the gas and the wall, MJ / m 2 / s; D B is the diameter of the adsorption bed body, m; α Hx is the specific surface area of the heat exchanger, m 2 / m 3 ; Q Hx is the heat transfer rate of the internal heat exchanger, MJ / m 2 / s;

[0042] Step 2. Establishment of the adsorption bed model for CBM enrichment (methane adsorption)

[0043] Set the basic parameters of the adsorption bed, including the bed height H, the bed diameter d, and the bed porosity ε i and the adsorbent porosity ε p , and established the adsorption bed model;

[0044] Step 3. Solution of the CBM enrichment model, including:

[0045] ① Set the initial conditions and boundary conditions of the adsorption process;

[0046] Give the gas components, temperature, and pressure inside the adsorption bed at the start of the simulation;

[0047] ② Set the boundary conditions of the adsorption bed:

[0048] Set the feed flow rate at the gas inlet to be fixed, and give the temperature, pressure, and gas composition;

[0049] Set the gas pressure at the gas outlet to be fixed, and give the flow rate, temperature, and gas composition;

[0050] ③ Numerically solve the process of concentrating coalbed methane;

[0051] Aspen solves by discretizing the governing equations, and the changes of pressure, gas composition, and adsorption amount inside the adsorption bed during the adsorption process with respect to time and distance can be obtained;

[0052] The governing equations include the mass, momentum, and energy conservation equations, and these equations are discretized by the first-order upwind scheme;

[0053] The time step of the solution process is set to 1 s. During the solution process, ensure that the tolerance of each parameter in the model is within 10 -7 below, and the operation process is continuous without breakpoints in the middle, then the simulation results of the coalbed methane concentration process are considered valid:

[0054] Step Four: Optimize the coalbed methane concentration process

[0055] After an adsorption process ends, according to the adsorption results, return to Step Three to adjust the initial conditions or boundary conditions, so as to find the optimal adsorption conditions for the corresponding adsorption bed.

[0056] Preferably, the calculation formula for the particle shape factor in Step One is as follows:

[0057]

[0058] In the formula, V p is the particle volume, m 3 , S p is the particle surface area, m 2 .

[0059] Compared with the prior art, the advantages of the optimization method of the present invention are:

[0060] (1) By using the process simulation tool, data such as the gas phase concentration and solid phase loading distribution inside the adsorption bed at any time, which are difficult to directly measure through experiments, can be obtained. When there is a lack of empirical correlation formulas and experimental data, it will be very difficult to solve engineering problems and optimize the design, while the use of process simulation technology can achieve it well.

[0061] (2)During the actual adsorption experiment process, data such as the variation trends of many parameters cannot be obtained intuitively. Through the simulation of the coalbed methane concentration enrichment process, adsorption waves, concentration waves, etc. in the adsorption container can be obtained, which is convenient for energy efficiency analysis.

[0062] (3)Regarding the problem that there is a certain error between the solution results of the lumped resistance model given by Aspen adsorption and the experimental values, by introducing the gas diffusion equation, the separation process using the adsorption fixed bed model is further optimized.

[0063] (4)Establish a model that can accurately predict the coalbed methane concentration enrichment process, laying a theoretical foundation for the optimal design of the adsorption fixed bed reactor. The simple operation process and accurate simulation results greatly reduce the time cost and economic cost of process optimization. Description of the Drawings

[0064] Figure 1 Flow chart of the coalbed methane concentration enrichment process model.

[0065] Figure 2 Comparison and verification of simulation results and experimental results: Comparison of experimental values and simulation curves of the outlet concentration changes under different pressures for two mass transfer models, where a is 1 bar, b is 3 bar, and c is 5 bar.

[0066] Figure 3 Distribution diagram of the gas-phase methane concentration in the adsorption bed at different times.

[0067] Figure 4 Distribution diagram of the gas-phase nitrogen concentration in the adsorption bed at different times.

[0068] Figure 5 Distribution diagram of the methane loading in the adsorption bed at different time points. Detailed Implementation Modes

[0069] The technical solution of the present invention will be further described in detail below in conjunction with the drawings and specific embodiments. The specific embodiments described are only for explaining the present invention and are not intended to limit the present invention.

[0070] Example 1

[0071] A method for constructing a coalbed methane concentration enrichment model based on Aspen adsorption mainly includes the establishment of a coalbed methane concentration enrichment adsorption fixed bed model and the solution of the coalbed methane concentration enrichment model. The flow chart is shown in Figure 1 .

[0072] Specifically as follows:

[0073] Step 1: Establishment of the coalbed methane concentration enrichment adsorption bed equilibrium model

[0074] ① First, make partial assumptions about the model, and set: The adsorbent material is uniformly filled in the adsorption bed and its physical properties are constant; The gas to be adsorbed is an ideal gas; The gas flow through the adsorbent material area is laminar;

[0075] ② Use Aspen adsorption to conduct numerical simulation on the coalbed methane concentration model, and establish the mass conservation equation, momentum conservation equation and energy conservation equation:

[0076] Mass conservation equation:

[0077] The overall mass balance of the multi-component gas-solid phase is given by the following formula:

[0078]

[0079] Mass balance of each component in the gas phase:

[0080]

[0081] In the above formula: ρ g is the gas density, kg / m3; v g is the apparent gas velocity, m / s; z is the axial coordinate, m; ρ s is the adsorbent density, kg / m3; w k is the adsorption capacity, kmol / kg; t is the time, s; ε i is the bed void fraction; E z，k is the axial dispersion coefficient; E r，k is the radial dispersion coefficient; c k is the molar concentration of component k, kmol / m 3 ; r is the radial coordinate, m; J k is the adsorption mass transfer rate;

[0082] The adsorption mass transfer rate is expressed by the micropore & macropore diffusion model as follows:

[0083]

[0084]

[0085] In the formula is the overall gas phase equilibrium adsorption capacity, kmol / kg; is the macropore gas phase equilibrium adsorption capacity, kmol / kg; K mic is the micropore mass transfer coefficient, K mac is the macropore mass transfer coefficient, and its calculation formula is:

[0086]

[0087]

[0088] where D efc is the micropore diffusion coefficient; D efp is the macropore diffusion coefficient; r c is the particle radius, m; r p is the pellet radius, m; The relationship between the adsorption amount and the micropore diffusion coefficient is obtained from Fick's law:

[0089]

[0090] where is the equilibrium adsorption amount, kmol / kg, and the adsorption equilibrium model is as follows:

[0091]

[0092] where P k is the partial pressure of component k, bar; IP1, IP2 are the adsorption constants of the adsorption model; i is the number of components;

[0093] Momentum conservation equation:

[0094]

[0095] where r p is the pellet radius, m; ψ is the pellet shape factor; μ is the kinematic viscosity, Ns / m 2 ; M is the molecular mass, kg / kmol;

[0096] Pellet shape factor:

[0097]

[0098] where V p is the pellet volume, m 3 , S p is the pellet surface area, m 2 ;

[0099] Energy conservation equation:

[0100] Gas phase energy balance equation:

[0101]

[0102] Solid phase energy balance equation:

[0103]

[0104] where k ga is the axial gas phase thermal conductivity, MW / m / K; k sa is the axial solid phase thermal conductivity, MW / m / K; k sr is the radial solid phase thermal conductivity, MW / m / K; T gis the gas phase temperature, K; T s is the solid phase temperature, K; C vg is the specific heat capacity of the gas mixture at constant volume, MJ / kmol / K; HTC is the gas-solid heat transfer coefficient, MJ / m 2 / s; a p is the particle specific surface area, m 2 / m 3 ; H w is the heat transfer coefficient between the gas and the wall, MJ / m 2 / s; D B is the diameter of the adsorption bed body, m; α Hx is the specific surface area of the heat exchanger, m 2 / m 3 ; Q Hx is the heat transfer rate of the internal heat exchanger, MJ / m 2 / s;

[0105] In the present example scheme, the macropore mass transfer coefficient K mac , the micropore mass transfer coefficient K mic , the bulk density ρ of the adsorbent s , the radius r of the adsorbent particles p , the shape factor ψ of the adsorbent, and the constants IP1 and IP2 of the adsorption equilibrium model need to be given. The macropore mass transfer coefficients of methane and nitrogen are both 1.01 / s, and the micropore mass transfer coefficients are 0.00981 / s and 0.00751 / s respectively; the bulk density of the adsorbent is 330 kg / m 3 ; the radius of the spherical carbon particles of the adsorbent is 0.00028 m, and the shape factor is 1; the adsorption equilibrium constants IP1 of methane and nitrogen are 0.00187 and 0.00049 respectively; the adsorption equilibrium constants IP2 of methane and nitrogen are 0.689 and 0.454 respectively.

[0106] Step 2: Establishment of the adsorption bed model for coalbed methane enrichment

[0107] Set the basic parameters of the adsorption bed, including the bed height H = 0.12 m, the bed diameter d = 0.009 m, and the bed porosity ε i = 0.36, and the porosity ε p of the adsorbent = 0.35, and an adsorption bed model was established;

[0108] Step 3: Solution of the coalbed methane enrichment model, including:

[0109] ① Set the initial conditions and boundary conditions of the adsorption process;

[0110] Give the gas composition, temperature and pressure in the adsorption bed at the start of the simulation; the temperature of the adsorption bed layer at the initial moment is 298 K, 1.01 bar, and the gas in the adsorption bed layer is the purge gas (Ar) before the test;

[0111] ②Set the boundary conditions of the adsorption bed layer:

[0112] Set the feed flow rate at the gas inlet to be fixed, and give the temperature, pressure, and gas composition; the feed flow rate is 2 ml / min, the inlet temperature is 298 K, the pressure is 1.01 bar, and the gas composition is methane: nitrogen = 0.3:0.7 v / v;

[0113] Set the gas pressure at the gas outlet to be fixed, and give the flow rate, temperature, and gas composition; the outlet gas pressure is 1.01 bar, the initial outlet flow rate is 0 ml / min, and the outlet temperature is 298 K; the gas composition is Ar;

[0114] ③Numerical solution of the coalbed methane enrichment process:

[0115] Aspen solves by discretizing the control equations, and the changes of pressure, gas composition, and adsorption amount in the adsorption bed layer with time and distance during the adsorption process can be obtained;

[0116] The control equations include the mass, momentum, and energy conservation equations, and these equations are discretized by the first-order upwind scheme;

[0117] The time step of the solution process is set to 1 s. During the solution process, ensure that the tolerance of each parameter in the model is within 10 -7 below, and the operation process is continuous without breakpoints in the middle. Then, it is considered that the simulation results of the coalbed methane enrichment process are valid. When the operation ends, the comparison between the experimental value of the outlet concentration change and the simulation results (Model 1) of this embodiment is obtained (Table 1, Figure 2 a), the gas-phase methane and nitrogen concentration distributions at each moment in the bed layer ( Figure 3 , Figure 4 ) and the methane loading distribution of the adsorption bed ( Figure 5 ).

[0118] Step Four: Optimize the coalbed methane enrichment process

[0119] After an adsorption process ends, according to the adsorption results, return to Step Three to adjust the initial conditions or boundary conditions, so as to find the optimal adsorption conditions for the corresponding adsorption bed layer.

[0120] Example 2

[0121] The process is the same as the above steps, but the adsorption pressures are adjusted to 3 bar and 5 bar respectively. The simulation results are shown in Table 1 and Figure 2 b and Figure 2 c.

[0122] Example 3

[0123] The adsorbent is replaced with porous carbon fiber, and the shape factor is 0.1. The other conditions are the same as in Example 1. The simulation results are shown in Table 2.

[0124] Example 4

[0125] The adsorbent was replaced with a porous carbon block, and the shape factor was 0.8. Other conditions were the same as in Example 1. The simulation results are shown in Table 2.

[0126] A fixed-bed model for the adsorption of CH4 by activated carbon was constructed. The lumped resistance model was selected for the adsorption kinetics, and the remaining steps were the same as those in the embodiments of the present invention. Comparing the solution results using the lumped resistance model (Model 2), the changes in the outlet methane and nitrogen concentrations during the adsorption process obtained by solving with the micropore & macropore diffusion mass transfer model (Model 1) were more consistent with the measured values (see Figure 2 , Table 1, Table 2), which confirmed that the adsorption fixed-bed model considering pore diffusion could predict the actual results more accurately. The constructed fixed-bed model considered the shape factor of the adsorbent and could well predict the dynamic separation results and was applicable to adsorbents with different morphologies.

[0127] Table 1 Correlation Coefficient between Simulation Results and Experimental Results of Example 1

[0128]

[0129] Table 2 Correlation Coefficient between Simulation Results and Experimental Results of Examples 1, 3, and 4

[0130]

[0131] Although the present invention has been described above in conjunction with the accompanying drawings, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many variations without departing from the purpose of the present invention, and all of these fall within the protection scope of the present invention.

Claims

1. A method for constructing a coalbed methane enrichment model based on Aspen adsorption, characterized in that: It includes the following steps: Step 1: Establishment of the equilibrium model of the coalbed methane enrichment adsorption bed ① First, make some assumptions about the model, including: the adsorbent material is uniformly filled in the adsorption bed and its physical properties are constant; the gas to be adsorbed is an ideal gas; the gas flow through the adsorbent material area is laminar flow; ② Use Aspen adsorption to perform numerical simulation on the coalbed methane enrichment model, and establish the mass conservation equation, momentum conservation equation and energy conservation equation: Mass conservation equation: Overall mass balance of multi-component gas-solid phase: Mass balance of each component in the gas phase: In the above formula: ρ g is the gas density, kg / m 3 ; v g is the superficial gas velocity, m / s; z is the axial coordinate, m; ρ s is the adsorbent density, kg / m 3 ; w k is the adsorption capacity, kmol / kg; t is the time, s; ε i is the void fraction of the bed; E z，k axial dispersion coefficient; E r，k radial dispersion coefficient; c k is the molar concentration of component k, kmol / m 3 ; r is the radial coordinate, m; J k is the adsorption mass transfer rate; The adsorption mass transfer rate is expressed by the micropore & macropore diffusion model as follows: where is the total gas-phase equilibrium adsorption capacity, kmol / kg; is the macropore gas-phase equilibrium adsorption capacity, kmol / kg; K mic is the micropore mass transfer coefficient, K mac is the macropore mass transfer coefficient, and the calculation formula is: where D efc is the micropore diffusion coefficient; D efp is the macropore diffusion coefficient; r c is the particle radius, m; r p is the grain radius, m; the relationship between the adsorption capacity and the micropore diffusion coefficient is obtained by Fick's law: In the formula, is the equilibrium adsorption capacity, in kmol / kg, and the adsorption equilibrium model is as follows: where P k is the partial pressure of component k, bar; IP1, IP2 are the adsorption constants of the adsorption model; i is the number of components; Momentum conservation equation: where r p is the particle radius, m; ψ is the particle shape factor; μ is the kinematic viscosity, Ns / m 2 ; M is the molecular mass, kg / kmol; Energy conservation equation: Gas phase energy balance equation: Solid phase energy balance equation: where k ga is the axial gas-phase thermal conductivity, MW / m / K; k sa is the axial solid-phase thermal conductivity, MW / m / K; k sr is the radial solid-phase thermal conductivity, MW / m / K; T g is the gas-phase temperature, K; T s is the solid-phase temperature, K; C vg is the specific heat capacity of the gas mixture at constant volume, MJ / kmol / K; HTC is the gas-solid heat transfer coefficient, MJ / m 2 / s; a p is the specific surface area of the particles, m 2 / m 3 ; H w is the heat transfer coefficient between the gas and the wall, MJ / m 2 / s; D B is the diameter of the adsorption bed, m; α Hx is the specific surface area of the heat exchanger, m 2 / m 3 ; Q Hx is the heat transfer rate of the internal heat exchanger, MJ / m 2 / s; Step 2: Establishment of the adsorption bed model for coalbed methane enrichment Set the basic parameters of the adsorption bed, including the bed height H, the bed diameter d, and the bed porosity ε i and the adsorbent porosity ε p , and an adsorption bed model was established; Step 3: Solution of the coalbed methane enrichment model, including: ① Set the initial conditions and boundary conditions of the adsorption process; Give the gas components, temperature and pressure in the adsorption bed layer at the beginning of the simulation; ② Set the boundary conditions of the adsorption bed layer: Set the feed flow rate at the gas inlet to be fixed, and give the temperature, pressure and gas composition; Set the gas pressure at the gas outlet to be fixed, and give the flow rate, temperature and gas composition; ③ Perform numerical solution for the coalbed methane enrichment process; Aspen solves by discretizing the control equations, and the changes of pressure, gas composition and adsorption amount in the adsorption bed layer with time and distance during the adsorption process can be obtained; The control equations include the mass, momentum and energy conservation equations, and these equations are discretized by the first-order upwind scheme; The time step of the solution process is set to 1 s. During the solution process, it is ensured that the tolerances of all parameters in the model are within 10 -7 below, and the running process is continuous without breakpoints in the middle. Then, the simulation results of the coalbed methane enrichment process are considered valid: Step 4: Optimize the coalbed methane enrichment process After an adsorption process is completed, according to the adsorption results, return to Step 3 to adjust the initial conditions or boundary conditions, so as to find the optimal adsorption conditions for the corresponding adsorption bed layer.

2. The construction method of a coalbed methane enrichment model based on Aspen adsorption according to claim 1, characterized in that: The calculation formula of the particle shape factor in Step 1 is as follows: Where, V p is the particle volume, m 3 , S p is the particle surface area, m 2 .

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