CN117006805A

CN117006805A - Optimization method and device for co-production LNG helium extraction process

Info

Publication number: CN117006805A
Application number: CN202310954083.7A
Authority: CN
Inventors: 吴义平; 尹秀玲; 张晋; 付莉; 曾保全; 孙杜芬; 邹倩
Original assignee: China National Petroleum Corp
Current assignee: China National Petroleum Corp
Priority date: 2023-07-31
Filing date: 2023-07-31
Publication date: 2023-11-07
Anticipated expiration: 2043-07-31
Also published as: CN117006805B

Abstract

The invention provides a method and a device for optimizing a co-production LNG helium extraction process, wherein the method comprises the following steps: establishing a helium extraction process combining LNG membrane separation and a low-temperature method according to the components of the raw gas of the lean helium field to be analyzed, wherein the helium extraction process comprises a helium extraction related device, a material flow and an energy flow; simulating helium extraction processes of different raw material gases by using software, wherein the helium contents of the different raw material gases are different; taking the minimum total energy consumption of the device in the helium extraction process as an optimization target, and establishing a nonlinear regression model of the optimization target and process parameters in the helium extraction process for each raw material gas helium extraction process; and for the nonlinear regression model corresponding to each raw gas, determining the process parameter optimization range of the raw gas by utilizing the nonlinear regression model and the process parameter value range, and completing the optimization of the raw gas process flow. The optimized combined LNG helium extraction process determined herein has the advantage of low energy consumption.

Description

Optimization method and device for co-production LNG helium extraction process

Technical Field

The invention relates to the field of helium extraction process optimization, in particular to a method and a device for optimizing a co-production LNG helium extraction process.

Background

Helium is mainly extracted from helium-rich natural gas, and helium extraction technology includes single helium extraction technology, combined natural gas helium extraction technology and co-production natural gas helium extraction technology. The single helium extraction technology includes a low temperature method for purifying helium by using a cryogenic method and a non-low temperature method mainly comprising a Pressure Swing Adsorption (PSA) method, a membrane separation method, a solvent absorption method and the like. The combined natural gas helium extraction technology is to use a plurality of helium extraction methods in a matching way, thereby improving the helium recovery rate. The technology for co-producing natural gas helium stripping is a method for integrating natural gas helium stripping with units such as liquefied natural gas production, gas denitrification and the like, and other byproducts are produced while helium is obtained, so that the purposes of reducing cost and improving overall benefit are achieved.

In the prior art, the cryogenic method in the single helium extraction technology is mainly adopted for helium extraction, and the method has the problems of high energy consumption and high cost. In the prior art, the membrane separation method is mainly used for coarse helium refining, LNG co-production helium extraction mainly adopts LNG tail gas BOG for helium extraction, and the membrane separation method is not applied to separation of raw material gas helium in a helium-lean field, so that an optimization method for the co-production LNG helium extraction process of the helium-lean field is needed to reduce energy consumption and cost.

Disclosure of Invention

The method is used for solving the problems of high energy consumption and high cost in the helium extraction process of the lean helium gas field in the prior art.

To solve the above technical problems, an aspect herein provides a method for optimizing a co-production LNG helium extraction process, including:

establishing a helium extraction process combining LNG membrane separation and a low-temperature method according to the components of the raw gas of the lean helium field to be analyzed, wherein the helium extraction process comprises a helium extraction related device, a material flow and an energy flow;

simulating helium extraction processes of different raw material gases by using software, wherein the helium contents of the different raw material gases are different;

taking the minimum total energy consumption of the device in the helium extraction process as an optimization target, and establishing a nonlinear regression model of the optimization target and process parameters in the helium extraction process for each raw material gas helium extraction process;

and for the nonlinear regression model corresponding to each raw gas, determining the process parameter optimization range of the raw gas by utilizing the nonlinear regression model and the process parameter value range, and completing the optimization of the raw gas process flow.

Further, optimizing the post helium stripping process for each feed gas further comprises:

calculating the full cycle cost of the device in the helium extraction process after the optimization of the raw material gas;

Calculating the operation cost according to each operation link in the helium extraction process after optimizing the raw material gas;

estimating the income of each product in the helium extraction process after optimizing the raw material gas;

calculating the helium extraction benefit of the co-production LNG according to the full cycle cost, the operation cost and the product income;

the cost of stripping LNG, and the helium extraction incremental benefit of the helium extraction process after optimizing the feed gas are calculated.

and calculating the unit helium extraction cost according to the accumulated output of helium in the helium extraction process after the optimization of the raw material gas, the total periodic investment of the accumulation device and the accumulated operation cost.

Further, the method further comprises the following steps:

and determining a target helium extraction process of the to-be-analyzed helium-depleted gas field according to the helium extraction increment benefit of the helium extraction process after optimizing each feed gas.

Further, according to each operation link in the helium extraction process after the optimization of the raw material gas, the operation cost is calculated, and the method comprises the following steps:

determining the component items of the operation cost and the technical cause of each component item according to each operation link in the helium extraction process after the optimization of the raw material gas;

and calculating the operation cost of the helium extraction process according to the actual treatment scale of each operation link and the technical cause of each constituent of each operation link in the helium extraction process after the optimization of the raw material gas.

Further, estimating the product revenue for the optimized process parameters of the feed gas includes:

predicting helium price by using a nonlinear gray Bernoulli model, wherein parameters in the nonlinear gray Bernoulli model are calculated by using a whale algorithm;

determining the LNG price according to the transportation cost and the factory price;

and calculating the product income under the optimized process parameters according to the predicted helium price, the helium amount obtained by the helium extraction process of the raw material gas, the LNG price and the LNG yield obtained by the helium extraction process of the raw material gas.

A second aspect herein provides a co-production LNG helium extraction process optimization apparatus comprising:

the helium extraction process determining unit is used for establishing a helium extraction process combining LNG membrane separation and a low-temperature method according to the lean helium field raw gas components to be analyzed, wherein the helium extraction process comprises a helium extraction related device, a material flow and an energy flow;

the simulation unit is used for simulating helium extraction processes of different raw gases by using software, wherein helium contents of the different raw gases are different;

the model determining unit is used for establishing a nonlinear regression model of the optimization target and process parameters in the helium extraction process for each raw material gas helium extraction process by taking the minimum total energy consumption in the helium extraction process as the optimization target;

And the process parameter optimization unit is used for determining the process parameter optimization range of the raw material gas by utilizing the nonlinear regression model and the process parameter value range corresponding to each raw material gas so as to finish the optimization of the process flow of the raw material gas.

A third aspect herein provides a computer apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of any of the preceding embodiments when the computer program is executed.

A fourth aspect herein provides a computer storage medium having stored thereon a computer program which, when executed by a processor of a computer device, implements a method as described in any of the previous embodiments.

The optimization method and the device for the combined LNG helium extraction process establish the combined LNG membrane separation and low-temperature process helium extraction process according to the lean helium field raw gas components to be analyzed, wherein the helium extraction process comprises helium extraction related devices, material flows and energy flows; simulating helium extraction processes of different raw material gases by using software, wherein the helium contents of the different raw material gases are different; taking the minimum total energy consumption of the device in the helium extraction process as an optimization target, and establishing a nonlinear regression model of the optimization target and process parameters in the helium extraction process for each raw material gas helium extraction process; and for the nonlinear regression model corresponding to each raw gas, determining the process parameter optimization range of the raw gas by using the nonlinear regression model and the process parameter value range, and completing the optimization of the process flow of the raw gas, so that the energy consumption of the helium extraction process of the helium-depleted gas field can be reduced.

The foregoing and other objects, features and advantages will be apparent from the following more particular description of preferred embodiments, as illustrated in the accompanying drawings.

Drawings

In order to more clearly illustrate the embodiments herein or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments herein and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.

FIG. 1 illustrates a flow chart of a method of optimizing a co-production LNG helium extraction process of embodiments herein;

FIG. 2 shows a schematic diagram of a co-production LNG helium extraction process of embodiments herein;

FIG. 3 illustrates a flow chart of an incremental benefit evaluation method of the co-production LNG helium extraction process after optimization of the embodiments herein;

FIG. 4 illustrates a block diagram of an optimization device for a co-production LNG helium extraction process of an embodiment herein.

FIG. 5 illustrates a block diagram of a computer device of embodiments herein;

fig. 6 shows a flowchart of the whale algorithm of the embodiments herein.

Description of the drawings:

401. a helium extraction process determination unit;

402. A simulation unit;

403. a model determination unit;

404. a process parameter optimizing unit;

405. an incremental benefit evaluation unit;

502. a computer device;

504. a processor;

506. a memory;

508. a driving mechanism;

510. an input/output module;

512. an input device;

514. an output device;

516. a presentation device;

518. a graphical user interface;

520. a network interface;

522. a communication link;

524. a communication bus.

Detailed Description

The following description of the embodiments of the present disclosure will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the disclosure. All other embodiments, based on the embodiments herein, which a person of ordinary skill in the art would obtain without undue burden, are within the scope of protection herein.

It is noted that the terms "comprises" and "comprising," and any variations thereof, in the description and claims herein and in the foregoing figures, are intended to cover a non-exclusive inclusion, such that a process, method, apparatus, article, or device that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or device.

The present specification provides method operational steps as described in the examples or flowcharts, but may include more or fewer operational steps based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one way of performing the order of steps and does not represent a unique order of execution. When a system or apparatus product in practice is executed, it may be executed sequentially or in parallel according to the method shown in the embodiments or the drawings.

The helium is widely applied in the high-tech fields of aerospace, medical treatment and the like, so that the demand of the helium is increased rapidly in China, and the helium is a national scarce strategic resource and plays an important role in national economy. In the prior art, the helium extraction process for the lean helium gas field has the problems of high energy consumption and high cost. Based on this, the optimization method of the co-production LNG helium extraction process comprises the following steps, as shown in fig. 1:

and 101, establishing a helium extraction process combining LNG membrane separation and a low-temperature method according to the components of the raw gas of the lean helium field to be analyzed, wherein the helium extraction process comprises a helium extraction related device, a material flow and an energy flow. The material flow reflects the material balance, the energy flow reflects the energy balance, and the helium extraction process is established according to the material balance and the energy balance.

The method is characterized in that a combined helium extraction flow path suitable for membrane separation and a low-temperature method of a lean helium field is designed according to the requirements of the raw material gas component and the product gas of the lean helium field and with reference to the existing helium extraction technology in actual production, and in some embodiments, the low-temperature method is a low-temperature distillation method.

The process terminal product comprises pipeline commodity gas, LNG and refined helium, the pipeline commodity gas has stronger market competitiveness, the co-production of LNG can reduce helium extraction cost, and the process is suitable for being used and popularized in helium-lean fields. The combined process of membrane separation and low temperature method adopts membrane separation, post expansion, nitrogen circulation refrigeration and at least two towers of low temperature distillation. Helium extraction units are divided into four parts of membrane separation, primary concentration, secondary concentration and nitrogen circulation.

The raw material gas is purified by a membrane separation device, part of the raw material gas is separated by a membrane, the helium concentration is increased by 8-9 times, and part of separated methane is delivered to the pipeline. The purified raw gas enters a raw gas cooler (such as a cold box 1 in fig. 2) for cooling after decarburization and dehydration, and is regulated by a flow regulating valve, part of natural gas enters the bottom of a primary concentration tower (such as a T-100 in fig. 2) as a heat source of an evaporator to be cooled, and then enters the raw gas cooler again to be converged with the raw gas for continuous precooling. And (5) the precooled natural gas enters the middle part of the primary concentration tower to carry out primary concentration. Part of liquid methane from the bottom of the primary concentration tower is throttled to provide cold energy for the top condenser. The low-pressure return gas after heat exchange and the low-pressure gas from the cryogenic device are converged and then enter a raw gas cooler to recover cold energy, part of the low-pressure return gas is pressurized by a tail gas compressor and then enters a natural gas output pipeline, and the other part of the low-pressure return gas enters a fuel gas system. And most of liquid first yard at the bottom of the tower enters a raw material gas cooler to recycle cold energy after being throttled. Methane reheated to-95 ℃ is cooled by a turbine expander and then exchanges heat with raw gas, and the exhaust gas after cold recovery is pressurized to 1.0Mpa by a coaxial compressor and then enters an output pipeline after being converged with natural gas from a tail gas compressor.

A secondary concentrating column section: primary coarse helium from the primary concentration tower enters a cryogenic device after preliminary cooling in an evaporator at the bottom of a secondary concentration tower (such as T-101 in figure 2). And feeding the cooled crude helium into the tower from the middle part of the secondary concentration tower so as to perform secondary concentration. And merging the liquid from the bottom of the tower with low-pressure gas from the top of the concentration tower after partial cold energy recovery in the cryocooler. The refrigeration required by the secondary concentrating column top condenser is provided by the nitrogen cycle.

Nitrogen circulation system: after nitrogen boosted by the compressor enters the cryogenic refrigerator and low-temperature nitrogen coming out of the tower top condenser and nitrogen methane liquid throttled at the tower bottom are cooled, the refrigerant is throttled to provide cold energy for the tower top condenser of the secondary concentration tower, the low-pressure refrigerator is boosted by the compressor, circulation is completed, and the lost nitrogen is periodically supplemented.

In some embodiments, the combined membrane separation and cryogenic process helium extraction process is shown in FIG. 2, where the primary equipment includes heat exchangers (including cold box 1, cold box 2, etc.), turbo-expanders E-100, E-101, etc., compressors K-100, K-101, etc., and concentrators T-100, T-101, throttles (VLV-100, VLV-101), and check valves (RCY).

The heat exchanger comprises a precooler, a cryocooler, a primary concentration tower, a secondary concentration tower bottom evaporator and a tower top condenser. The heat exchanger is a plate-fin heat exchanger, so that the heat exchange effect can be improved, the cold quantity of the device is better recovered, and the precooling temperature of helium-extracted natural gas is further reduced.

The turbine expander is a key device necessary for obtaining cold energy by separating gas by a low-temperature method, and achieves the aim of refrigeration by performing external work through adiabatic expansion. The helium turboexpander can be adjusted in a larger cold energy range, the isentropic efficiency reaches more than 70%, and frequent inlet flow fluctuation is met.

The compressor provides power for the nitrogen circulation refrigerating system through motor operation, and realizes the refrigerating cycle of compression-condensation (heat release) -expansion-evaporation (heat absorption).

The concentration tower is main equipment for chemical separation, and a packed tower type is selected as a helium extracting device.

The raw material gas is enriched with helium gas and partial gaseous methane is removed through a primary membrane device, the raw material gas is cooled through a cold box 1 and then provides heat for a tower top reboiler of a concentration tower and a denitrification tower, and the cooled raw material gas enters a cold box 2 and then enters a primary concentration tower T-100 for primary helium extraction. And the methane subjected to heat exchange and temperature rise through the condenser enters the cold box 3 for cooling, enters the denitrification tower T-101 after throttling, and the liquid methane flowing out of the denitrification tower bottom is stored in the LNG storage tank.

And after the crude helium at the top of the tower enters the cold box 3 for cooling, the crude helium enters the secondary concentration tower T-102 through throttling to obtain the crude helium. The crude helium is subjected to a pressure swing adsorption device and a helium liquefying device to obtain 99.999% liquid helium. The process flow can obtain pipeline commodity natural gas, a small amount of LNG and liquid helium, and is suitable for the co-production of LNG and helium extraction of inland gas fields.

Step 102, simulating helium extraction processes of different raw gases by using software, wherein helium contents of the different raw gases are different.

When the step is implemented, ASPEN-HYSYS can be adopted. The main components of the raw material gas in the step are helium, nitrogen, methane, ethane, propane and CO ₂ And other heavy hydrocarbons, pressure, temperature, etc. may also be considered in the implementation. The choice of membrane material is critical to the economics of the helium stripping process, and specific implementations may choose a polymer membrane with high selectivity and high permeability to helium in the feed gas methane and nitrogen.

And 103, taking the minimum total energy consumption in the helium extraction process as an optimization target, and establishing a nonlinear regression model of the optimization target and process parameters in the helium extraction process for each raw material gas helium extraction process.

In this step, process parameters include, but are not limited to, primary concentrator temperature (. Degree.C.), primary concentrator feed pressure (kPa), primary concentrator bottoms distribution ratio, and secondary concentrator reflux ratio. Total energy consumption W _{Total (S)} Comprises a total energy consumption W of a tower top condenser and a tower bottom evaporator of a primary concentration tower ₁ Energy consumption sum W of top condenser and bottom evaporator of secondary concentration tower ₂ Energy W of nitrogen compressor _{Nitrogen and nitrogen} And total compressor power W _Pressing 。

Specifically, a nonlinear regression model of an optimization target and each main process parameter in the helium extraction process is established by adopting a response surface method, and is expressed as follows:

W _{total (S)} ＝aX ₁ +bX ₂ +cX ₃ +dX ₄ +eX ₁ X ₂ +fX ₁ X ₃ +gX ₁ X ₄ +hX ₂ X ₃ +iX ₂ X ₄ +jX ₃ X ₄ +kX ₁ ² +lX ₂ ² +mX ₃ ² +nX ₄ ² +ε

Wherein X is ₁ X represents the temperature (DEG C) of the first-stage concentration tower ₂ Represents the feed pressure (kPa), X of the first-stage concentration column ₃ X represents the distribution ratio of the tower bottom material flow of the primary concentration tower ₄ Representing the reflux ratio of the secondary concentrating column. a.b, c, d, e, f, g, h, I, j, k, l, m, n represent the coefficients of variation, ε being the intercept term, these coefficients being obtained by regression.

The response surface method is to obtain the total energy consumption of the system under different technological parameter combinations by utilizing experimental design, and to fit the functional relation between the factors and the response surface by adopting data regression, and to find the optimal technological parameters by analyzing the regression equation, so as to solve the problem of multi-variable optimization. The method adopts a Box-Behnken Design (BBD) response surface method, adopts a User-Defined Design, uses the temperature (DEG C) of a primary concentration tower, the feeding pressure (kPa) of the primary concentration tower, the distribution ratio of the tower bottom material flow of the primary concentration tower, uses the reflux ratio of a secondary concentration tower as an independent variable, and uses the total energy consumption of equipment such as a tower, a tail gas compressor, a nitrogen compressor and the like as a response value. 29 test points were designed, each with different feed gas parameters including composition, pressure, temperature, etc., wherein 6 sets of repeated tests were arranged to perform a mismatch analysis on the desired function.

Step 104, for the nonlinear regression model formed by the regression of the raw gas parameters at each test point, determining the process parameter optimization range of the raw gas by using the nonlinear regression model and the process parameter value range, and completing the optimization of the raw gas process flow.

In the implementation of the step, design Expert software is adopted to take a fitting equation obtained by response surface analysis as an optimization target, actual values of process parameters are taken as constraints, and an optimization value and an optimization parameter are obtained through nonlinear programming. The optimal value is obtained as follows: the feeding temperature of the primary concentration tower is reduced by 2.95 ℃, the feeding pressure of the primary concentration tower is increased by 27.25kPa, the distribution ratio of the tower bottom flow of the primary concentration tower is reduced by 0.02mol/mol, the reflux ratio of the secondary concentration tower is increased by 0.3mol/mol, and the total energy consumption is reduced by 175.233kW. And (3) increasing the power of the condenser according to the optimal parameter value to reduce the feeding temperature of the primary concentration tower, increasing the output power of the compressor to increase the feeding pressure of the primary concentration tower, reducing the number of layers of the primary concentration tower plates to reduce the distribution ratio of the bottom material flow, increasing the number of layers of the secondary concentration tower plates to increase the reflux ratio, and obtaining the optimal process flow with the minimum total energy consumption.

The existing research adopts ASPEN-HYSYS software to simulate the investment, public engineering and operation cost of each device aiming at a specific helium extraction process, and an economic evaluation module is used for evaluating the economic benefit of the helium extraction process, wherein the economic evaluation module takes NPV as an evaluation index to calculate cash inflow and cash outflow; or adopting a detailed item estimation method to estimate each investment and cost in detail according to helium extraction process design, and further carrying out cash flow simulation and economic benefit calculation. However, since the default quota of the rapid-change ASPEN-HYSYS software simulation data of the technology is not in accordance with the actual helium-extracting device investment and cost data, the detailed estimation method needs complete process design and cost estimation of each device flow, and has the problem of consuming a great deal of time and manpower, and is not suitable for the economic benefit evaluation of the helium-extracting project in the investment opportunity selection stage without detailed process design and device price inquiry. No research is currently available on methods for evaluating the capital, operating costs, revenues and incremental economic benefits of LNG production in inland lean helium fields.

Based on this, the following method for evaluating the incremental benefit of LNG helium extraction is proposed based on optimization of LNG helium extraction process, specifically, as shown in fig. 3, for each raw gas, the optimized post helium extraction process further includes:

step 301 calculates the full cycle cost of the apparatus in the feed gas optimized post helium stripping process.

In this step, the full cycle costs of the plant in the helium extraction process include plant costs, operating costs, and utility costs. In the specific implementation, the full cycle cost of each device is estimated according to the actual cost of the same device with different scales obtained by investigation.

Specifically, the full cycle cost of the apparatus in the helium extraction process includes: (1) membrane-related investments. The choice of membrane is determined by the gas composition, the selectivity and permeability of each component. The economics of different membrane separations can be achieved at different temperatures and pressures, including membrane facilities, compressors, heat exchanger investments. (2) Investment of decarburization dehydration device. The stage mainly comprises decarburization and dehydration by an MDEA solvent and a molecular sieve. (3) Low temperature distillation related investments. Cryogenic distillation includes LNG liquefaction and demethanization stages. The cryogenic distillation has design requirements for feed pressure and temperature, reflux ratio, feed ratio, and the partial investment includes compressor investment, heat exchanger investment, condenser investment, rectifying tower investment, etc. meeting the design requirements of cryogenic distillation. (4) And (5) storing and transporting the relevant investment. Mainly the investment in equipment involved in the storage and transportation of liquid helium, LNG and cryogen.

(1) Membrane-related investments. The investment of the membrane separation device is calculated according to the membrane area, and comprises the cost of a membrane frame, membrane materials, connecting valves, supporting structures, instruments and meters and pipelines. The single stage polymeric membrane is capable of purifying a helium-containing nitrogen stream by a factor of 8 to 9.

Wherein CC _mm And CC _mf Is the capital cost of the membrane module and its frame. A is that _m 、C _m And C _mf Is the membrane area (m ² ) Price of unit film module ($/m) ² ) And membrane frame unit price (M$), mem _CAPEX Invest in membranes.

(2) Investment of decarburization dehydration device. The main equipment comprises a decarburization absorption tower, a purification gas separator and a heat exchanger. After heat exchange of a gas-gas heat exchanger, raw gas of the MDEA decarburization system firstly enters the bottommost part of a decarburization absorption tower and is in countercurrent contact with MDEA lean liquid to remove CO in the raw gas ₂ The components are removed by a purification gas separator, and then enter a downstream dehydration device. The rich amine liquid flowing out from the bottom of the flash distillation tower enters the upper part of the regeneration tower to flash distillation after throttling, after entrained gas is further removed, the rich amine liquid exchanges heat with lean liquid at the bottom of the regeneration tower through a solution heat exchanger and heats up, and then enters the inside of the regeneration tower to be in countercurrent contact with hot vapor rising in the tower body, so that CO in the rich liquid is obtained ₂ The gas is removed from the MDEA rich liquid by supplying energy required for regeneration through a reboiler at the bottom of the regeneration tower to generate endothermic chemical reaction, and the endothermic chemical reaction enters the upper part of the regeneration tower to be flashed.

The investment of the decarbonization and dehydration device is related to the component content of the raw material gas and the treatment scale, and the decarbonization and dehydration device is based on the treatment scale of each device in the same co-production LNG helium extraction process. And estimating the treatment scale of the decarburization and dehydration device of the project according to the component content of the carbon dioxide and water after the raw material gas is subjected to membrane separation and the treatment scale of the analog project device.

The decarburization and dehydration investment is estimated by a scale index method according to the treatment scale.

（4）

Wherein, the scale index takes a value of 0.6-0.9, and the adjustment coefficient considers the comprehensive adjustment coefficients such as quota, unit price, cost change and the like at different times and different places.

(3) Low temperature distillation related investments. The main equipment comprises a condenser, a reboiler, a distillation column, a heat exchanger and a cooler. The number of layers of trays, reboiler, condenser duty and reflux ratio were calculated based on the distillation column inlet temperature, pressure and feed composition. Capital costs are calculated from the corresponding number of facilities and unit price selected for the temperature, pressure and flow rate of the process gas during simulation.

The part is divided into supercharging device investment, demethanizer investment, helium refining device investment, helium liquefying device investment, natural gas liquefying device investment and flash gas supercharging device investment according to treatment objects. The plant investment is related to the scale of the intake air treatment while the scale effect is taken into account. Because the price difference of devices in each area and each company is large, the equipment price obtained by directly adopting ASPEN-HYSYS software simulation is large in comparison with the actual price, the part is analogized by investment under the same technology of a certain domestic helium extraction project, and the scale index method is adopted to estimate the intake treatment scale.

I) Treatment scale of each apparatus

Flash gas pressurization plant treatment scale = feed gas treatment scale (11)

II) estimation of investment in units

(4) And (5) storing and transporting the relevant investment. The part mainly comprises liquid helium storage and transportation and LNG storage and transportation related investments, including LNG tank areas and loading, cryogen storage devices, helium storage and loading facilities and empty nitrogen station investments.

Step 302, calculating the operation cost according to each operation link in the helium extraction process after the optimization of the raw material gas.

When the step is implemented, the component items of the operation cost and the technical cause of each component item are determined according to each operation link (each material, fuel, manual input and the like) in the helium extraction process after the optimization of the raw material gas; and then, calculating the operation cost of the helium extraction process according to the actual treatment scale of each operation link and the technical cause of each constituent sub-item of each operation link in the helium extraction process after the optimization of the raw material gas. Wherein the actual process scale is analogically determined from the actual process scale, see the process scale formula above.

According to the process flow of the membrane separation and the cryogenic distillation combined production LNG helium extraction, the component items of the operation cost are composed of direct labor cost, material cost, power cost, fuel cost, repair cost, water cost, refrigerant cost and indirect cost. The direct labor costs are primarily for plant operation, and the material costs include membrane replacement costs, molecular sieve costs, solvent costs, and dehydrogenation catalyst costs. The power cost comprises the electricity consumption of the condenser, the reboiler, the heat exchanger and the cooler equipment. Indirect fees include administrative fees, sales fees, and financial fees.

Direct labor cost = total number of devices x individual device personnel x labor cost.

Film replacement cost = film replacement unit price x annual replacement amount.

Molecular sieve cost = molecular sieve unit price x annual usage.

Solvent cost = solvent unit price x annual consumption.

Dehydrogenation catalyst cost = dehydrogenation catalyst unit price x annual usage.

Coolant charge = annual usage x unit price of coolant.

Cost of liquid nitrogen = unit price of liquid nitrogen x annual consumption.

Power cost = total number of devices x power of devices x electricity price.

Fuel cost = consumption x unit price of fuel.

Water cost = consumption x water unit price

Repair fee = fixed asset total x repair rate.

Management fee = direct manual fee x management rate.

Sales cost = production cost x sales rate.

Financial fee = loan x annual rate.

The above-described determination of the annual consumption of the operation is critical. And determining technical causes of different operation cost items according to the objects of the materials, the fuel, the manpower and the like which are put into operation by combining the process flow, and calculating the annual consumption of each cost by the technical causes.

TABLE 1 cost of operation composition and cost technological reasons

Each operating cost is estimated according to different cost trends and cost ratings.

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Repair fee = total investment x repair fee coefficient (35)

Management fee = business income x management fee coefficient (36)

Business charge = incomes x business charge coefficient (37)

Wherein, the direct labor cost and other operation cost scale indexes are 0.7, and the fuel cost distinguishes the fuel and LNG consumption natural gas cost. The financial cost is determined according to the loan amount, the interest rate, the repayment time and the repayment mode.

Step 303, estimating the respective product revenues for the optimized post helium stripping process for the feed gas.

The products under the helium extraction process in this step include refined helium and LNG (liquefied natural gas), and when implemented, include: helium prices, i.e. power forms of gray models, are predicted using a nonlinear gray bernoulli model (Nonlinear Grey Bernoulli Model, NGBM) in which parameters are calculated using whale algorithm. The whale algorithm execution flow is shown in fig. 6.

Determining the LNG price according to the transportation cost and the factory price; and calculating the product income under the optimized process parameters according to the predicted helium price, the helium amount obtained by the helium extraction process of the raw material gas, the LNG price and the LNG yield obtained by the helium extraction process of the raw material gas.

Specifically, the gray prediction method can use small sample data to quantify the internal uncertainty, and the traditional gray model is not suitable for sequence fitting with larger fluctuation and can only be used for sequences growing exponentially. And the price of helium and the growth rate thereof show nonlinear characteristics, so that a nonlinear gray Bernoulli model suitable for fitting the history data with large fluctuation is adopted in the step. Parameter values in the NGBM model were determined using whale algorithm. The basic parameter is set to a population size n=40, and the maximum iteration number max_iter=50. The non-linear parameter r can be obtained by Matlab programming, the parameters a and b are further obtained, and the predicted price value can be obtained by modeling the parameters with an NGBM model.

The specific determination process of the LNG price comprises the following steps: 1) According to the market price of the adjacent market, the gate price of the natural gas in a preset area is combined for adjustment; 2) And determining the price of the LNG by taking the import to the shore price of the LNG as a reference and taking the distance and the freight from the shore region to the preset region into consideration. Under the LNG co-production helium extraction process flow, the final product comprises pipeline commodity gas besides LNG and refined helium. The raw material gas is pipeline commodity gas, so that the income and the cost of the pipeline commodity gas are not considered in the calculation of income and cost. The LNG and refined helium production in this step decays with the field production, and the total revenue of the project is estimated from the homonymously decayed LNG production and refined helium production and the corresponding prices.

And 304, calculating the helium extraction benefit of the combined LNG according to the full cycle cost, the operation cost and the product income.

When the step is implemented, annual investment and operation cost are determined according to the investment and operation cost estimated values and helium production planning and output change in the life period (estimated according to natural gas output and helium content of a gas field), annual cash outflow is obtained in each year of the life period, annual cash inflow is obtained by combining the project total income estimated by annual LNG and refined helium output and corresponding prices, net present value and internal income value of the LNG helium extraction project are calculated by cash inflow and cash outflow in the life period, and then the LNG helium extraction benefit is calculated according to the net present value and the internal income value.

NPV represents net present value, CI represents cash inflow, CO represents cash outflow, t represents the t-th year, n is life span, i ₀ Is the baseline discount rate and NCFt represents the net cash flow at the t-th year. The standard discount rate of the oil and gas industry is 12 percent, and the reference discount rate can be reduced to 6 percent for new energy or other strategic resources.

When npv=0, i at this time ₀ =irr, IRR represents the internal yield.

Specifically, the present step calculates cash flow and profit for the co-production LNG helium project, irrespective of loan and interest costs. Investment is put into years according to the analog production scale. Since feed gas decays with field yield, the corresponding operating costs are adjusted according to the feed gas (field yield) intake scale. The sales tax in the value-added tax mainly takes the sales income of LNG and refined helium products as tax bases, and the income tax takes the operation cost of investment construction and outsourcing as tax base. The tax and the additional are mainly added for urban tax and education fee, and both are based on added value tax. The construction investment forms an asset metering depreciation. Allowing loss of spin. From the cash inflow and cash outflow in the cash flow table, the net present value of the project and the internal yield rate are calculated to judge the project economy, wherein the discount rate is 12%.

In step 305, the cost of stripping LNG is calculated as the incremental benefit of the helium extraction process after optimization of the feed gas.

By analyzing the investment attribution of each plant and materials, fuel, labor, etc., the cost of stripping LNG from the total cost includes the cost of stripping LNG plant and the cost of operation.

In the whole period cost, firstly methane gas and helium-rich concentrated gas are separated by a membrane separation device, at the moment, the helium concentration is increased by 8-9 times, and 2/3 methane gas is removed and is taken as commodity gas to be delivered from a pipeline. The membrane separation device is used for improving the gas concentration and reducing the gas inlet scale, and the investment is closely related to the LNG treatment scale and is classified as LNG investment. The pressurization device is partly for natural gas liquefaction and partly for helium extraction, and the investment is split according to the LNG investment ratio in the co-production project. The investment of the decarbonization dehydration device is to purify raw material gas, and then natural gas liquefaction and helium extraction are realized through low-temperature distillation, which is classified as LNG investment. The demethanizer, helium refining device, helium liquefying device and helium storage and loading facilities are coarse helium extraction, helium refining, helium liquefaction and helium storage and transportation, and all the investment is classified into helium preparation. The natural gas liquefaction device, the flash gas supercharging device, the LNG tank farm and the loading and refrigerant storage device are LNG preparation facilities and are classified as LNG investment. The empty nitrogen station is used for providing nitrogen and is used for co-producing LNG helium extraction refrigeration, and the investment of LNG is classified. The ground supporting facilities are split according to the investment ratio of LNG.

In the operation cost, the electricity consumption is divided according to the LNG investment ratio, the molecular sieve cost, the MDEA solution cost, the defoamer cost, the membrane replacement cost and the cryogen cost are classified into LNG, the liquid nitrogen is mainly used for helium liquefaction, the operation cost for preparing helium is classified, and the fuel cost is used for distinguishing the raw material gas cost and the fuel consumption for LNG consumption. Direct labor and other operating fees are split according to LNG investment ratio.

LNG investment and operating costs are deducted from the cash flow sheet at step 304 to obtain an incremental cash flow of helium extraction, and the net present value and internal rate of return for the helium extraction item are calculated, with a discount rate of 6%. And calculating the helium extraction increment benefit of the helium extraction process after optimizing the raw material gas according to the net present value and the internal benefit of the helium extraction project.

In one embodiment herein, step 305 further includes:

In specific implementation, the unit helium extraction cost is calculated by using the following formula:

unit helium extraction cost= (cumulative device full cycle investment + cumulative operating cost + tax)/helium cumulative yield.

In one embodiment herein, further comprising:

and determining a target helium extraction process of the to-be-analyzed helium-depleted gas field according to the helium extraction increment benefit of the helium extraction process after optimizing each feed gas. Specifically, when the net present value (reference discount rate 6%) is greater than 0, the helium extraction link is effective; when the internal yield is greater than the reference discount rate, the helium extraction link is effective.

The embodiment is applied to economic evaluation of a lean helium Tian Di helium project, is beneficial to accurately evaluating the economic value of the helium project, provides a method support for economically and effectively acquiring key mineral resources and natural gas industrial chain increment, and ensures the safety of rare strategic resources.

Based on the same inventive concept, there is also provided herein a co-production LNG helium extraction process optimization device, as described in the following examples. Because the principle of solving the problem of the co-production LNG helium extraction process optimizing device is similar to that of the co-production LNG helium extraction process optimizing method, the implementation of the co-production LNG helium extraction process optimizing device can refer to the co-production LNG helium extraction process optimizing method, and repeated parts are omitted.

Specifically, as shown in fig. 4, the optimization device for the co-production LNG helium extraction process includes:

a helium extraction process determining unit 401, configured to establish a helium extraction process for co-producing LNG membrane separation and low temperature method combination according to a lean helium field feed gas component to be analyzed, where the helium extraction process includes a helium extraction related device, a material flow and an energy flow;

a simulation unit 402, configured to simulate helium extraction processes of different raw gases by using software, where helium contents of the different raw gases are different;

a model determining unit 403, configured to establish, for each helium extraction process of the raw material gas, a nonlinear regression model of the optimization target and process parameters in the helium extraction process, with the minimum total energy consumption in the helium extraction process as an optimization target;

And the process parameter optimization unit 404 is configured to determine, for each nonlinear regression model corresponding to the feed gas, a process parameter optimization range of the feed gas by using the nonlinear regression model and the process parameter value range, and complete optimization of the feed gas process.

Further, the method further comprises the following steps: the incremental benefit evaluation unit 405 is used for calculating the full cycle cost of the device in the helium extraction process after the optimization of the raw material gas; calculating the operation cost according to each operation link in the helium extraction process after optimizing the raw material gas; estimating the income of each product in the helium extraction process after optimizing the raw material gas; according to the full cycle cost, the operation cost and the product income, the net present value and the internal income ratio of the LNG helium extraction project are co-produced, and further the co-production LNG helium extraction benefit is calculated; the cost of stripping LNG, and the helium extraction incremental benefit of the helium extraction process after optimizing the feed gas are calculated.

According to the embodiment, the energy consumption of the lean helium Tian Di helium process can be reduced by optimizing the combined production LNG helium extraction process related to an inland lean helium field, meanwhile, according to different raw material gas helium contents and product extraction requirements, the net present value and the internal profitability of a combined production LNG helium extraction project are calculated by adopting process simulation and actual device investment cost analogy, LNG investment and operation cost are stripped from a technical angle, the helium extraction incremental benefit is determined, the incremental benefit of the helium extraction part can be accurately and reliably determined, further the profitability of a helium extraction link is evaluated, and the target helium extraction process is selected. In summary, the present disclosure enables an increase in helium component content, a decrease in helium extraction unit investment and cost.

In an embodiment herein, a computer device is also provided, as shown in fig. 5, the computer device 502 may include one or more processors 504, such as one or more Central Processing Units (CPUs), each of which may implement one or more hardware threads. The computer device 502 may also include any memory 506 for storing any kind of information, such as code, settings, data, etc. For example, and without limitation, memory 506 may include any one or more of the following combinations: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any memory may store information using any technique. Further, any memory may provide volatile or non-volatile retention of information. Further, any memory may represent fixed or removable components of computer device 502. In one case, when the processor 504 executes associated instructions stored in any memory or combination of memories, the computer device 502 can perform any of the operations of the associated instructions. The computer device 502 also includes one or more drive mechanisms 508, such as a hard disk drive mechanism, an optical disk drive mechanism, and the like, for interacting with any memory.

The computer device 502 may also include an input/output module 510 (I/O) for receiving various inputs (via an input device 512) and for providing various outputs (via an output device 514). One particular output mechanism may include a presentation device 516 and an associated graphical user interface 518 (GUI). In other embodiments, input/output module 510 (I/O), input device 512, and output device 514 may not be included, but merely as a computer device in a network. Computer device 502 may also include one or more network interfaces 520 for exchanging data with other devices via one or more communication links 522. One or more communication buses 524 couple the above-described components together.

Communication link 522 may be implemented in any manner, for example, by a local area network, a wide area network (e.g., the internet), a point-to-point connection, etc., or any combination thereof. Communication link 522 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.

Embodiments herein also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the above method.

Embodiments herein also provide a computer readable instruction, wherein the program therein causes the processor to perform the method of any of the preceding embodiments when the processor executes the instruction.

It should be understood that, in the various embodiments herein, the sequence number of each process described above does not mean the sequence of execution, and the execution sequence of each process should be determined by its functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments herein.

It should also be understood that in embodiments herein, the term "and/or" is merely one relationship that describes an associated object, meaning that three relationships may exist. For example, a and/or B may represent: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.

Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.

In the several embodiments provided herein, it should be understood that the disclosed systems, devices, and methods may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices, or elements, or may be an electrical, mechanical, or other form of connection.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the elements may be selected according to actual needs to achieve the objectives of the embodiments herein.

In addition, each functional unit in the embodiments herein may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solutions herein are essentially or portions contributing to the prior art, or all or portions of the technical solutions may be embodied in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments herein. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

Specific examples are set forth herein to illustrate the principles and embodiments herein and are merely illustrative of the methods herein and their core ideas; also, as will be apparent to those of ordinary skill in the art in light of the teachings herein, many variations are possible in the specific embodiments and in the scope of use, and nothing in this specification should be construed as a limitation on the invention.

Claims

1. The optimization method for the co-production LNG helium extraction process is characterized by comprising the following steps of:

and for the nonlinear regression model corresponding to each raw gas, determining the process parameter optimization range of the raw gas by utilizing the nonlinear regression model and the process parameter value range, and completing the optimization of the process flow of the raw gas.

2. The method of claim 1, wherein the post helium stripping process is optimized for each feed gas, further comprising:

3. The method of claim 2, wherein the post helium stripping process is optimized for each feed gas, further comprising:

4. The method as recited in claim 2, further comprising:

5. The method of claim 2, wherein calculating an operating cost based on each operating link in the feed gas optimized post helium stripping process comprises:

6. The method of claim 2, wherein estimating the respective product revenues for the optimized process parameters of the feed gas comprises:

7. The method of claim 2, wherein the feed gas optimized post helium stripping process apparatus comprises: membrane separation device, decarbonization dehydration device, cryogenic distillation device, storage transportation device.

8. The utility model provides a coproduction LNG draws helium technology optimizing device which characterized in that includes:

9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 7 when executing the computer program.

10. A computer storage medium having stored thereon a computer program, which when executed by a processor of a computer device implements the method of any of claims 1 to 7.