Process design and optimization of helium extraction and ethane co-production by nitrogen double expansion refrigeration

MA Guoguang; ZHOU Mingjie; LEI Yang; LIU Lu; DENG Haotian

doi:10.12434/j.issn.2097-2547.20230306

您当前的位置：

首页 >

文章列表页 >

Process design and optimization of helium extraction and ethane co-production by nitrogen double expansion refrigeration

- Process design and optimization of helium extraction and ethane co-production by nitrogen double expansion refrigeration
- Vol. 49, Issue 10, Pages: 110-118(2024)
- 作者机构：
  
  1.西南石油大学　石油与天然气工程学院，四川成都 610500
  2.深圳燃气集团股份有限公司，广东深圳 518000
- 作者简介：
- 基金信息：
- DOI：10.12434/j.issn.2097-2547.20230306
  CLC： TE646
- Published：25 October 2024，
  
  Received：10 September 2023，
  
  Revised：23 October 2023，
- 稿件说明：
移动端阅览
马国光,周明杰,雷洋等.氮气双膨胀制冷提氦联产乙烷工艺设计与优化[J].低碳化学与化工,2024,49(10):110-118.

MA Guoguang,ZHOU Mingjie,LEI Yang,et al.Process design and optimization of helium extraction and ethane co-production by nitrogen double expansion refrigeration[J].Low-carbon Chemistry and Chemical Engineering,2024,49(10):110-118.
马国光,周明杰,雷洋等.氮气双膨胀制冷提氦联产乙烷工艺设计与优化[J].低碳化学与化工,2024,49(10):110-118. DOI： 10.12434/j.issn.2097-2547.20230306.

MA Guoguang,ZHOU Mingjie,LEI Yang,et al.Process design and optimization of helium extraction and ethane co-production by nitrogen double expansion refrigeration[J].Low-carbon Chemistry and Chemical Engineering,2024,49(10):110-118. DOI： 10.12434/j.issn.2097-2547.20230306.

摘要

国内某气田天然气中乙烷和氦气含量（物质的量分数）逐年升高，回收价值凸显。提出了一种氮气双膨胀制冷提氦联产乙烷工艺，采用HYSYS软件对该工艺进行了流程模拟，并对工艺流程的关键参数（低温分离器温度、脱甲烷塔塔顶回流比、二级提氦塔进料温度、二级提氦塔塔顶回流比、氮气膨胀端入口压力、氮气膨胀端出口压力和氮气制冷剂流量）对工艺指标的影响规律开展了研究。基于最优化理论，以C

收率最大和二次粗氦浓度最大时装置总能耗最小为目标，采用Back Propagation（BP）神经网络算法对关键参数进行了寻优。结果表明，装置总能耗主要受低温分离器温度、氮气膨胀端出口压力和氮气制冷剂流量影响，C

收率主要受低温分离器温度和脱甲烷塔塔顶回流比影响，氦收率主要受二级提氦塔进料温度影响。关键参数最佳组合为：低温分离器温度为-95.30 ℃，氮气制冷剂流量为1549.22 kmol/h，氮气膨胀端入口压力为3.25 MPa，氮气膨胀端出口压力为0.44 MPa，脱甲烷塔塔顶回流比为0.13，二级提氦塔进料温度为-150.57 ℃，二级提氦塔塔顶回流比为0.80。相比于优化前，优化后装置总能耗降低了1.46%，C

收率提升了5.64%，二次粗氦浓度（物质的量分数）

提升了1.81%。

Abstract

The content (mole fraction) of ethane and helium in the natural gas of a domestic gas field is increasing year by year

and the recovery value is highlighted. A process of helium extraction and ethane co-production by nitrogen double expansion refrigeration was proposed. The process was simulated by HYSYS software

and the influences of the key parameters of the process (temperature of the cryogenic separator

reflux ratio of the demethanizer top

feed temperature of the secondary helium extraction tower

reflux ratio of the secondary helium extraction tower top

inlet pressure of the nitrogen expansion end

outlet pressure of the nitrogen expansion end and flow rate of the nitrogen refrigerant) on the process indexes were investigated. Based on the optimisation theory

the Back Propagation (BP) neural network algorithm was used to optimise the key parameters with the objectives of minimising the total energy consumption of the unit when the C

yield and the secondary crude helium concentration were maximised. The results show that the total energy consumption of the unit is mainly affected by temperature of the cryogenic separator

the outlet pressure of the nitrogen expansion end and the flow rate of the nitrogen refrigerant

and the C

yield is mainly affected by temperature of the cryogenic separator and the reflux ratio of the demethanizer top

and the helium yield is mainly affected by the feed temperature of the secondary helium extraction tower. The optimal combination of key parameters is as follows: Temperature of the cryogenic separator is -95.30 ℃

flow rate of the nitrogen refrigerant is 1549.22 kmol/h

inlet pressure of the nitrogen expansion end is 3.25 MPa

outlet pressure of the nitrogen expansion end is 0.44 MPa

reflux ratio of the demethanizer top is 0.13

feed temperature of the secondary helium extraction tower is -150.57 ℃

and eflux ratio of the secondary helium extraction tower top is

0.80. Compared with the pre-optimization

the total energy consumption of the optimized unit is reduced by 1.46%

the C

yield is increased by 5.64%

and the secondary crude helium concentration (mole fraction) is increased by 1.81%.

关键词

氮气双膨胀制冷天然气提氦乙烷回收联产工艺参数优化BP神经网络算法

Keywords

nitrogen double expansion refrigerationhelium extraction from natural gasethane recoveryco-production processparameter optimizationBP neural network algorithm

references

蒋洪, 蔡棋成. 高压天然气乙烷回收高效流程[J]. 石油与天然气化工, 2017, 46(2): 6-11+21.

JIANG H, CAI Q C. High efficiency process of ethane recovery for high-pressure natural gas [J]. Chemical Engineering of Oil & Gas, 2017, 46(2): 6-11+21.

李长俊, 张财功, 贾文龙, 等. 天然气提氦技术开发进展[J]. 天然气化工—C1化学与化工, 2020, 45(4): 108-116.

LI C J, ZHANG C G, JIA W L, et al. Progress in technologies for helium-extraction from natural gas [J]. Natural Gas Chemical Industry, 2020, 45(4): 108-116.

赖秀文, 邵勇, 张淑文, 等. 富氦天然气中提取氦气的深冷工艺研究[J]. 深冷技术, 2013, (5): 36-39.

LAI X W, HAO Y, ZHANG S W, et al. Approach to cryogenic process to extract helium from helium-rich NG [J]. Cryogenic Technology, 2013, (5): 36-39.

蒋洪, 陈泳村, 程祥. 低含氦天然气提氦联产LNG工艺设计与分析[J]. 低碳化学与化工, 2023, 48(4): 169-175.

JIANG H, CHEN Y C, CHENG X. Process design and analysis of extracting helium from low helium natural gas and co-producing LNG [J]. Low-Carbon Chemistry and Chemical Engineering, 2023, 48(4): 169-175.

TYURINA E A, STEPANOV V V. Power-generating and processing plants for combined production of liquefied natural gas and electricity with extraction of helium [J]. Thermal Engineering, 2009, 56(7): 577-582.

钟志良, 何珺, 汪宏伟, 等. 某大型提氦装置工艺技术探讨[J]. 天然气与石油, 2011, 29(1): 25-28+33+6.

ZHONG Z L, HE J, WANG H W, et al. Discuss on helium extraction technology in certain large gas treatment unit [J]. Natural Gas and Oil, 2011, 29(1): 25-28+33+6.

杜双. 天然气低温提氦工艺优化研究[D]. 成都: 西南石油大学, 2019.

DU S. Study on optimization of low temperature helium extraction process from natural gas [D]. Chengdu: Southwest Petroleum University, 2019.

马国光, 杜双. 天然气提氦与制LNG结合工艺分析[J]. 化学工程, 2019, 47(1): 74-78.

MA G G, DU S. Analysis on the combination process of natural gas helium extraction and LNG production [J]. Chemical Engineering, 2019, 47(1): 74-78. .

周军, 徐东阳, 梁光川, 等. 联产乙烷天然气提氦工艺的经济性与适用性分析[J]. 石油化工, 2023, 52(2): 229-236.

ZHOU J, XU D Y, LIANG G C, et al. Economic and applicability analysis of extraction process of helium from natural gas with coproduction of ethane [J]. Petrochemical Technology, 2023, 52(2): 229-236.

蒋洪, 陈泳村, 程祥, 等. 深冷法提氦联产LNG工艺分析优化[J]. 化学工程, 2023, 51(8): 78-83+88.

JIANG H, CHEN Y C, CHENG X, et al. Exergy analysis and optimization of helium extraction and LNG production by cryogenic process [J]. Chemical Engineering, 2023, 51(8): 78-83+88.

罗尧丹. 某提氦装置工艺优化研究[D]. 成都: 西南石油大学, 2015.

LUO Y D. Study on process optimization of a helium extraction device [D]. Chengdu: Southwest Petroleum University, 2015.

HAMEDI H, KARIMI A I, GUNDERSEN T. Optimization of helium extraction processes integrated with nitrogen removal units: A comparative study [J]. Computers and Chemical Engineering, 2019, 121: 354-366.

TYOOR D A. 基于人工神经网络的天然气液化工艺优化研究[D]. 西安: 西安石油大学, 2020.

TYOOR D A. Study on optimization of natural gas liquefaction process based on artificial neural network [D]. Xi’an: Xi’an Shiyou University, 2020.

马晓茜, 廖艳芬. 液化天然气储运与利用中的几个关键问题[J]. 石油与天然气化工, 2005, (5): 363-367+336-337.

MA X Q, LIAO Y F. The key issues in lng storage, transport and utilization [J]. Chemical Engineering of Oil & Gas, 2005, (5): 363-367+336-337.

张会娟. 基于神经网络的多组分液体翻滚预测模型研究[D]. 大连: 大连理工大学, 2020.

ZHANG H J. Study on prediction model of multi-component liquid tumbling based on neural network [D]. Dalian: Dalian University of Technology, 2020.

刘淼儿, 单卫光, 朱建鲁, 等. 基于GA-BP模型的混合制冷剂天然气液化装置运行参数优化分析[J]. 中国海上油气, 2023, 35(2): 195-201.

LIU M E, SHAN W G, ZHU J L, et al. Operation parameters optimization analysis of mixed refrigerant cycle natural gas liquefaction unit based on GA-BP model [J]. China Offshore Oil and Gas, 2023, 35(2): 195-201.

郭子江, 尹晨阳, 马国光, 等. 基于BP神经网络的低温提氦工艺优化[J]. 天然气化工—C1化学与化工, 2020, 45(1): 51-56.

GUO Z J, YIN C Y, MA G G, et al. Optimization of low temperature extraction process based on BP neural network [J]. Natural Gas Chemical Industry, 2020, 45(1): 51-56.

GUAN X Y, LU K D, ZHANG N G, et al. Analysis of the photochemical characteristics and sensitivity of ozone pollution in Xi’an [J]. Chinese Science Bulletin, 2021, 66(35): 4561-4573.

LI S H, ZHOU H M, YAN Y S, et al. Reliability and sensitivity analysis of loop-designed security and stability control system in interconnected power systems [J]. Global Energy Interconnection, 2022, 5(5): 501-511.

MOSTAFAEI H, BEHNAMFAR F, ALEMBAGHERI M. Reliability and sensitivity analysis of wedge stability in the abutments of an arch dam using artificial neural network [J]. Earthquake Engineering and Engineering Vibration, 2022, 21(4): 1019-1033.

LI H C, CHEN Y, LIU D S, et al. Sensitivity analysis, determination and optimization of granite RHT parameters [J]. Journal of Beijing Institute of Technology, 2019, 28(1): 94-102.

唐霏, 彭星煜. 基于RS-BP神经网络的增压站能效评价及预测[J]. 油气储运, 2019, 38(3): 314-320.

TANG F, PENY X Y. Energy efficiency evaluation and prediction of booster stations based on RS-BP Neural Network [J]. Oil & Gas Storage and Transportation, 2019, 38(3): 314-320.

苏俊收, 刘汉光, 周朋辉, 等. 正交试验设计在工程车辆驾驶室悬置系统优化上的应用[J]. 机械设计与制造, 2022, (1): 93-96.

SU J S, LIU H G, ZHOU P H, et al. The application of orthogonal test in the system of the suspension system of the cab of the engineering vehicle [J]. Machinery Design & Manufacture, 2022, (1): 93-96.

王瑞. 基于遗传优化BP神经网络的污水处理水质预测研究[D]. 广州: 华南理工大学, 2012.

WANG R. Prediction of wastewater treatment based on genetic algorithm optimization BP artificial neural network [D]. Guangzhou: South China University of Technology, 2012.

Views

下载量

CNKI被引量

Alert me when the article has been cited

提交

Tools

Publicity Resources

Parameters optimization for natural gas ethane recovery process based on response surface methodology

Optimization of SCORE process parameters for propane recovery based on response surface methodology

Optimization of parameters of dual mixed refrigerant liquefaction process based on Particle Swarm Optimization algorithm

Analysis of energy consumption of amine solution regeneration in natural gas decarburized

Related Author

WANG Xiaolei

RAO Helong

HU Feng

CHEN Yuntao

XIE Hu

LIAO Mingwang

LYU Xiaoming

LI Ziyuan

Related Institution

State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University

No.1 Gas Production Plant of Xinjiang Oilfield Company

PipeChina Southwest Pipeline Co., Ltd.

Petroleum Engineering School, Southwest Petroleum University

National Engineering Laboratory for Pipeline Safety, Beijing Key Laboratory of Urban Oil and Gas Distribution Technology,China University of Petroleum (Beijing)

Postal code：610225
Tel：028-85964717 Email：dthxyhg@swchem.com
Technical support is provided by Beijing Founder electronics co., LTD 蜀ICP备12008600号-10 蜀公网安备51012202001533
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.
Total Visits：128596 Visits Today：713

⁰