天然气是清洁能源，使用量在不断增加。天然气集输的最主要方式是管道运输，在日常运行中，存在山体滑坡、腐蚀穿孔及外力破坏的情况易导致输送管道破裂发生泄漏。高硫天然气管道硫化氢泄漏会引起硫化氢中毒、云团爆炸等事故和造成环境污染。为了研究影响硫化氢泄漏规律的因素，建立有针对性的分级预警方法，为硫化氢泄漏事故预防提供保障。得到以下结论：

通过自研硫化氢管道泄漏实验平台，研究在不同浓度、泄漏管径和风流条件下硫化氢的泄漏规律。结论表明：泄漏源的硫化氢浓度越大，硫化氢气体越容易聚集，达到危险浓度的时间越短。泄漏管径对硫化氢泄漏扩散有消极影响，泄漏管径越小，扩散速度越快，达到临界危险浓度的时间越短。风流方向会影响硫化氢的扩散方向，从而更容易使硫化氢聚集，不易扩散，高浓度区域增大，危险性增大。

利用FLACS软件对普光301井及周边环境进行数值模拟，研究在不同风速、温度、泄漏孔径和泄漏位置条件下，高硫天然气管道硫化氢泄漏气体浓度分布规律。硫化氢泄漏会形成云团进行扩散。结论表明：环境风速、温度、泄漏孔径和泄漏位置会对泄漏气云的浓度分布情况、云团扩散时的形态和扩散距离造成影响。风速增大会使泄漏气体云团的扩散范围变大，抑制高浓度区域形成。温度和泄漏孔径增大会使泄漏气云的扩散范围变大，促使高浓度区域形成。泄漏位置附近有障碍物容易形成不易消散的稳定硫化氢云团，这些云团在监测时不易监测到，危险性较高。

利用GAN网络对实验数据和FLACS模拟数据进行数据增强，获得大量有效数据，对高斯烟羽模型进行优化，用优化后的模型对高硫天然气管道硫化氢泄漏扩散危险区域进行预测划分。根据优化后的高斯烟羽模型在不同风速下划分的危险区域，研究设计了有针对性的高硫天然气管道硫化氢泄漏风险预警办法及事故应急处置对策。

Natural gas is a clean energy source and its use is increasing. The most important way of natural gas gathering and transportation is pipeline transportation, in the daily operation, there are landslides, corrosion perforation and external influence damage caused by transmission pipeline rupture leakage. Sulphur-containing natural gas pipeline leaks may cause accidents such as hydrogen sulphide poisoning, cloud explosions and environmental pollution. In order to study the factors affecting the pattern of hydrogen sulphide leakage, establish a targeted grading warning method to provide protection for the prevention of hydrogen sulphide leakage accidents. This paper carries out the following research:

Through the independently constructed experimental platform for hydrogen sulphide leakage in pipelines, the leakage law of hydrogen sulphide is investigated under the conditions of different concentrations, leakage pipe diameters and wind flow. The study shows that: the larger the concentration of hydrogen sulfide in the leakage source, the easier it is to gather hydrogen sulfide gas, and the shorter the time to reach the dangerous concentration; the diameter of the leakage pipe has a negative impact on the diffusion of hydrogen sulfide leakage, the smaller the diameter of the leakage pipe, the faster the diffusion speed, and the shorter the time to reach the critical dangerous concentration; the wind flow affects the direction of the diffusion of hydrogen sulfide, which is easier to make the hydrogen sulfide gather, not easy to diffuse, and the area of high concentration is larger, and the risk is increased. Increase. Wind speed will accelerate the diffusion of hydrogen sulphide, which is not easy to form a gathering area, and the leakage range becomes larger, which brings difficulty for monitoring.

Numerical simulation of Puguang 301 well and the surrounding environment is carried out by FLACS software to study the distribution law of gas concentration of sulphur-containing natural gas pipeline leakage under different conditions of wind speed, temperature, leakage aperture and leakage location. Hydrogen sulphide leakage will form clouds for diffusion. The effects of ambient wind speed, temperature, leakage aperture and leakage location on the concentration distribution of the leakage gas cloud, the morphology of the cloud during diffusion and the diffusion distance were investigated. The increase of wind speed will make the diffusion range of the leaking gas cloud larger and inhibit the formation of the high concentration area; the increase of temperature and leakage aperture will make the diffusion range of the leaking gas cloud larger and promote the formation of the high concentration area; there are obstacles near the location of the leakage, so that the cloud will not be easy to diffuse to the far distance, and the high concentration area will not be easy to dissipate, and the diffusion range will be small and the concentration will be high.

Data enhancement of experimental data and FLACS simulation data is carried out using GAN network to obtain a large amount of effective data to optimise the Gaussian smoke plume model, and the optimised model is used to predict and classify the hazardous area of sulphur-containing natural gas pipeline leakage diffusion. Based on the optimised Gaussian plume model in different wind speeds, a targeted risk warning method for sulphur-containing natural gas pipeline leakage and emergency response countermeasures were designed.

[1]张抗, 李铁军. 中国未开发天然气储量分析和对策[J]. 天然气地球科学, 2015, 26(02): 199-207.

[2]王保群, 林燕红, 代运锋. 我国成品油管道现状与展望[J]. 石油规划设计, 2010, 21(05): 7-9+50.

[3]李雪, 余晓钟, 钟书丽. 川渝地区天然气产业可持续发展影响因素分析[J]. 石油科技论坛, 2018, 37(06): 6-13+18.

[4]王小强, 王保群, 王博等. 我国长输天然气管道现状及发展趋势[J]. 石油规划设计, 2018, 29(05): 1-6+48.

[5]陈蕊, 孙文宇, 吴珉颉. 国家管网公司成立对中国天然气市场竞争格局的影响[J]. 天然气工业, 2020, 40(03): 137-45.

[6]杨光. 《中长期油气管网规划》意义重大[J]. 中国能源, 2017, 39(12): 28-30.《中长期油气管网规划》发布[J]. 天然气工业, 2017, 37(07): 114.

[7]高振宇, 张慧宇, 高鹏. 2022年中国油气管道建设新进展[J]. 国际石油经济, 2023, 31(03): 16-23.

[8]戴金星. 含硫化氢的天然气分布特征、分类及其成因探讨[J]. 沉积学报, 1985, (04): 109-120.

[9]侯莹, 伍彬彬, 邓云峰等. 集输管线安全管理与应急系统的研究[J]. 中国安全生产科学技术, 2011, 7(02): 98-103.

[10]洪流, 庄建斌, 刘冲. 油田集输管线安全管理与应急系统应用分析[J]. 中国石油和化工标准与质量, 2017, 37(14): 50-51.

[11]马团校. 硫化氢腐蚀与防护[J]. 全面腐蚀控制, 2021, 35(01): 91-93+96.

[12]石油化工湿硫化氢环境设备设计导则. 中华人民共和国工业和信息化部. 2017.

[13]徐超, 张伟. 含硫天然气井口高压抗硫仪表过程连接设计[J]. 石油化工建设, 2021, 43(S2): 99-101.

[14]Koopman R P, Cederwall R T, Ermak D L, et al. Analysis of Burro series 40m3 LNG spill experiments[J]. Journal of Hazardous Materials, 1982, 6(1): 43–83.

[15]Luketa H A, Koopman R P, Ermak D L. On the application of computational fluid dynamics codes for liquefied natural gas dispersion[J]. Journal of Hazardous Materials, 2007, 140(3): 504-517.

[16]庄学强. 大型液化天然气储罐泄漏扩散数值模拟[D]. 武汉: 武汉理工大学, 2012.

[17]Sun B, Utikar R P, Pareek V K, et al. Computational fluid dynamics analysis of liquefied natural gas dispersion for risk assessment strategies[J]. Journal of Loss Prevention in the Process Industries, 2013, 26(1): 117-128.

[18]Ikealumba W C, Wu H. Modeling of liquefied natural gas release and dispersion: Incorporating a direct computational fluid dynamics simulation method for LNG spill and pool formation[J]. Industrial & Engineering Chemistry Research, 2016, 55(6): 1778-1787.

[19]Hanna S, Britter R, Argenta E, et al. The Jack Rabbit chlorine release experiments: Implications odense gas removal from a depression and downwind concentrations[J]. Journal of Hazardous Materials, 2012, 12(406): 213-214.

[20]Zhang Y, Zhu J, Peng Y, et al. Experimental research of flow rate and diffusion behavior of nature gas leakage underwater[J]. Journal of Loss Prevention in the Process Industries, 2020, 65: 104119.

[21]周宁, 潘东, 冷明, 等. 油库罐区危险化学品的泄漏扩散实验[J]. 油气储运, 2012, 31(04): 263-266+328-329.

[22]Lee R L, Gresho P M, Chan S T, et al. A Three Dimensional, Finite Element Model for Simulating Heavier-Than-Air Gaseous Releases over Variable Terrain[J]. Air Pollution Modeling and Its Application II, 1983: 555-573.

[23]Li X J, Zhou R P, Konovessis D. CFD analysis of natural gas dispersion in engine room space based on multi-factor coupling[J]. Ocean Engineering, 2016, 111: 524–532.

[24]Liu A, Huang J, Li Z, et al. Numerical simulation and experiment on the law of urban natural gas leakage and diffusion for different building layouts[J]. Journal of Natural Gas Science & Engineering, 2018, 54: 1-10.

[25]杨冬冬, 陈国明, 付建民, 等. 海洋平台含硫化氢天然气泄漏爆炸连锁事故后果动态评估[J]. 化工进展, 2021, 40(11): 6393-6400.

[26]辛保泉, 卢卫, 张相建, 等. 硫化氢泄漏后果定量分析方法及指标响应规律[J]. 过程工程学报, 2018, 18(S1): 82-88.

[27]苏诗漫, 王浩丞, 史春艳, 等. 高含硫天然气管道泄漏H2S扩散规律研究[J]. 成都理工大学学报(自然科学版), 2024, 51(01): 130-136.

[28]孟庆浩, 杨子祯, 侯惠让, 等. 基于变施密特数的障碍环境气体扩散数值仿真[J]. 安全与环境学报, 2022, 22(02): 919-925.

[29]展宗红, 赵东风, 刘真真, 等. 基于CFD的城市埋地天然气管道泄漏扩散数值分析[J]. 工业安全与环保, 2020, 46(07): 8-11+21.

[30]周宁, 王伟天, 陈兵, 等. 石化管道丁烷气体泄漏扩散数值模拟[J]. 安全与环境工程, 2020, 27(02): 175-182.

[31]王强, 薛生, 郑晓亮, 等. 基于CFD-DEM耦合的埋地输气管道泄漏声场分析[J]. 振动与冲击, 2023, 42(18): 321-331.

[32]孙健飞, 李岩松, 梁永图. 输气管道泄漏速率模型研究进展[J]. 油气储运, 2020, 39(05): 512-518.

[33]梁俊丽, 孔维华, 费文华, 等. 基于复杂地形的高斯烟羽模型改进[J]. 环境工程学报, 2016, 10(06): 3125-3129.

[34]蔡凤英, 谈宗山, 孟赫, 等. 化工安全工程[M]. 北京: 科学出版社, 2001: 15-20.

[35]Rosen M A, Ao Y. Feasibility of using exergy to assess air pollution levels around a smokestack[J]. Journal of Shenyang Architectural and Civil Engineering Institute, 2005, 21(3): 73-76.

[36]朱红钧, 林元华, 马成学. 平坦地区含硫化氢集输管道的泄漏扩散模拟[J]. 西南石油大学学报(自然科学版), 2009, 31(06): 156-160.

[37]Britter R E, Mcquaid J. Workbook on the dispersion of dense gases[J]. Health and Executive, 1988, 11(2): 149-150.

[38]穆爽. 管窥美国管道安全[J]. 中国石油企业, 2004(06): 48-49.

[39]Yuhua D, Huilin G, Jing’en Z, et al. Evaluation of gas release rate through holes in pipelines[J]. Journal of Loss Prevention in the Process Industries, 2002, 15(6): 423-428.

[40]Montiel H, Vı́lchez J A, Casal J, et al. Mathematical modelling of accidental gas releases[J]. Journal of Hazardous Materials, 1998, 59(2-3): 211-233.

[41]Jo Y D, Ahn B J. A simple model for the release rate of hazardous gas from a hole on high-pressure pipelines[J]. Journal of hazardous materials, 2003, 97(1-3): 31-46.

[42]Sun L. Mathematical modeling of the flow in a pipeline with a leak[J]. Mathematics and computers in simulation, 2012, 82(11): 2253-2267.

[43]Liu A, Huang J, Li Z, et al. Numerical simulation and experiment on the law of urban natural gas leakage and diffusion for different building layouts[J]. Journal of Natural Gas Science and Engineering, 2018, 54: 1-10.

[44]Yuan F, Zeng Y, Khoo B C. A new real-gas model to characterize and predict gas leakage for high-pressure gas pipeline[J]. Journal of Loss Prevention in the Process Industries, 2022, 74: 104650.

[45]Yan M, Li J, Guan Y. Rupture Leakage Model for a Natural Gas Pipeline[J]. Journal of Pipeline Systems Engineering and Practice, 2023, 14(1): 04022060.

[46]Jing X, Ke L. A model for underground pipeline small leakage and its numerical solution[J]. Acta Petrolei Sinica, 2012, 33(3): 493.

[47]Zhang Y, Yang Y, Wu F, et al. Numerical investigation on pinhole leakage and diffusion characteristics of medium-pressure buried hydrogen pipeline[J]. International Journal of Hydrogen Energy, 2024, 51: 807-817.

[48]Zhou Z, Zhang J, Huang X, et al. Trend of soil temperature during pipeline leakage of high-pressure natural gas: Experimental and numerical study[J]. Measurement, 2020, 153: 107440.

[49]赵江平, 田辉. 近海复杂水体下海底输氢管道小孔泄漏扩散规律研究[J]. 中国安全生产科学技术, 2024, 20(02): 75-81.

[50]邓兵兵, 谢昱姝, 邓方, 等. 埋地燃气管道在土壤中小孔泄漏扩散特性研究[J]. 中国安全科学学报, 2023, 33(10): 160-166.

[51]刘爱华, 周欣莹, 许赐聪, 等. 城镇燃气管道小孔泄漏流量系数的定量研究[J/OL]. 安全与环境学报: 1-10[2024-04-07].

[52]马梅, 蒋仲安. 隧道内埋地燃气管道泄漏扩散规律研究[J]. 石油与天然气化工, 2022, 51(01): 132-137.

[53]蔺跃武, 刘典明. 天然气输送管道破裂泄漏量计算[J]. 化工设备与管道, 2003(05): 44-47.

[54]王小完, 南庆宾, 骆济豪, 等. 基于大孔模型的天然气管道泄漏火灾模拟分析[J]. 灾害学, 2022, 37(02): 49-53.

[55]罗威, 袁锐波, 陈有锦, 等. WOA下的修正后石油管道泄漏模型定位研究[J]. 重庆理工大学学报(自然科学), 2023, 37(09): 302-311.

[56]安建川. 输气管道泄漏模型不确定性因素敏感性分析[J]. 西南石油大学学报(自然科学版), 2021, 43(01): 149-156.

[57]岳云飞, 杨文斌, 严欣明, 等. 非金属管道微小泄漏动力学数值模拟和试验对比[J]. 工业安全与环保, 2020, 46(03): 7-12.

[58]申文东. 石油钻井井喷事故致因机理分析及预警系统研究[D]. 成都: 西南石油大学, 2017.

[59]Wang Q, Tang H, Yuan X, et al. An early warning system for oil security in China[J]. Sustainability, 2018, 10(1): 283-240.

[60]Yakubu R N. Understanding Early Warning Messaging about Climate Stressors in the Northern Region of Ghana[J]. Natural Hazard Review, 2020,21(2):05020003.

[61]Leonard G S, Johnston D M, Paton D, et al. Developing effective warning systems: Ongoing research at Ruapehu volcano, New Zealand[J]. Journal of Volcanology & Geothermal Research, 2008, 172(3): 199-215.

[62]Chang Y, Khan F, Ahmed S. A risk-based approach to design warning system for processing facilities[J]. Process Safety & Environment Protection, 2011, 89(5): 310-316.

[63]Peng Y, Zhang Y, Wei Y. Intelligent early-warning analysis of operational risks based on grey Kalman filter[J]. Journal of Intelligent & Fuzzy Systems, 2019, 37(5): 5801-5808.

[64]Liu S, Zhang P, Tang Q, et al. A novel safety early warning methodology for pipelines under landslide geological hazard[J]. Journal of Pipeline Systems Engineering and Practice, 2024, 15(1): 04023050.

[65]Fu J, Zou S, Sun J, et al. Self-adaptive early warning of undesirable gas-liquid flow pattern in offshore oil and gas pipeline-riser system[J]. Process Safety and Environmental Protection, 2024, 182: 254-278.

[66]Qiu J, Liang W, Zhang L, et al. The early-warning model of equipment chain in gas pipeline based on DNN-HMM[J]. Journal of Natural Gas Science and Engineering, 2015, 27: 1710-1722.

[67]Hu J, Chen C, Liu Z. Early warning method for overseas natural gas pipeline accidents based on FDOOBN under severe environmental conditions[J]. Process Safety and Environmental Protection, 2022, 157: 175-192.

[68]葛华, 方迎潮, 朱建平, 等. 穿越管道滑坡地表位移预警阈值及预警模型研究[J]. 人民长江, 2023, 54(01): 126-132.

[69]刘志强, 陈旭东. 化工园区有毒有害气体环境风险预警体系研究[J]. 资源节约与环保, 2021(09): 145-146.

[70]罗刚, 蒋学彬, 涂熹薇, 等. 油气田有毒气体泄漏预警与监测系统研究[J]. 钻采工艺, 2013, 36(06): 116-118.

[71]李玉星, 董邵灿, 胡其会, 等. 油气管道第三方破坏预警技术现状[J]. 中国安全生产科学技术, 2023, 19(S2): 115-121.

[72]林桔, 黄增威, 康世洋. 移动监测在化工园区有毒有害气体预警监测布点中的应用[J]. 广州化工, 2020, 48(20): 104-106.

[73]李兴华, 王媛媛, 袁子龙. 基于新一代信息技术的化工园区气体泄漏监测预警系统[J]. 中国安全生产科学技术, 2021, 17(S1): 10-14.

[74]GEXCON A S. FLACS V9.1 user’s manual[M]. Bergen: GEXCON AS, 2011.

[75]Bray, K. N. C. (1990). Studies of the turbulent burning velocity. Proceedings of the Royal Society of London, Series A, 431: 315-335.

[76]孙恩吉, 李红果, 王敏. 基于 Realizable k-ε湍流模型的氨气泄漏数值模拟研究[J]. 中国安全生产科学技术, 2017, 13(02): 114-118.

[77]李玉星, 姚光镇. 输气管道设计与管理[M]. 山东: 中国石油大学出版社, 2009.

[78]JO Y D, AHN B J. Analysis of hazard areas associated with high-pressure natural-gas pipelines[J]. Journal of Loss Prevention in the Process Industries, 2002, 15(3): 179-88.

[79]王江萍, 韩路. 基于Fluent的天然气管道泄漏传质传热研究[J]. 西安石油大学学报(自然科学版), 2020, 35(05): 108-15.

[80]李金鹏. 新编普通化学[M]. 郑州: 郑州大学出版社, 2017.

[81]王正龙, 张保稳. 生成对抗网络研究综述[J]. 网络与信息安全学报, 2021, 7(4): 68–85.

[82]朱静, 綦远磊, 辛培刚, 等. 多因素下居民室内天然气泄漏扩散数值模拟[J]. 消防科学与技术, 2021, 40(07): 1013-6.

[83]沈泽亚. 典型复杂下垫面突发大气污染事故污染物扩散与溯源技术研究[D]. 北京: 北京工业大学, 2022. 2022. 000633.

[84]SY 6137-2012, 含硫化氢油气生产和天然气处理装置作业安全技术规程[S].