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A liquid loading prediction method of gas pipeline based on machine learning

Petroleum Science 2022年第6期19卷 3004-3015页

作者： Bing-Yuan Hong Sheng-Nan Liu Xiao-Ping Li Di Fan Shuai-Peng Ji Si-Hang Chen Cui-Cui Li Jing Gong National-Local Joint Engineering Laboratory of Harbor Oil&Gas Storage and Transportation Technology/Zhejiang Provincial Key Laboratory of Petrochemical Pollution Control School of Petrochemical Engineering and EnvironmentZhejiang Ocean UniversityZhoushan316022China National Engineering Laboratory for Pipeline Safety/MOE Key Laboratory of Petroleum Engineering/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology China University of Petroleum-BeijingBeijing102249China China Huadian Group Energy Co. Ltd.North China BranchTianjin300280China China Petroleum Engineering&Construction Corp Beijing100120China

The liquid loading is one of the most frequently encountered phenomena in the transportation of gas pipeline,reducing the transmission efficiency and threatening the flow assurance.However,most of the traditional mechanism models are semi-empirical models,and have to be resolved under different working conditions with complex calculation process.The development of big data technology and artificial intelligence provides the possibility to establish data-driven models.This paper aims to establish a liquid loading prediction model for natural gas pipeline with high generalization ability based on machine learning.First,according to the characteristics of actual gas pipeline,a variety of reasonable combinations of working conditions such as different gas velocity,pipe diameters,water contents and outlet pressures were set,and multiple undulating pipeline topography with different elevation differences was established.Then a large number of simulations were performed by simulator OLGA to obtain the data required for machine learning.After data preprocessing,six supervised learning algorithms,including support vector machine(SVM),decision tree(DT),random forest(RF),artificial neural network(ANN),plain Bayesian classification(NBC),and K nearest neighbor algorithm(KNN),were compared to evaluate the performance of liquid loading prediction.Finally,the RF and KNN with better performance were selected for parameter tuning and then used to the actual pipeline for liquid loading location prediction.Compared with OLGA simulation,the established data-driven model not only improves calculation efficiency and reduces workload,but also can provide technical support for gas pipeline flow assurance.

关键词： liquid loading Data-driven method Machine learning Gas pipeline Multiphase flow

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On the Development of a Model for the Prediction of liquid loading in Gas Wells with an Inclined Section

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Fluid Dynamics & Materials Processing 2019年第5期15卷 527-544页

作者： Mengna Liao Ruiquan Liao Jie Liu Shuangquan Liu Li Li Xiuwu Wang Yang Cheng School of Petroleum Engineering Yangtze UniversityWuhan430100China Laboratory of Multiphase Pipe Flow of Gas Lift Innovation Center CNPC(Yangtze University)Wuhan430100China Oil and Gas Technology Research Institute of Changqing Oilfield Company Xi’an710000China

The ability to predict liquid loading in horizontal gas wells is of great importance for determining the time of drainage and optimizing the related production technology.In the present work,we describe the outcomes of experiments conducted using air-water mixtures in a horizontal well.The results show that the configuration with an inclined section is the most susceptible to liquid loading.Laboratory experiments in an inclined pipe were also conducted to analyze the variation of the critical gas flow rate under different angles,pressure and liquid volume(taking the equal liquid volume at inlet and outlet as the criterion for judging on the critical state).According to these results,the related angle of the inclined section ranges from 45°to 60°.Finally,a modified approach based on the Belfroid model has been used to predict the critical gas flow rate for the inclined section.After comparison with field data,this modified model shows an accuracy of 96%,indicating that it has better performances with respect to other models used in the past to predict liquid loading.

关键词： Horizontal gas well inclined section liquid loading critical gas flow rate air-water flow

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英文摘要

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石油与天然气化工 2012年第3期41卷 357-362页

The article presents abstracts of papers on chemical engineering of oil and gas, including a traceable calibration procedure for hydrocarbon dew point chilled mirror instruments and research direction and challenges f... 详细信息

关键词： acidizing air oxidation amine value ammonia or ammonium salt analysis anti-swelling agent anti-swelling performance anti-swelling rate anticorrosion coating ASP produced water average particle size bimodal calibration casing--damaged well catalyst cement chimney clay minerals CO2 comparison research complex gas components core damage corrosion inhibitor CPS crude sewage desulphurization determination diversion ejector energy development energy efficiency benchmarking evaluation FCC foam drainage foam mass foam stabilizer foamed acid foaming agent function design Gas field gathering pipelines H2S high temperature high-sulfur hydrocarbon dew point hydrocarbon dew point chilled mirror instruments incinerator inspection integrated equipment kinetic hydrateinhibitors LaFeO3 liquefied petroleum gas dispenser liquid loading load low permeability and low pressure LPG mechanical strength methane methane hydrates metrological verification microbial flocculant multifunctional activated acid natural gas natural gas desulfurization natural gas hydrate network management platform new technology offshore oilfield oil yield oilfield application operation operation points parameter optimization performance evaluation perovskite oxide compound plugging plugging causes analysis polymer polymer-surfactant displacement pore distribution prevention measures removal rate of solid suspensions replacement rate response of performance retarder rotating-strip-port round-port scale inhibitor scaling screening silica gel slight expansion SO2 solid-liquid separation treatment solubilization sour gas field sulfur recovery system construction tail gas treatment hydro-treating heater technical summary thermodynamics titration method traceability transport pipeline treatment technology uncertainty of measurement viscosity waste drilling fluid water content water injection water producing water sensitivity damage water-sensitivity

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