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 mech...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.展开更多
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 o...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.展开更多
With complicated formation mechanisms,liquid loading in gas wells during gasfield development may significantly affect the productivity of gas wells and the ultimate recovery rate.Dynamic monitoring data of the Samand...With complicated formation mechanisms,liquid loading in gas wells during gasfield development may significantly affect the productivity of gas wells and the ultimate recovery rate.Dynamic monitoring data of the Samandepe Gasfield in Turkmenistan shows that liquid loading can be found extensively in gas wells.Their formation mechanisms and negative impacts on gasfield development severely restrict the productivity enhancement of this gasfield.With their origins taken into consideration,liquid loads in gas wells were classified into three types:formation water,condensed liquid,and external liquid.By using the hydrostatic pressure gradient method and through PLT monitoring,properties of liquid loads in the Samandepe Gasfield were determined.In addition,formation mechanisms related to liquid loading in gas wells were obtained through analyses of critical fluid-carrying capacities and by using gas-reservoir production data.The following findings were obtained.Liquid loading was commonly found in this gas well with majority of reservoir formations in lower well intervals flooded.However,the formation mechanisms for these liquid loads are different from those of other gasfields.Due to long-term shut-down of gas wells,killing fluids precipitated and pores in lower reservoir formations were plugged.As a result,natural gas had no access to boreholes,killing fluids were impossibly carried out of the borehole.Instead,the killing fluid was detained at the bottomhole to generate liquid load and eliminate the possibility of formation water coning.Moreover,since the gasfield was dominated by block reservoirs with favorable physical properties and connectivity,impacts of liquid load on gasfield development were insignificant.Thus,to enhance the recovery rate of the Samandepe Gasfield significantly,it is necessary to expand the gasfield development scale and strengthen the development of marginal gas reservoirs.展开更多
This paper studies the mode selection of Lamb waves for evaluating solid plates with liquid loading. For this purpose, the Lamb wave selected should have the features such as zero normal displacement components at the...This paper studies the mode selection of Lamb waves for evaluating solid plates with liquid loading. For this purpose, the Lamb wave selected should have the features such as zero normal displacement components at the plate surface in contact with liquid, small dispersion, and maximum group velocity. It is found that when the phase velocity of Lamb wave is equal to the longitudinal wave velocity of the plate material, its normal displacement at the plate surface is always zero. Through the numerical analyses, the specific S2 Lamb wave that has zero normal displacement component at the plate surface, small dispersion and maximum group velocity compared with the other Lamb waves has been found. With respect to the specific S2 Lamb wave, some experimental examinations have been carried out. It is found that the liquid loading on the plate surface has less influence on the specific S2 Lamb wave signal but it can effectively eliminate the other signals. Moreover, the specific S2 Lamb wave selected exhibits the capability of detecting multiple defects in the solid plate with the liquid loading. It can be concluded that the specific S2 Lamb wave selected is suitable for the evaluation of solid plates with liquid loading.展开更多
Shortage in phosphorus （P） resources and P wastewater pollution is considered as a serious problem worldwide. The application of modified biochar for P recovery from wastewater and reuse of recovered P as agricultur...Shortage in phosphorus （P） resources and P wastewater pollution is considered as a serious problem worldwide. The application of modified biochar for P recovery from wastewater and reuse of recovered P as agricultural fertilizer is a preferred process. This work aims to develop a calcium and magnesium loaded biochar （Ca-Mg/biochar） application for P recovery from biogas fermentation liquid. The physico-chemical characterization, adsorption efficiency, adsorption selectivity, and postsorption availability of Ca-Mg/biochar were investigated. The synthesized Ca-Mg/biochar was rich in organic functional groups and in CaO and MgO nanoparticles. With the increase in synthesis temperature, the yield decreased, C content increased, H content decreased, N content remained the same basically, and BET surface area increased. The P adsorption of Ca-Mg/biochar could be accelerated by nano-CaO and nano-MgO particles and reached equilibrium after 360min. The process was endothermic, spontaneous, and showed an increase in the disorder of the solid-liquid interface. Moreover, it could be fitted by the Freundlich model. The maximum P adsorption amounts were 294.22, 315.33, and 326.63 mg/g. The P adsorption selectivity of Ca-Mg/biochar could not be significantly influenced by the typical pH level of biogas fermentation liquid. The nano-CaO and nano-MgO particles of Ca-Mg/biochar could reduce the negative interaction effects of coexisting ions. The P releasing amounts of postsorption Ca-Mg/biochar were in the order of Ca-Mg/B600 〉 Ca-Mg/B4S0 〉 Ca-Mg/B300. Results revealed that postsorption Ca-Mg/biochar can continually release P and is more suitable for an acid environment.展开更多
Daya Bay reactor anti-neutrino experiment is designed to measure an important parameter, θ13, of neutrino by using anti-neutrino created by Daya Bay and Ling Ao nuclear power plants. The experiment need 200 tonnes ga...Daya Bay reactor anti-neutrino experiment is designed to measure an important parameter, θ13, of neutrino by using anti-neutrino created by Daya Bay and Ling Ao nuclear power plants. The experiment need 200 tonnes gadolinium loaded liquid scintillator (Gd-LS) as target. The purpose of this research is to develop suitable Gd-LS candidates for this experiment, which should have long attenuation length, high light yield, long term stability, and should be compatible with the material used to build the containers. Two kinds of Gd-LS were developed using carboxylic acids 2-ethylhexanoic acid (EHA) and 3, 5, 5-trimethylhexanoic acid (TMHA) as complexing ligands and mesitylene and linear alkyl benzene (LAB) as scintillator solvents. Four Gd-LS samples with different Gd content and complexing ligands were prepared and characterized. The relative light yields and the stabilities of all samples are satisfying, and the values of attenuation length show that TMHA is a better ligand than EHA.展开更多
With a Geant4 software package based on the Monte Carlo method, a multi-cell 4π detection system is designed, which consists of 40 Gadolinium-loaded liquid scintillation detectors. These detectors, associated with a ...With a Geant4 software package based on the Monte Carlo method, a multi-cell 4π detection system is designed, which consists of 40 Gadolinium-loaded liquid scintillation detectors. These detectors, associated with a fission chamber in its geometrical center, constitute a platform. This platform is mainly used for the measurement of a fissionable nucleus(n, 2n) reaction cross section. In order to properly determine the experimental set-up, we carry out a systematic numerical simulation using our model which is established by the Geant4 software package. This work provides rich and valuable reference data for experiments on the fissionable nucleus(n, 2n) cross section measurement in the future.展开更多
The thermo-order-mechanical behaviors of liquid crystal elastomers （LCEs） under biaxial loading are studied in this paper. Inverse method for nonlinear elastic problems is utilized by imposing biaxial stretching to ...The thermo-order-mechanical behaviors of liquid crystal elastomers （LCEs） under biaxial loading are studied in this paper. Inverse method for nonlinear elastic problems is utilized by imposing biaxial stretching to thin rectangular samples. Neo-classical elastic energy is used together with the Landau-de Gennes nematic free energy. Under plane stress assumptions, the constitutive equations are derived. Due to the possible reorientations of the liquid crystal molecules induced by the imposed biaxial loading, the in-plane nonlinear stress-strain relations can have different expressions depending on which loading axis will have the largest effective principal strain. And the free energy is a multi-well non-convex potential function. As shown by some typical loading paths, the LCE samples will exhibit an anisotropic nonlinear elastic behavior, as long as the loading has not induced a reorientation of the liquid crystal molecules. When this did occur, jumps of stresses could take place for dead loadings due to the losing of stability.展开更多
In the mid-to-late stages of gas reservoir development,liquid loading in gas wells becomes a common challenge.Plunger lift,as an intermittent production technique,is widely used for deliquification in gas wells.With t...In the mid-to-late stages of gas reservoir development,liquid loading in gas wells becomes a common challenge.Plunger lift,as an intermittent production technique,is widely used for deliquification in gas wells.With the advancement of big data and artificial intelligence,the future of oil and gas field development is trending towards intelligent,unmanned,and automated operations.Currently,the optimization of plunger lift working systems is primarily based on expert experience and manual control,focusing mainly on the success of the plunger lift without adequately considering the impact of different working systems on gas production.Additionally,liquid loading in gas wells is a dynamic process,and the intermittent nature of plunger lift requires accurate modeling;using constant inflow dynamics to describe reservoir flow introduces significant errors.To address these challenges,this study establishes a coupled wellbore-reservoir model for plunger lift wells and validates the computational wellhead pressure results against field measurements.Building on this model,a novel optimization control algorithm based on the deep deterministic policy gradient(DDPG)framework is proposed.The algorithm aims to optimize plunger lift working systems to balance overall reservoir pressure,stabilize gas-water ratios,and maximize gas production.Through simulation experiments in three different production optimization scenarios,the effectiveness of reinforcement learning algorithms(including RL,PPO,DQN,and the proposed DDPG)and traditional optimization algorithms(including GA,PSO,and Bayesian optimization)in enhancing production efficiency is compared.The results demonstrate that the coupled model provides highly accurate calculations and can precisely describe the transient production of wellbore and gas reservoir systems.The proposed DDPG algorithm achieves the highest reward value during training with minimal error,leading to a potential increase in cumulative gas production by up to 5%and cumulative liquid production by 252%.The DDPG algorithm exhibits robustness across different optimization scenarios,showcasing excellent adaptability and generalization capabilities.展开更多
基金supported by the National Science and Technology Major Project of China(2016ZX05066005-001)Zhejiang Province Key Research and Development Plan(2021C03152)Zhoushan Science and Technology Project(2021C21011)
文摘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.
基金The authors like to express appreciation to the support given by the major national science and technology special project:Research and Application of Key Technologies for Oil Production and Gas Recovery in Complex Carbonate Reservoirs in Central Asia and Middle East(2017ZX05030-005)Scientific Research Startup Fund Project for Introducing Talent of Kunming University of Science and Technology(KKSY20180502).
文摘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.
基金CNPC Project“Research and Application of Key Development Technologies in Turkmenistan Amu Darya Right Bank 16.5 Billion Cubic Meters Natural Gas Production Enhancement”(No.2011E-2505)National Key S&T Project“Natural Gas Development Demonstration Project in the Middle Area of Amu Darya Right Bank”(No.2011ZX05059).
文摘With complicated formation mechanisms,liquid loading in gas wells during gasfield development may significantly affect the productivity of gas wells and the ultimate recovery rate.Dynamic monitoring data of the Samandepe Gasfield in Turkmenistan shows that liquid loading can be found extensively in gas wells.Their formation mechanisms and negative impacts on gasfield development severely restrict the productivity enhancement of this gasfield.With their origins taken into consideration,liquid loads in gas wells were classified into three types:formation water,condensed liquid,and external liquid.By using the hydrostatic pressure gradient method and through PLT monitoring,properties of liquid loads in the Samandepe Gasfield were determined.In addition,formation mechanisms related to liquid loading in gas wells were obtained through analyses of critical fluid-carrying capacities and by using gas-reservoir production data.The following findings were obtained.Liquid loading was commonly found in this gas well with majority of reservoir formations in lower well intervals flooded.However,the formation mechanisms for these liquid loads are different from those of other gasfields.Due to long-term shut-down of gas wells,killing fluids precipitated and pores in lower reservoir formations were plugged.As a result,natural gas had no access to boreholes,killing fluids were impossibly carried out of the borehole.Instead,the killing fluid was detained at the bottomhole to generate liquid load and eliminate the possibility of formation water coning.Moreover,since the gasfield was dominated by block reservoirs with favorable physical properties and connectivity,impacts of liquid load on gasfield development were insignificant.Thus,to enhance the recovery rate of the Samandepe Gasfield significantly,it is necessary to expand the gasfield development scale and strengthen the development of marginal gas reservoirs.
基金supported by the National Natural Science Foundation of China(Grant No.11274388)
文摘This paper studies the mode selection of Lamb waves for evaluating solid plates with liquid loading. For this purpose, the Lamb wave selected should have the features such as zero normal displacement components at the plate surface in contact with liquid, small dispersion, and maximum group velocity. It is found that when the phase velocity of Lamb wave is equal to the longitudinal wave velocity of the plate material, its normal displacement at the plate surface is always zero. Through the numerical analyses, the specific S2 Lamb wave that has zero normal displacement component at the plate surface, small dispersion and maximum group velocity compared with the other Lamb waves has been found. With respect to the specific S2 Lamb wave, some experimental examinations have been carried out. It is found that the liquid loading on the plate surface has less influence on the specific S2 Lamb wave signal but it can effectively eliminate the other signals. Moreover, the specific S2 Lamb wave selected exhibits the capability of detecting multiple defects in the solid plate with the liquid loading. It can be concluded that the specific S2 Lamb wave selected is suitable for the evaluation of solid plates with liquid loading.
基金supported by the Specialized Research Fund for the Doctoral Program of Higher Education of China (No. 20120008120013)the National Natural Science Foundation of China (No. 31401944)+2 种基金the Beijing Natural Science Foundation (No. 6144026)the China Scholarship Council (No. 201206355006)the Chinese Universities Scientific Fund of China Agricultural University (No. 2011JS169)
文摘Shortage in phosphorus （P） resources and P wastewater pollution is considered as a serious problem worldwide. The application of modified biochar for P recovery from wastewater and reuse of recovered P as agricultural fertilizer is a preferred process. This work aims to develop a calcium and magnesium loaded biochar （Ca-Mg/biochar） application for P recovery from biogas fermentation liquid. The physico-chemical characterization, adsorption efficiency, adsorption selectivity, and postsorption availability of Ca-Mg/biochar were investigated. The synthesized Ca-Mg/biochar was rich in organic functional groups and in CaO and MgO nanoparticles. With the increase in synthesis temperature, the yield decreased, C content increased, H content decreased, N content remained the same basically, and BET surface area increased. The P adsorption of Ca-Mg/biochar could be accelerated by nano-CaO and nano-MgO particles and reached equilibrium after 360min. The process was endothermic, spontaneous, and showed an increase in the disorder of the solid-liquid interface. Moreover, it could be fitted by the Freundlich model. The maximum P adsorption amounts were 294.22, 315.33, and 326.63 mg/g. The P adsorption selectivity of Ca-Mg/biochar could not be significantly influenced by the typical pH level of biogas fermentation liquid. The nano-CaO and nano-MgO particles of Ca-Mg/biochar could reduce the negative interaction effects of coexisting ions. The P releasing amounts of postsorption Ca-Mg/biochar were in the order of Ca-Mg/B600 〉 Ca-Mg/B4S0 〉 Ca-Mg/B300. Results revealed that postsorption Ca-Mg/biochar can continually release P and is more suitable for an acid environment.
基金the Natural Science Foundation of China (NSFC 10535050)
文摘Daya Bay reactor anti-neutrino experiment is designed to measure an important parameter, θ13, of neutrino by using anti-neutrino created by Daya Bay and Ling Ao nuclear power plants. The experiment need 200 tonnes gadolinium loaded liquid scintillator (Gd-LS) as target. The purpose of this research is to develop suitable Gd-LS candidates for this experiment, which should have long attenuation length, high light yield, long term stability, and should be compatible with the material used to build the containers. Two kinds of Gd-LS were developed using carboxylic acids 2-ethylhexanoic acid (EHA) and 3, 5, 5-trimethylhexanoic acid (TMHA) as complexing ligands and mesitylene and linear alkyl benzene (LAB) as scintillator solvents. Four Gd-LS samples with different Gd content and complexing ligands were prepared and characterized. The relative light yields and the stabilities of all samples are satisfying, and the values of attenuation length show that TMHA is a better ligand than EHA.
基金Supported by National Natural Science Foundation of China(No.11375063)the Fundamental Research Funds for the Central Universities(No.13QN59)
文摘With a Geant4 software package based on the Monte Carlo method, a multi-cell 4π detection system is designed, which consists of 40 Gadolinium-loaded liquid scintillation detectors. These detectors, associated with a fission chamber in its geometrical center, constitute a platform. This platform is mainly used for the measurement of a fissionable nucleus(n, 2n) reaction cross section. In order to properly determine the experimental set-up, we carry out a systematic numerical simulation using our model which is established by the Geant4 software package. This work provides rich and valuable reference data for experiments on the fissionable nucleus(n, 2n) cross section measurement in the future.
基金supported by National Natural Science Foundation of China (Nos. 11072062 and 11172068)the Research Fund for the Doctoral Program of Higher Education of China (No. 20110071110013)
文摘The thermo-order-mechanical behaviors of liquid crystal elastomers （LCEs） under biaxial loading are studied in this paper. Inverse method for nonlinear elastic problems is utilized by imposing biaxial stretching to thin rectangular samples. Neo-classical elastic energy is used together with the Landau-de Gennes nematic free energy. Under plane stress assumptions, the constitutive equations are derived. Due to the possible reorientations of the liquid crystal molecules induced by the imposed biaxial loading, the in-plane nonlinear stress-strain relations can have different expressions depending on which loading axis will have the largest effective principal strain. And the free energy is a multi-well non-convex potential function. As shown by some typical loading paths, the LCE samples will exhibit an anisotropic nonlinear elastic behavior, as long as the loading has not induced a reorientation of the liquid crystal molecules. When this did occur, jumps of stresses could take place for dead loadings due to the losing of stability.
基金support from Science Foundation of China University of Petroleum,Beijing(No.2462023YJRC019)National Natural Science Foundation of China(No.52204059)Key Core Technology Research Project Foundation of PetroChina Group(No.2023ZG18).
文摘In the mid-to-late stages of gas reservoir development,liquid loading in gas wells becomes a common challenge.Plunger lift,as an intermittent production technique,is widely used for deliquification in gas wells.With the advancement of big data and artificial intelligence,the future of oil and gas field development is trending towards intelligent,unmanned,and automated operations.Currently,the optimization of plunger lift working systems is primarily based on expert experience and manual control,focusing mainly on the success of the plunger lift without adequately considering the impact of different working systems on gas production.Additionally,liquid loading in gas wells is a dynamic process,and the intermittent nature of plunger lift requires accurate modeling;using constant inflow dynamics to describe reservoir flow introduces significant errors.To address these challenges,this study establishes a coupled wellbore-reservoir model for plunger lift wells and validates the computational wellhead pressure results against field measurements.Building on this model,a novel optimization control algorithm based on the deep deterministic policy gradient(DDPG)framework is proposed.The algorithm aims to optimize plunger lift working systems to balance overall reservoir pressure,stabilize gas-water ratios,and maximize gas production.Through simulation experiments in three different production optimization scenarios,the effectiveness of reinforcement learning algorithms(including RL,PPO,DQN,and the proposed DDPG)and traditional optimization algorithms(including GA,PSO,and Bayesian optimization)in enhancing production efficiency is compared.The results demonstrate that the coupled model provides highly accurate calculations and can precisely describe the transient production of wellbore and gas reservoir systems.The proposed DDPG algorithm achieves the highest reward value during training with minimal error,leading to a potential increase in cumulative gas production by up to 5%and cumulative liquid production by 252%.The DDPG algorithm exhibits robustness across different optimization scenarios,showcasing excellent adaptability and generalization capabilities.
