On the Development of a Model for the Prediction of Liquid Loading in Gas Wells with an Inclined Section

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.

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

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.

A new model for predicting the critical liquid-carrying velocity in inclined gas wells

Based on the assumption of gas-liquid stratified flow pattern in inclined gas wells,considering the influence of wettability and surface tension on the circumferential distribution of liquid film along the wellbore wall,the influence of the change of the gas-liquid interface configuration on the potential energy,kinetic energy and surface free energy of the two-phase system per unit length of the tube is investigated,and a new model for calculating the gas-liquid distribution at critical conditions is developed by using the principle of minimum energy.Considering the influence of the inclination angle,the calculation model of interfacial friction factor is established,and finally closed the governing equations.The interface shape is more vulnerable to wettability and surface tension at a low liquid holdup,resulting in a curved interface configuration.The interface is more curved when the smaller is the pipe diameter,or the smaller the liquid holdup,or the smaller the deviation angle,or the greater gas velocity,or the greater the gas density.The critical liquid-carrying velocity increases nonlinearly and then decreases with the increase of inclination angle.The inclination corresponding to the maximum critical liquid-carrying velocity increases with the increase of the diameter of the wellbore,and it is also affected by the fluid properties of the gas phase and liquid phase.The mean relative errors for critical liquid-carrying velocity and critical pressure gradient are 1.19%and 3.02%,respectively,and the misclassification rate is 2.38%in the field trial,implying the new model can provide a valid judgement on the liquid loading in inclined gas wells.

Research and Development of Gadolinium Loaded Liquid Scintillator for Daya Bay Neutrino Experiment

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.

Study on the Optimization of Agaricus bisporus Liquid Spawn Production Process

On the basis of single-factor experiment, an orthogonal experiment was carried out with culture temperature, initial pH, inoculation amount and liquid loading volume as factors at three levels. With the mycelium biomass as an index, the optimal secondary liquid seed culture conditions were obtained： culture temperature 27 ℃, initial pH 6.5, inoculation amount 13%, liquid loading volume 100 ml. Under the optimized conditions, mycelium biomass reached the maximum.

Mode selection of Lamb waves for the evaluation of solid plates with liquid loading

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.

Phosphorus recovery from biogas fermentation liquid by Ca-Mg loaded biochar

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.