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.

Contribution of tuned liquid column gas dampers to the performance of offshore wind turbines under wind, wave, and seismic excitations

The main intention of the present study is to reduce wind, wave, and seismic induced vibrations of jacket- type offshore wind turbines （JOWTs） through a newly developed vibration absorber, called tuned liquid column gas damper （TLCGD）. Using a Simulink-based model, an analytical model is developed to simulate global behavior of JOWTs under different dynamic excitations. The study is followed by a parametric study to explore efficiency of the TLCGD in terms of nacelle acceleration reduction under wind, wave, and earthquake loads. Study results indicate that optimum frequency of the TLCGD is rather insensitive to excitation type. In addition, while the gain in vibration control from TLCGDs with higher mass ratios is generally more pronounced, heavy TLCGDs are more sensitive to their tuned frequency such that ill-regulated TLCGD with high mass ratio can lead to destructive results. It is revealed that a well regulated TLCGD has noticeable contribution to the dynamic response of the JOWT under any excitation.

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.

Critical impeller speeds for a gas-inducing stirring tank loaded with solid particles

The influence of solid particles size,density and loading on the critical gas-inducing impeller speed was investigated in a gas–liquid–solid stirring tank equipped with a hollow Rushton impeller.Three types of solid particles,hollow glass beads with diameters of 300 μm,200 μm,100 μm,and 60 μm,silica gel and desalting resin,were used.It was found that the adding solid particles would change the critical impeller speed.For hollow glass beads and silica gel,whose relative densities were less than or equal to 1.5,the critical impeller speeds increased with the solid loading before reaching the maximum values,and then decreased to a value even lower than that without added solids.The size of the solids also had apparent influence on the critical impeller speed,and larger solid particles correspond to a smaller critical impeller speed.The experimental data also showed that the gasinducing was beneficial to the suspension of the solid particles.

Predicting a, c indices in reversed-phase high-performance liquid chromatography (RP-HPLC) from Kovats index in gas chromatography (GC)

KOVATS index is the most precise index system reflecting the interaction between the molecules of solutes and stationary phase in gas chromatography at present. Large quantity of Kovats in dex data have been published. It is a good way to use Kováts index in gas chromatography to predict the retention value in liquid chromatography, which is significant in theory and apphcation.

气井井筒积液与排液周期预报技术

在气田开发过程中,由于地层水和天然气中的凝析水的影响,常会造成气井井筒积液,在井底产生回压,影响气井正常生产,积液严重时会压死气井。根据气井积液规律和气藏开发压力递减规律,通过计算气井向井流和油管流出动态,确定气井日产气量、日产水、日产油,并进行井筒积液判断与排液周期预测;对于气井未来流入预测,引入了极限视采气指数的概念;在理论模型和方法研究的基础上,编制了气井井筒积液分析软件;计算表明,气藏在开发过程中,随着地层压力下降,排液周期会越来越短。

深层凝析气井临界携液模型优化研究

以Turner模型为代表的临界携液流量模型在预测积液位置和表面张力方面均存在不足,导致积液预测结果与凝析气井实际情况偏差较大。为提高积液预测精度,考虑临界携液流量和表面张力沿井筒的差异分布,取井筒中临界携液流量的最大值作为积液判断标准,并根据不同温度、压力条件计算对应的表面张力。同时,考虑井筒中存在气体、凝析油和地层水三相,建立凝析气井井筒温压耦合计算模型。实例验证表明,改进后的4种临界携液流量模型与原始模型相比,均提高了积液预测精度,其中改进的李闽模型预测精度提高的幅度最大,预测精度最高,适合于雅克拉—大涝坝深层凝析气井的积液预测。该研究对现场开展积液判断和排液工艺优选具有指导意义。

苏里格气田积液气井产能的快速评价方法

苏里格气田大部分气井生产过程中会出现井筒积液现象,需要开展大量的产能测试,指导排水采气措施优化工作。为了降低气井产能测试成本,提高气田开发效益,通过开展井筒积液气井套压变化规律分析,明确了气井积液初期和井筒液面到达节流器时套压变化特征,结合节流器下入深度计算出井筒积液的液柱高度,在此基础上提出了一种利用井口生产数据计算井筒积液气井井底流压和气井产能的快速方法。以苏里格气田井筒积液气井产能预测为例,该方法预测产能与实际产能误差为4.2%~9.6%,每口气井可以节省产能测试费用30余万元。该产能评价方法充分考虑了井筒积液对井底流压计算的影响,测试结果不仅可以满足现场精度要求,而且能有效降低产能测试成本。

气举举升效率与井筒流态影响关系研究

目前，很多气田都存在气水同产的问题，其中多数气井都受到储层压力过低和井底积液双重因素的影响，这个问题在低渗透深层气井开发中显得尤为突出。随着气井开采年限的增加，地层能量衰减，气体流动速度不断下降，在井筒中会经历多种流态变化，其中段塞流向环雾流转换的过程中会经历一种中间流态——过渡流。通过可靠的实验证明过渡流是一种极不稳定的流动状态，严重影响气举工艺的携液效率，了解并能准确预测过渡流态的发生，可以对优化气举排液设计提供有效帮助。此外，通过对现场及实验室数据的分析，总结了一套预测过渡流发生的简单方法。该方法利用井口实际注入气体流速随深度变化曲线与Turner模型计算的临界携液速度随深度变化曲线为主要依据，依靠两条线的关系判断过渡流发生的可能性。现场实例验证该方法可以有效判断过渡流发生的时间，由此可以及时制定或改变相应的措施予以避免。

深层凝析气藏气井积液预测方法优选

积液问题严重影响雅克拉—大涝坝深层凝析气藏气井的正常生产,常用积液预测方法在雅克拉—大涝坝深层凝析气藏的适用性亟需进一步论证。对临界携液流量法和动能因子法的适用性进行了评价与优选研究。阐述各积液预测方法的基本原理与差异,考虑临界携液流量和表面张力沿井筒的动态分布,对原始临界携液模型进行改进;通过误差分析,分别选取适合于该气藏高、低气液比气井的井筒温压计算模型;通过实例分析,优选出适用于深层凝析气藏气井的积液预测方法。结果表明,修正的拟单相流温压耦合计算模型适用于该气藏高气液比气井井筒温压计算,Hagedorn-Brown方法和Hasan方法适用于低气液比气井井筒温压计算。改进的临界携液流量模型与原始模型相比,提高了积液预测精度。改进的李闽模型和界限值取为6的动能因子法积液预测精度较高,适用于雅克拉—大涝坝深层凝析气藏气井的积液预测。

气井积液量预测模型改进

随着国内老气区开发的不断深入,气井出水积液问题日益严重.为了对气井积液严重程度进行准确评估,并为气井排水采气工艺方式的选择及方案设计提供可靠积液量预测参数,在对原预测模型存在问题系统分析的基础上,综合考虑多种因素,建立了油管内积液量和环空积液量预测新模型.新模型理论依据充分,有效解决了原模型计算过程中由参数经验取值带来的不确定性.通过13口探液面气井的对比分析,新模型计算值与实测值吻合程度较好,计算精度较高.

涩北气田排水采气优选模式

针对柴达木盆地涩北气田所面临的气井井底积液、产水导致产量迅速递减的问题,从准确把握气井排水采气时机、优选经济有效的排水采气方式出发,结合涩北气田生产动态,综合考虑动能因子、积液高度、油压、日产水以及油压、套压压差等多种因素准确诊断了气井积液的状况;分析了涩北一号气田递减阶段气井日产气量和水气比等生产数据的变化规律,根据多项管流井底压力计算理论、临界流量计算模型及涩北气田实际的采气油管尺寸,研制出了排水采气方式选择控制图,并建立了涩北气田排水采气优选模式;回归出了相应的计算公式,预测了涩北一号气田大规模进入优选管柱排水及泡排排水采气时期的具体时机,由于涩北气田属于次活跃与不活跃水驱气藏,水气比上升缓慢,除少数离边水比较近的井外,在整个开发期内不会大规模进入气举排水开采期。

破损舰船运动与波浪载荷预报方法

为了研究舰船舱室破损对船体运动与波浪载荷的影响,采用三维频域势流理论,计算了发生第二类舱室破损后舰船在斜浪规则波上的运动与垂向弯矩。以一典型破损情况为例,计算了船舶破损后的浮态及稳性,并与破损前进行了比较,结果显示,横摇运动及垂向弯矩明显增加,而其它5个自由度运动则有所减小。基于船舶静力学原理,分析了舰船破损对浮态及稳性的影响。最后,使用格林函数法研究了舱室进水导致的液舱晃荡,结果表明,液舱晃荡附加质量在某些频率附近有明显的共振效应,必须通过阻尼系数考虑流体粘性的影响,避免产生非物理结果。

气井积液理论预测及室内实验验证

气井中的液体逐渐积累会导致气井产量下降,生产时间缩短,甚至停产。为了揭示气井积液的机理,预测气井积液的临界携液流量,结合理论研究和室内实验开展工作,基于牛顿内摩擦定律气液两相力学平衡建立了液膜反转新模型,反转临界点采用最小气液界面剪力方法计算;该模型考虑了倾斜角对液膜厚度的影响,并基于实验数据改进了气液界面摩擦系数,与前人模型相比准确度更高;将改进模型的结果与室内模拟实验值相比,最大误差不超过10%,可用于气井临界携液流量的计算。模拟实验和理论成果加深了气井积液现象的认识,对积液的原因做出了解释,所提出的预测模型有助于预防气井积液带来的危害,增加了气井产量和经济效益。

苏里格气田井下节流气井积液量预测方法及应用

苏里格气田属于典型的致密砂岩气藏,储层具有典型的"低渗透、低孔隙、低丰度、强非均质性"的特征,区块气井生产主要采用安装井下节流器、多井串接和集气站计量等简化的地面设施以节约成本。因此,对于井下安装节流器气井测试井筒积液情况需拔取节流器,而且井筒液面随生产动态变化,常规的井筒积液测试成本较高、影响气井产量,难以大规模使用。如何对节流器气井积液情况准确地预测尤为关键,直接影响气井排水采气措施的实施。针对以上情况,以苏里格气田X1区块为例,利用气井常规生产资料,结合节流器气嘴尺寸、下深等参数,提出产量比较法(实际产量与理论产量对比分析法)和油、套压差预测法,并结合现场测试数据进行方法验证,准确地预测了X1区块气井积液量,为气井精细措施管理提供了重要的依据。

一种低渗碳酸盐岩气藏气井积液的早期判识方法

岩溶风化壳型低渗碳酸盐岩气藏受沉积成岩作用影响,储层非均质性强,一旦含水,开发难度极大。以鄂尔多斯盆地靖边气田为例,目前该类气藏整体进入开发中后期,因现有方法判识滞后且精度较低,气井气液流动状态难以及时准确识别,面临单井产量低、气井积液产水等问题,造成剩余储量动用难、气藏采收率低。根据低渗碳酸盐岩气藏渗流机理与生产特征,提出了基于常规生产资料的井筒积液早期判识技术,并在此基础上改进了积液产水气井生产制度以及气水动态分布预测技术思路,细化了“动态控水、地质避水”的剩余储量动用策略。靖边气田据此实施了“气水流动状态判识+生产制度动态优化+气水分布预测”的一体化技术流程,使老井控水、新井防水能力切实提升,典型产水单元水气比趋于稳定、连续生产气井比例提升20%,近3年年均增产气量1.8×10^(8) m^(3),年均提高采收率0.1%。

页岩气水平井全井筒临界携液流量模型

目前的临界携液流量模型均未完整反映页岩气井的复杂井身结构和返排液量变化特征,无法准确预测页岩气水平井积液。为此,通过对液滴动力学和能量分析,综合考虑井筒产液量、液滴变形和造斜率变化引起的液滴能量损失,建立了页岩气井全井筒临界携液流量模型。根据最大稳定变形液滴能量平衡关系,确定了最大稳定变形液滴长轴长度;选取了适用于页岩气水平井的曳力系数和表面张力公式;根据误差分析优选了Mukherjee-Brill两相流模型计算页岩气水平井井筒压力分布。实例分析表明,与现有临界携液流量模型相比,新模型对于页岩气水平井的积液预测符合率最高,预测精度达92.3%。新模型可以准确预测积液井和接近积液井,对不积液井的积液预测精度也能满足现场应用要求,可以有效指导页岩气井积液判断与排采工艺选择。

基于环雾流理论的气井临界流速预测模型

井筒积液是伴随气井生产的常见现象,积液会导致气井产量降低,严重时甚至会使得气井停产。精确的积液预测有助于及时采取措施以减少积液带来的危害,而临界气体流速是气井积液预测的关键。回顾了气井积液预测的相关研究,指出了最小压降模型、液滴模型的局限性,基于现有实验观察认为液膜模型有较好的适用性。考虑到斜井中液膜周向不均匀分布及气相核心中液滴夹带,提出了更符合实际的环雾流模型用于不同管径、不同井斜角下的气井积液预测。基于以往室内实验数据和现场生产数据,将新模型与现有6种积液预测模型进行对比评价。综合考虑模型预测结果正确率及预测误差,认为新的环雾流模型较其他模型预测结果更优,可准确方便地对气井积液进行预测。

基于液膜临界速度的井筒积液预测新方法

现阶段用于预测气井积液问题的模型大多针对垂直井筒从Turner所建立的液滴受力模型上发展而来,认为井底积液是由井筒中液滴下落造成的,对井筒倾斜角和液膜逆流的影响没有深入探讨。本文对Unified多相流动模型进行编程,运用多相流动模型对垂直井筒、倾角75°井筒和60°井筒分别进行了数值模拟,分别从井筒内流动压降和液膜速度对井底积液进行判定。研究结果表明,液膜逆流是造成井底积液的重要因素之一,得出了液膜的临界速度为-0.3 m/s,当液膜速度低于该临界速度时井底发生积液。通过对比流动压降预测方法的预测结果,液膜逆流法的预测结果平均误差为11.56%,最大误差仅为19%,而最小压降法预测的平均误差则在38%左右,得出液膜速度可以更加准确的预测井底积液问题。本文研究结果可为深水气井积液预测提供新思路。