Experimental study on wax deposition of highly paraffinic oil in intermittent gas-oil flow in pipelines

Oil-gas two phase wax deposition is a fairly common and open-ended question in flow assurance of multiphase transportation pipelines.This paper investigated the two main aspects of oil-gas two phase wax deposition layer:apparent thickness and crystal structure characteristics.A typical highly paraffinic oil in Bohai Sea,China,was used as the experimental material to investigate the wax deposition thickness in oil-gas two phase under the influence of different oil temperatures,superficial gas/liquid phase velocities and gas-oil ratios by using multiphase flow loop experimental device.Just as in the classical theory of wax molecular diffusion,it showed that wax deposition thickness of oil-gas two phase increased with increasing oil temperature.Analysis of the impact of different superficial phase velocities found that the actual liquid flow heat transfer and shear stripping was the gas phase dominant mechanisms determining wax deposit thickness.In addition,the crystal structure of the wax deposition layer was characterized with the help of small-angle X-ray scattering(SAXS)for different circumferential positions,flow rates and gas-oil ratios.The bottom deposition layer had a complex crystal structure and high hardness,which were subject to change over flow rate variations.Furthermore,the SAXS results provided evidence that the indirect effect of the actual liquid velocity modified by the gas phase was the main mechanism.Our study of the effect of gas phase on the wax deposition of oil-gas two phase will help shed light onto the mechanism by which this important process occurs.Our findings address a very urgent need in the field of wax deposition of highly paraffinic oil to understand the flow security of oilgas two phase that occurs easily in multiphase field pipelines.

Prediction Model of Wax Deposition Rate in Waxy Crude Oil Pipelines by Elman Neural Network Based on Improved Reptile Search Algorithm

A hard problem that hinders the movement of waxy crude oil is wax deposition in oil pipelines.To ensure the safe operation of crude oil pipelines,an accurate model must be developed to predict the rate of wax deposition in crude oil pipelines.Aiming at the shortcomings of the ENN prediction model,which easily falls into the local minimum value and weak generalization ability in the implementation process,an optimized ENN prediction model based on the IRSA is proposed.The validity of the new model was confirmed by the accurate prediction of two sets of experimental data on wax deposition in crude oil pipelines.The two groups of crude oil wax deposition rate case prediction results showed that the average absolute percentage errors of IRSA-ENN prediction models is 0.5476% and 0.7831%,respectively.Additionally,it shows a higher prediction accuracy compared to the ENN prediction model.In fact,the new model established by using the IRSA to optimize ENN can optimize the initial weights and thresholds in the prediction process,which can overcome the shortcomings of the ENN prediction model,such as weak generalization ability and tendency to fall into the local minimum value,so that it has the advantages of strong implementation and high prediction accuracy.

Pre-heating temperature induced flowability and wax deposition characteristics of crude oil adding wax inhibitors

This paper investigated the effects of pre-heating treatment temperatures(T_(pre))on the flowability and wax deposition characteristics of a typical waxy crude oil after adding wax inhibitors.It is found that there is little difference in wax precipitation exothermic characteristics of crude oils at different T_(pre),as well as the wax crystal solubility coefficient in the temperature range of 25-30℃.For the undoped crude oil,the flowability after wax precipitation gets much improved and the wax deposition is alleviated as T_(pre)increasing.At T_(pre)=50℃,the viscosity and wax deposition rate of crude oil adding wax inhibitors are higher than those of the undoped crude oil.When the T_(pre)increases to 60,70,and 80℃,the flowability of the doped crude oil are largely improved and the wax deposition is suppressed with the T_(pre)increase,but the wax content of wax deposit increases gradually.It is speculated that,on the one hand,the T_(pre)increase helps the dispersion of asphaltenes into smaller sizes,which facilitates the co-crystallization with paraffin waxes and generates more aggregated wax crystal flocs.This weakens the low-temperature gel structure and increases the solid concentration required for the crosslink to form the wax deposit.On the other hand,the decrease in viscosity increases the diffusion rate of wax molecules and accelerates the aging of wax deposits.The experimental results have important guiding significance for the pipeline transportation of doped crude oils.

Wax deposition modeling in oil-water stratified pipe flow

Wax deposition in oil-water stratified flow is commonly encountered onshore and offshore oil production pipe systems,and typically reduces transportation capacity of oil.The accurate predicted model of wax deposition has becomes an indispensable approach to design effective remediation strategies.However,a reliable mechanistic model for wax deposition prediction in oil-water two-phase stratified pipe flow is lacking to validate the deposition process.In this work,a three-dimensional(axial,radial,and angular)robust wax deposit model for oil-water stratified circular pipe flow was developed.The model of formation of a gel deposit based on the first principles of rheology was developed,associated with the results obtained from hydrodynamics and heat/mass transfer simulations.The predictions for wax deposition are found to compare satisfactorily with experimental data with two different oils for single phase and four different water cuts for oil-water stratified pipe flow.It can be seen from the wax gelation mechanism that an increase in water cut can help to reduce the wall/oil-deposit interface shear stress,thereby leading to an increase in the degree of gelation as well as the deposit rate.Furthermore,a local deposit analysis in the circumferential direction was conducted,for water cut 75%and total flow rate 5 m3/h,which provided insights to understand that the thickness on pipe wall was roughly uniformly distributed locates near the top of the pipe and the nearer the position gets close to two points,where the oil-water interface contacts the inner wall,the deposition thickness quickly dropped to 0.It was attributed to the fact that a roughly uniformly thickness far away from the oil-water interface contact the inner wall resulted in the slowly changes temperature along the circumferential pipe wall wetted by oil.

Effect of surfactants and their blend with silica nanoparticles on wax deposition in a Malaysian crude oil

The present study investigated the wax deposition tendencies of a light Malaysian crude oil（42.4° API）, and the wax inhibiting potential of some surfactants and their blends with nanoparticles. With the knowledge that the majority of the wax inhibition research revolved around polymeric wax inhibitors, which cause environmental issues, we highlighted the potential of surfactants and their blend with SiO2 nanoparticles as wax deposition inhibitors. Different surfactants including oil-based, silane-based, Gemini and bio-surfactants were considered as primary surfactants. The primary surfactants and their respective blends at a concentration of 400 ppm were screened as wax inhibitor candidates using cold finger apparatus. The screening results showed a significant influence on the paraffin inhibition efficiency on wax deposition by using 400 ppm of silane-based surfactant, which decreased the wax deposition up to 53.9% as compared to that of the untreated crude oil. The inhibition efficiency among the silane-based surfactant（highest） and bio-surfactant（lowest）revealed an appreciable difference up to 36.5%. Furthermore, the wax from the treated sample was found to deposit in a thin gel-like form, which adhered inadequately to the surface of the cold finger. A further investigation by blending the 400 ppm silane-based surfactant with a 400 ppm SiO2 nanoparticle suspension in a load ratio of 3：1 found that the wax inhibition decreased up to 81% as compared to the scenario when they were not added. However, we have shown that the synergy between the silane-based surfactant and the nanoparticles is influenced by the concentration and load ratio of surfactant and nanoparticles, residence time, differential temperature and rotation rate.

Prediction Model Based on the Grey Theory for Tackling Wax Deposition in Oil Pipelines

Problems involving wax deposition threaten seriously crude pipelines both economically and operationally. Wax deposition in oil pipelines is a complicated problem having a number of uncertainties and indeterminations. The Grey System Theory is a suitable theory for coping with systems in which some information is clear and some is not, so it is an adequate model for studying the process of wax deposition. In order to predict accurately wax deposition along a pipeline, the Grey Model was applied to fit the data of wax deposition rate and the thickness of the deposited wax layer on the pipe-wall, and to give accurate forecast on wax deposition in oil pipelines. The results showed that the average residential error of the Grey Prediction Model is smaller than 2%. They further showed that this model exhibited high prediction accuracy. Our investigation proved that the Grey Model is a viable means for forecasting wax deposition. These findings offer valuable references for the oil industry and for firms dealing with wax cleaning in oil pipelines.

Physical properties of wax deposits on the walls of crude pipelines

Wax deposits on the wall of a crude oil pipeline are a solid wax network of fine crystals, filled with oil, resin, asphaltene and other impurities. In this paper, a series of experiments on wax deposition in a laboratory flow loop were performed under different conditions （flow rate, temperature differential between crude oil and pipeline wall, and dissolved wax concentration gradient）, and the wax deposits were analyzed, so quantitative relationships among wax content, wax appearance temperature （WAT）, shear stress, and radial concentration gradient of dissolved wax at the solid/liquid interface were obtained. Finally, a model was established to predict WAT and the wax content of the deposit.

Waxes in asphaltenes of crude oils and wax deposits

Composition and molecular mass distribution of n-alkanes in asphaltenes of crude oils of different ages and in wax deposits formed in the borehole equipment were studied. In asphaltenes, n-alkanes from C12 to C60 were detected. The high molecular weight paraffins in asphaltenes would form a crystalline phase with a melting point of 80–90 ℃. The peculiarities of the redistribution of high molecular paraffin hydrocarbons between oil and the corresponding wax deposit were detected. In the oils, the high molecular weight paraffinic hydrocarbons C50–C60were found, which were not practically detected in the corresponding wax deposits.

Determination of thickness of wax deposition in oil pipelines using gamma-ray transmission method

Wax deposition in pipelines is a crucial problem in the oil industry.An approach that combines the gammaray transmission method with scanning technology is proposed to detect the thickness of wax deposition.The performance of the method is validated through simulations with MCNP code.An experiment is also carried out with a 300 mCi ^(137)Cs source and a LaBr_3 detector.A good correspondence is observed between the simulation and experimental results.The results indicate that the approach is efficient for detecting the thickness of wax deposition in oil pipelines.

The Thermodynamic Model on Paraffin Wax Deposition Prediction

In process of crude oil production and transportation, wax and other solid deposition issues have a significant impact on oilfield production. Solid precipitation not only reduces the production efficiency and increases the cost of production. Therefore, there is a need to study the rate of paraffin wax deposition and cloud point temperature in order to guide the oil field control the paraffin wax deposition. In this paper, we use the Flory theory of polymer solution to correct the liquid activity coefficients, and regular solution theory to correct for the non ideality of the solid mixture, and we consider the impact of isoparaffin. Finally, thermodynamic model is established. The actual example calculation shows that the forecast results of this model are more accurate.

Predicting wax deposition using robust machine learning techniques

Accurate prediction of wax deposition is of vital interest in digitalized systems to avoid many issues that interrupt the flow assurance during production of hydrocarbon fluids.The present investigation aims at establishing rigorous intelligent schemes for predicting wax deposition under extensive production conditions.To do so,multilayer perceptron(MLP)optimized with Levenberg-Marquardt algorithm(MLPLMA)and Bayesian Regularization algorithm(MLP-BR)were taught using 88 experimental measurements.These latter were described by some independent variables,namely temperature(in K),specific gravity,and compositions of C1eC3,C4eC7,C8eC15,C16eC22,C23eC29 and C30þ.The obtained results showed that MLP-LMA achieved the best performance with an overall root mean square error of 0.2198 and a coefficient of determination(R2)of 0.9971.The performance comparison revealed that MLP-LMA outperforms the prior approaches in the literature.

Wax deposition law and OLGA-Based prediction method for multiphase flow in submarine pipelines

In this study,the effects of wax deposition on submarine multiphase pipelines are investigated.In order to understand the mechanism of wax deposition in submarine multiphase pipelines,a wax deposition model in a submarine pipeline was established using the OLGA wax deposition module,and key factors influencing this phenomenon were analyzed.Additionally,a multifactor impact analysis of wax deposition was performed via the orthogonal test method.The results indicated the relative influence of five factors on oil-gas-water three-phase wax deposition,namely,oil flow rate,water content,inlet temperature,gas-oil ratio,and outlet pressure.Then,the main influencing factors of wax deposition in a multiphase pipeline flow were extracted,and the wax deposition prediction model was established.The wax deposition rate under different operating conditions was simulated using the OLGA wax deposition simulation module.The SPSS software was used to perform nonlinear regression analysis under different working conditions.In this manner,the constant terms in the wax deposition prediction model for a submarine multiphase pipeline were obtained.The prediction model could be used to programmatically predict wax deposition along a multiphase pipeline by programming the initial waxing conditions.By using this method,the wax deposition prediction model of an MN submarine multiphase pipeline was obtained under different working conditions.After comparing the predicted and the OLGA simulation results,it was concluded that the established wax deposition model can be used to accurately calculate the wax deposition in a submarine multiphase pipeline within an allowable error range.If the physical properties and operating parameters of the conveying medium in a multiphase pipeline are given,the developed oil-gas-water three-phase wax deposition model can be used to predict the distribution of wax deposition in submarine multiphase pipelines without laboratory experiments.The results of this study can help production units understand the waxing situation of pipelines in time in order to scientifically formulate a pigging plan and avoid pipeline blockages and shutdowns.

A prediction method for the wax deposition rate based on a radial basis function neural network

The radial basis function neural network is a popular supervised learning tool based on machinery learning technology.Its high precision having been proven,the radial basis function neural network has been applied in many areas.The accumulation of deposited materials in the pipeline may lead to the need for increased pumping power,a decreased flow rate or even to the total blockage of the line,with losses of production and capital investment,so research on predicting the wax deposition rate is significant for the safe and economical operation of an oil pipeline.This paper adopts the radial basis function neural network to predict the wax deposition rate by considering four main influencing factors,the pipe wall temperature gradient,pipe wall wax crystal solubility coefficient,pipe wall shear stress and crude oil viscosity,by the gray correlational analysis method.MATLAB software is employed to establish the RBF neural network.Compared with the previous literature,favorable consistency exists between the predicted outcomes and the experimental results,with a relative error of 1.5%.It can be concluded that the prediction method of wax deposition rate based on the RBF neural network is feasible.

金龙2井区含蜡原油结蜡微观机理及预测模型

采用分子动力学方法研究了含蜡原油结蜡的微观机理,通过实例优选了结蜡预测模型,根据含水率对结蜡量的影响对预测模型进行修正,并提出考虑原有结蜡厚度对后续结蜡影响的计算流程。实验结果表明,初始蜡分子先在原油中分散,后在非晶细胞盒子中聚集形成蜡晶,随着温度升高径向分布函数峰值降低,蜡分子分布从紧密聚集向分散转变;修正后的结蜡预测模型计算误差仅为4%,随着含水率的增高结蜡厚度减小,随生产时间的延长结蜡厚度增加缓慢。修正后的结蜡预测模型能准确预测金龙2井区清蜡周期,可为现场清防蜡工艺提供理论指导。

油水乳化胶凝作用对蜡沉积影响的定量表征

通过对乳液黏温曲线变化规律进行挖掘,对凝油团形成过程定量表征,推导得出凝油团形成的数学关系表达式,将胶凝过程细化为凝油团形成和黏附两个阶段。通过蜡沉积的温度条件,发现随着沉积管壁的温度降低,凝油团形成系数逐渐增大,胶凝作用逐渐显著,即在沉积初期蜡沉积的厚度迅速增加,这与蜡沉积实验结果相吻合。

垢对蜡沉积物强度及聚乙烯管道清管特性的影响

油井采出原油中含有泥沙、垢等颗粒物,在管输过程中颗粒物与原油中的蜡分子协同沉积,导致管道输量降低,严重时可能造成管道堵塞,影响原油管道安全输送。对掺垢蜡沉积物进行了屈服应力测试实验和显微特性实验;对室内聚乙烯管道进行了清管实验;基于清管实验结果,利用π定理建立了清管效率预测模型。结果表明,碳酸钙垢对蜡沉积物强度的影响存在临界垢质量分数;沉积物中含垢,会提高清管器的蜡层破坏力和清管效率;通过室内实验和第三方文献实验数据,验证了所建立的模型。

机动管线输送舰用燃料油蜡沉积计算模型研究

舰用燃料油是我国海军大型舰艇的燃料。在战时需要采用基于机动钢质管线的岸滩无码头油料补给系统,为舰艇补给燃料油。机动管线加热输送舰用燃料油过程中,由于冬季低温和强换热的作用,使得管线中蜡沉积问题十分突出,严重影响油料补给系统的正常工作。通过对燃料油蜡沉积过程机理及蜡沉积动力学特性分析,建立了舰用燃料油蜡沉积动力学模型。结合蜡沉积过程中流动传热计算结果确定了模型所需参数,计算得到管输舰用燃料油蜡沉积速率,阐明蜡沉积机理,得到了不同流速、不同油温和不同油壁温差对蜡沉积速率的影响。

冷热油交替输送对管道结蜡层溶解规律的影响研究

为更好地管理冷热油交替输送管道,保障输送安全,利用Couette结蜡装置,通过改变溶解时间、温度、转速、蜡沉积性质等因素,探究了进口轻质冷油对国产含蜡热油在一定油温、壁温、转速、结蜡时间等实验条件下所形成蜡沉积层的溶解规律。研究结果表明,低碳数蜡比高碳数蜡更容易被溶解,而冷油温度是影响溶解效果的关键因素,冷油温度提高15℃可使溶蜡量增加17倍;流速提高更有利于高碳数蜡的扩散;溶蜡效果与蜡沉积层性质有关,并且溶蜡效果并不会随溶解时间的增长而持续改善,在溶蜡时长为1 h处存在明显转折点。

石油沥青质结构及其对蜡分子结晶和沉积行为影响研究进展

深水油气资源将是21世纪全球油气资源开发的战略性接替区域。高沥青质含量作为深水油气资源的一个重要特征,对油气开采、储存运输和炼化过程都具有重要影响,尤其是沥青质与蜡在深水油气开发过程中的相互作用至关重要。以深水油气资源开采为契机,从沥青质结构角度,对沥青质结构表征、沥青质在油水界面的分布、沥青质对蜡结晶和原油胶凝及沉积过程影响等进行了系统论述。结果表明:沥青质结构特征可以采用原子力显微镜等进行表征,且多以多环芳烃为核心,直链或支烃基作为其支链;沥青质结构中表面官能团(亚砜基官能团、吡啶官能团等)对油水界面的稳定性影响不一;沥青质对蜡分子结晶和沉积行为影响,目前研究多集中在定性层面,微观机理分析有待深入。但分析沥青质与蜡的作用关系、作用过程及机理,将是未来主要的研究方向,能够为深水油气资源开采与输送提供理论参考和技术支持。

凝析油管道蜡沉积特性及蜡沉积模型研究

目前,诸多学者认为凝析油管道无需进行清管作业,但现场却时常发生堵管现象。基于此,利用环道实验装置确定不同油温、壁温及油流流速对凝析油析蜡特性的影响,通过相关系数矩阵和方差膨胀因子验证了动力学蜡沉积速率模型中参数选取的准确性,并通过全局优化求解方法对无量纲参数进行求解,最后结合现场清管作业验证模型准确性。结果表明,油壁温差越大,温度区间越小,沉积物质量和蜡沉积速率越大,油流流速对蜡沉积的影响存在临界状态;沥青质的含量对于蜡沉积速率和沉积物中的蜡含量影响较大;全局优化算法中Levenberg-Marquardt算法的误差最小,模型精度最高,模型决定系数0.9017;预测结果中当量蜡沉积厚度和模型蜡沉积厚度的相对误差范围在[-18.63%,27.35%],平均相对误差绝对值为6.12%,证明了动力学蜡沉积模型预测结果的准确性。