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.

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.

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。

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。

石西至克拉玛依原油管道结蜡特性及安全清管周期研究

目前含蜡原油管道的清管周期没有统一标准,需要根据油品性质和管道的实际情况确定。采用OLGA软件对石西至克拉玛依原油管道(SK原油管道)的结蜡特性进行了模拟分析,利用浓密膏体的管道输送阻力计算公式,将蜡堵分析转化为蜡柱长度和压降关系的计算,制定了SK原油管道的安全清管周期。结果表明:在管道103 km处流体温度降到25℃,从103 km至终点的管段均处于析蜡温度的区间范围;管道运行5天后,采用HeatAnalogy模型模拟的结蜡厚度在110.06 km处达到最大(0.01 mm),结蜡量为80 kg,结蜡量在运行2天后才有明显增加并呈直线上升趋势;以收球筒长度4 m作为蜡柱长度的极限值,计算得到收蜡量为200 kg,推算SK原油管道的清管周期可由目前的5天延长至9天,大大减少了操作成本。结果可为含蜡原油管道的结蜡特性研究及安全清管周期制定提供理论参考。

注CO_(2)改善河南双河油田低渗储层注水能力机理研究

针对双河油田低渗储层注水能力差、注水水质不达标和高凝原油蜡沉积等问题,通过自主设计的水-CO_(2)储层注入能力评价装置,开展流动性实验、CO_(2)驱油实验,结合岩心扫描电镜等测试手段,明确双河低渗储层注水能力差的主要机制,探索CO_(2)改善低渗储层注入能力的主要机理。结果表明,产出水中的悬浮颗粒和油中蜡晶等组分的沉积可导致孔隙堵塞,从而降低储层的注水能力。CO_(2)对产出水中无机悬浮颗粒及岩石碱性矿物、碳酸盐岩矿物有明显溶蚀作用,是显著提高储层注水能力的主要机理。CO_(2)可溶解在岩石表面的原油蜡质组分沉积,有效改善储层注水能力。同时,CO_(2)驱提高采收率效果明显,采收率提高13.01%~21.51%,后续水驱进一步提高5.40%~6.04%。研究表明:注CO_(2)可显著改善双河油田低渗储层注入能力,为CO_(2)增注驱油技术在现场应用提供理论支撑。

微生物防蜡技术在HT区块的应用效果分析

在开采、运送的过程中由于温度、压力及流动条件的变化,石蜡不断从原油中析出,造成井筒、管线的结蜡。微生物防蜡作为一项新兴的技术,受到广泛的关注,但是需要根据现场的环境条件选用合适的微生物防蜡菌液,有效解决油井结蜡的问题。通过开展原油黏度测定、菌群含量检测,对比功图载荷变验证其防蜡应用效果。经过180d的现场试验,HT区块4口油井结蜡周期明显延长,取得了不错的防蜡效果。

大型煤化工甲醇合成装置水冷器在线除蜡技术分析

分析了甲醇性质与合成工艺流程,介绍了大型煤化工甲醇合成装置水冷器蜡的成因、危害以及在线除蜡技术,最后介绍了在线除蜡具体操作流程,以期给相关人士提供有效参考。

Application of Epoxy Coatings to Increase the Efficiency of Wax Oils Production

When producing hydrocarbons,an important task relates to the optimization of the stock of the producing well.The main complications for wells in non-working mode are represented by the formation of asphalt-resinparaffin deposits.This issue is one of the most common problems in the production and transportation of oil.A promising method to deal with these deposits is the application of smooth coatings made of epoxy polymers on the inner surface of the production well tubing.In this work,a number of laboratory studies were carried out on the“Cold Finger”installation to assess the effectiveness of this approach.These laboratory studies have shown that the efficiency related to smooth coatings is 27%while the resulting thermal conductivity ranges from 0.259 to 0.279 W/(m°C).These results demonstrate that this technology can reduce the amount of organic deposits and increase the temperature of oil.

掺稀稠油重组分沉积规律研究

稠油因蜡、胶质、沥青质等重组分含量多,致使其流动性差,在管输过程中极易出现重组分沉积堵塞管道,给管输安全带来严峻挑战。掺混稀油是改善稠油流动性的有效方法之一,但目前的研究对掺混原油沉积规律关注较少。基于此,本文采用小型沉积实验装置,系统研究稀油类型、掺混比例、沉积时间等对掺混原油沉积规律的影响。结果表明,随着沉积时间增加,掺混原油沉积物质量逐渐增大;施加搅拌后,掺混原油沉积物质量减小,且搅拌速率越大,沉积物质量越小;增大稀油掺混量,掺混原油析蜡点降低,沉积物质量减小。揭示了沉积物中蜡、胶质、沥青质含量增加是造成沉积物质量增大的主要原因,提出了将掺混原油析蜡点作为稠油掺稀输送的重要工艺参数加以考虑。该结论为掺混原油管道主要进线指标以及清管周期的确定提供了理论指导。