Pipeline Flow Research Articles

Virtual Meter with Flow Pattern Recognition Using Deep Learning Neural Networks: Experiments and Analyses

Summary Operators often require real-time measurement of fluid flow rates in each well of their fields, which allows better control of production. However, petroleum is a complex multiphase mixture composed of water, gas, oil, and other sediments, which makes its flow challenging to measure and monitor. A critical issue is how the liquid component interacts with the gaseous phase, also known as the flow pattern. For example, sometimes liquids can accumulate in the lower part of the pipeline and block the flow completely, causing a gas pressure buildup that can lead to unstable flow regimes or even accidents (blowouts). On the other hand, some flow patterns can also facilitate sediment deposition, leading to obstructions and reduced production. Thus, this work aims to show that deep neural networks can act as a virtual flowmeter (VFM) using only a history of production, pressure, and temperature telemetry, accurately estimating the flow of all fluids in real time. In addition, these networks can also use the same input data to detect and recognize flow patterns that can harm the regular operation of the wells, allowing greater control without requiring additional costs or the installation of any new equipment. To demonstrate the feasibility of this approach and provide data to train the neural networks, a water-air loop was constructed to resemble an oil well. This setup featured inclined and vertical transparent pipes to generate and observe different flow patterns and sensors to record temperature, pressure, and volumetric flow rates. The results show that deep neural networks achieved up to 98% accuracy in flow pattern prediction and 1% mean absolute prediction error (MAPE) in flow rates, highlighting the capability of this technique to provide crucial insights into the behavior of multiphase flow in risers and pipelines.

Development of artificial neural networks for the prediction of the pressure field along a horizontal pipe conveying high-viscosity two-phase flow

Pressure fluctuations are one of the primary concerns regarding the safety of two-phase flows in pipelines. Therefore, it is crucial to closely monitor pressure variations and predict their spatiotemporal behavior to the greatest extent possible. In this article, we present the development of a set of models based on artificial neural networks (ANN) to predict the time-dependent behavior of the pressures produced by high-viscosity gas-liquid flows at predetermined locations along a horizontal pipeline. Different volume fractions of glycerin and air constitute the mixtures of interest. The models use the measured values of the mass-flow rates of both fluids at the pipe’s inlet, together with the pressures measured at other locations further downstream. In order to determine the optimal architecture for the artificial neural network, we tested the following four transfer functions for the hidden layer: logsig, tansig, softplus, and swish. Additionally, we utilized the linear function purelin for the output layer. We employed the Levenberg–Marquardt algorithm to train the ANN models and the experimental data set to test their performance.

Features selection for recognition of severe slugging in a long pipeline with an S-shaped riser by decision tree

In deep-sea oil and gas, S-shaped riser is the key equipment to transport the multiphase working substance produced underwater to the surface platform. The occurrence of severe slugging will seriously threaten the safe production of offshore oil and gas fields. Therefore, accurate and rapid recognition of hazardous flow patterns such as severe slugging is an urgent need to ensure the safety of multiphase flow in deep-sea long-distance pipelines. This paper has built a set of long S-shaped riser with industrial parameters, including 1687 m horizontal and downward inclined pipelines and 16.7 m S-shaped riser. The gas-liquid two-phase flow patterns, including severe slugging, oscillating flow and stable flow, are studied in this system. The pressure and differential pressure features of different signals are extracted from different positions along the pipeline, and a more comprehensive and reasonable evaluation criterion of signal performance is established. Making use of the advantages of visualization of the structure of decision tree, a new method to evaluate the recognition effect of features is proposed based on its classification principle. The original signal is decomposed into components of different scales through wavelet multi-scale analysis, and then the statistical features with good flow pattern differentiation ability are calculated. It is found that the mean of wavelet approximate component has the best recognition effect among all features. On the basis of feature correlation analysis, 7 features with high recognition rate applicable to 22 signals along the pipeline are optimally selected from 13 original features. For the water differential pressure signal DP13, the recognition rate obtained by using its 4 optimal features is 91.4 %, and the error between the recognition rate obtained by using all features is only 0.2 %. The overall recognition rate of the signal is the highest and the practicability is the best. When the sample duration is 6.2s, the recognition rate using the optimal feature reaches 90.8 %, thus ensuring the real-time recognition of the flow pattern while obtaining a high recognition rate.

Investigating the dynamic characteristics of oil droplets spreading on solid surfaces in water

The use of thermoplastic-reinforced pipes for fluid recovery is becoming increasingly common because the oil field enters the high-water-cut stage in this process. Investigating frictional drag in case of oil-water flow in nonmetallic gathering pipelines is important because the dynamics of oil droplets on the inner surfaces of the pipes have a significantly influence on the drag. In this article, we experimentally and theoretically investigate the dynamic characteristics of the spreading of oil droplets with varying diameters from 600 to 900 μm and viscosities on surfaces with different degrees of wettability in water. The durations of oscillation and spreading of oil droplets on the surfaces submerged in water were found to be dependent on their diameter and viscosity. Because the prevalent equations used for calculations in this context cannot adequately describe the durations of oscillation and spreading of the oil droplets on surfaces in water, we corrected them based on experimental data. Finally, we examined the dimensionless maximum diameter of spreading of the oil droplets on the surfaces in water, and found that it was influenced by the diameter of the oil droplets and the wettability of the surface. We developed a theoretical model to represent the behavior of the oil droplets as they spread in order to predict the dimensionless maximum diameter of spreading, and verified it by using experimental data. And the results showed that the deviations between the experimental results and those of the model were generally within ±8%.

Heat transfer characteristics of subsea long-distance pipeline subject to direct electrical heating

For deep-water pipelines with long tie-back distances, high external pressure, and low ambient temperature, it is a key issue to ensure flow safety by controlling the generation of hydrates and waxes through electric heating technology. In-detail analysis of the heat transfer performance of electric heating pipelines is of great engineering significance for developing the safety of pipeline flow in offshore oil-gas fields. This paper proposed an electrical heating analytical method applicable to long-distance submarine pipelines. Based on the thermal equilibrium theory and the differential equation of heat conduction, a mathematical model of heat-fluid coupling for electric heating pipes is established, involving the theoretical model of the steady-state distribution of the electric heating in the axial and radial directions. Then, the definition of the average temperature of the pipeline is introduced and combined with the two-point Hermite approximation interpolation method, and an improved lumped parameter model of the transient heat transfer of the electric heating pipeline is established. Meanwhile, the finite difference method is applied to solve the ordinary differential equation of the pipeline and the energy equation of the internal fluid. The steady-state calculation result is utilized as the initial value of the transient heat transfer process, and the model is applied to analyze the influence variation on the transient temperature response characteristics of the pipeline under different working conditions, finally determining the prediction formula of the average temperature of the fluid under normal transportation and shutdown conditions.

Numerical Simulation of an Online Cotton Lint Sampling Device Using Coupled CFD–DEM Analysis

Cotton processing is the process of converting harvested seed cotton into lint by cleaning, ginning, and cleaning the lint. The real-time acquisition of lint parameters during processing is critical in improving cotton processing quality and efficiency. The existing online inspection system cannot realize quantitative sampling detection, resulting in large fluctuations in the detection of moisture rate, and the impurity content of lint can only be measured according to the number of impurity grains and the percentage of impurity areas. This research developed a quantitative sampling device for cotton lint processing that can collect the right number of cotton samples and obtain the weight of the samples, laying the foundation for the accurate detection of cotton lint dampness and impurity rates. This research aimed to develop an online quantitative sampling device with a sampling plate as its core. The quantitative sampling procedure, consisting of a gas–solid two-phase flow in a cotton pipeline, was numerically simulated and experimentally analyzed using computational fluid dynamics (CFD) and the discrete element method (DEM). According to the coupling results, the maximum pressure differential between the top and bottom regions of the sampling plate when conveying was 1024.45 Pa. This pressure is adequate to allow for cotton samples to accumulate on the sampling plate. Simultaneously, the steady conveying speed of lint is 59.31% of the unloaded conveying wind speed, providing a theoretical foundation for the sampling time of the quantitative sample device in the processing chain. The results from testing the prototype indicate that the quantitative sampling device in the cotton flow can effectively perform the quantitative sampling of cotton lint under uniform conditions, with a sampling pass rate of 84%.

Allocation of transportation capacity for complex natural gas pipeline network under fair opening

China has formed a national natural gas pipeline network, and reasonable and accurate pipeline capacity allocation scheme has important significance for improving the utilization rate of pipeline network, improving the income of pipeline network operators and ensuring the gas consumption of downstream users, which poses greater challenges to the formulation of pipeline capacity allocation rules and mechanisms. This paper takes the natural gas pipeline network system as the research object, and studies the rules and mechanisms of pipeline capacity allocation. A capacity allocation model of natural gas pipeline network is proposed with the net present value of pipeline network operator's income as the goal, considering the gas consumption characteristics of downstream users, the dynamic change of gas source node capacity, pipeline hydraulic characteristics, pipeline flow direction, compressor and other constraints. Based on the simulation of the actual pipeline network by the proposed model, seven allocation rules and one mechanism are proposed. Specifically, the user priority of non-interruptible type, the pipeline path adjustable type and the gas source node adjustable type is higher than the corresponding comparison type. In the pipeline capacity allocation mechanism, the amount compensation mechanism for pipeline capacity transactions is as follows: When the pipeline capacity transaction occurs between users, the transaction information is submitted to the pipeline network operator. The pipeline network operator proposes the corresponding amount compensation according to the transaction information, and the transaction parties negotiate the proportion of the amount compensation and submit it to the pipeline network operator. In addition, it is recommended that pipeline network operators vigorously develop LNG receiving stations and downstream interruptible and compressible users in the future.

New in the hydraulics of channels with permeable walls: indicator of the relative value of the dissipation

The factors that have led to the creation of the scientific direction “hydraulics of variable mass” to study the fluid movement laws in channels with permeable walls are indicated. The results of applying of the dynamics of a variable mass point for describing the flow in such pipelines are presented. It is noted unjustifiability of the second Newton’s law generalization to the case of motion of a variable mass point for hydrodynamics problems. The functionality of one-dimensional and multidimensional models of fluid motion in permeable channels based on the classical equations of fluid and gas mechanics is characterized. It is substantiated the dominance of one-dimensional models in engineering computational practice, and a number of contradictions in the description of fluid dynamics are shown (with the flow visualization). On the base of the new kinematic image (instead of the generally accepted “solid jet”, when fluid particles are separated or joined), it has been obtained a one-dimensional equation of fluid motion in a permeable channel in which the friction coefficient is an indicator of the relative magnitude of the energy dissipation of the flow. The dependence of the Coriolis coefficient on the flow regime is constructed. The structure of the friction drag coefficient of a permeable channel has been studied using the vector dimension of length. It is shown that the dissipation of the flow energy in a permeable channel is higher both during outflow and inflow of liquid than in channels with solid walls at the same flow rates. The results are in demand in the development of chemical technology devices, nuclear reactors with microfuel elements, filters and heat exchangers containing channels with permeable walls.

Visualizing flow dynamics and restart of Carbopol gel solutions in tube and parallel-plates geometries with wall slip.

The present study examines the impact of slip in Carbopol solutions during the restart flow in pipelines utilizing in situ visualization techniques. Rheological tests were conducted using smooth and hatched parallel plate geometries to obtain the rheological characteristics of the solutions. The behavior of the solutions in the creep tests is compared with those in the experimental unit. Three flow regimes were identified through rheological and experimental setup tests: non-flow, slip, and yielded. The slip regime allowed the establishment of a slip static yield stress value, indicating significant deformation states, and a restart pressure decrease of about 61% when compared to the static yield stress. The flow dynamics under the wall slip effect is captured by velocity profiles, velocity contour maps and velocity gradient. Transient correlations of the scaling law type were determined, with wall slip in proportion to the velocity gradient and wall shear stress. Additionally, the concentration of viscoplastic material in the solution increased the scaling law index. This research seeks to provide valuable findings by quantifying the effects of apparent wall slip through in situ measurements. Such insights are crucial for designing and managing pipeline transport systems that handle yield stress fluids, applicable across various industries including cosmetics, food processing, and the production of waxy oils.

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 oil-gas two phase that occurs easily in multiphase field pipelines.

Study on Resistance Loss of Fly Ash Slurry Multistage High‐Pressure Grouting Pipeline Based on Fluent

In order to understand the resistance loss along the way during multistage high‐pressure slurry transportation, the flow state of fly ash slurry in the pipeline was simulated by Fluent software in this paper, and the effects of pipe diameter D, pipe transportation flow rate Q, and fly ash mass concentration Cw on the resistance loss along the pipeline were studied. The fly ash slurry is a non‐Newtonian Bingham fluid that moves in a turbulent state in a pipeline. When simulating the flow of fly ash slurry using Fluent software, the mesh type is a mixed mesh of hexahedron and wedge shapes, and the viscous model is selected as realizable k‐ε Turbulence Model, with Enhanced‐Wall Function (EWF) selected as the wall function, combined with a four‐layer boundary layer mesh, which can more accurately capture the details of velocity changes at the wall, thereby improving the accuracy of the model. The inlet of the model is the velocity inlet, and the outlet is the pressure outlet. The coupled algorithm is chosen as the solution method. Under these conditions, the model converges quickly and the calculation accuracy is high. The results show that the resistance loss along the pipeline decreases as a power function with the increase of pipeline diameter, and there is a polynomial relationship between the pipeline flow and the resistance loss along the pipeline, while the mass concentration of fly ash slurry changes linearly with the resistance loss along the pipeline. In addition, three friction coefficient models, namely Blasius formula, Colebrook–White equation, and Wilson–Thomas model, were selected according to the flow characteristics of fly ash slurry. Based on the Blasius formula with the smallest relative calculation error, the Blasius formula was modified by multiple linear regression analysis to improve the accuracy of the frictional resistance coefficient model and to provide help for the design and use of separate layer grouting conveying system.

NUMERICAL INVESTIGATION OF LIQUID-CARRYING AXIAL AND SWIRL FLOW IN A BENT PIPE

Water condensation occurs in the sloping sections of natural gas pipelines due to fluctuations in temperature and pressure. This event has a major effect on the efficiency and security of gas transportation. In this numerical study, the flow of water via a swirling flow in a wavy pipeline is examined using computational fluid dynamics. A 1-inch pipe is used to simulate a low-lying area of the pipeline, which is normally where the condensate water would gather. The effect of swirl on the flow patterns in the U-shaped pipe with previously published experimental results is studied and validated. In order to comprehend the change of static and dynamic pressure, results are extended in the doubly undulated pipe (w-pipe). According to the innovative analysis in this study, higher swirl flow could empty the water build-up faster than swirl flow inlet velocities below 11.2 m/s in a given amount of time. When the effusion volume increases and the water-carrying capacity is enhanced, several flow regimes, including annular flow, plug flow, slug flow, stratified wave flow, and stratified flow, are observed along with an increase in air velocity.

Гидравлические исследования поливного модуля системы комбинированного орошения

Purpose: to state hydraulic characteristics and determine priority directions for improving the irrigation module design for combined drip and micro-sprinkler irrigation. Materials and methods. The study is based on the joint use of theoretical methods – a well-known mathematical model for calculating the hydraulic characteristics of the irrigation module and experiment, which allows assessing the problem state and scale solutions in any necessary proportions. Results. According to calculations, the uniformity of watering is maintained at an acceptable level at a lower head level in the range of 1.56–1.68 atm when installing six microsprinklers on a drip line. When installing eight sprinklers, the water head along the length of the drip pipeline decreased to an unacceptable 1.39–1.40 atm. Experimental studies have shown that there is only an option with two sprinklers installed on the pipeline above the level of 1.5 atm. Already with the installation of four sprinklers, the water head along the length of the pipeline decreased to 1.45–1.47 atm. At the same time, the variation in the actual microsprinkler performance reached 16 % or more. The discrepancy between experimental and model data is explained by the fact that the calculation model does not fully take into account local resistances that arise when connecting sprinklers. Conclusions. Two main reasons of the increased uneven distribution of irrigation water over the irrigated area have been identified. The first reason is a significant increase in water flow in the irrigation pipeline when emitters and sprinklers work together. The solution to this problem is to develop structures that make it possible to separate the water flow through emitters and through sprinklers in time. The second reason is an increase in local resistance in the water diversion units to the sprinklers. The solution to this problem is to develop special water diversion structures that would be characterized by minimal local resistance.

Structure and principle of operation of the apparatus for introducing chlorine into the process pipeline

The article discusses the study of swirling flow in technological pipelines. It examines the nature of the swirling flow, presenting the experimental velocity distribution and pressure inside the pipe in graphical and tabular form. The scope of the study includes the displacement of liquid and gas, as well as the purification of natural waters using ozone and chlorine. The article analyzes the existing technological processes for the preparation of drinking water from surface water sources in Uzbekistan. Due to the significant volumes of water consumption for economic activities, the issue of drinking water disinfection is crucial. In addition to traditional disinfection methods, modern researchers are focusing on developing innovative technologies for this process. The article also studies the features of water formation and its qualitative composition, with an analysis of the reliability of the existing drinking water treatment technology.

Model analysis of flow-induced vibration (LIV) in submarine oil and gas pipeline

Abstract In order to realistically simulate the flow-induced vibration of submarine oil and gas pipelines, this paper assembles a gas-liquid two-phase flow vibration device, develops a detailed and comprehensive experimental procedure, and sets the flow aperture, flow pressure, flow depth, flow direction, and gas-liquid phase apparent flow rate and other variables. According to the different types of pipelines, the multiphase flow-induced vibration of submarine oil and gas pipelines can be categorized into straight pipe vibration and elbow pipe vibration, and combined with the theoretical knowledge of fluid dynamics and the equations of motion to construct a multiphase flow-induced vibration model of submarine oil and gas pipelines and discuss the vibration mechanism of submarine oil and gas pipelines in two-phase liquid flow. Combined with the corresponding experimental parameters, the vibration phenomenon induced by gas-liquid two-phase flow in submarine oil and gas pipelines is experimentally analyzed. It is analyzed that the first-order intrinsic frequency of the submarine oil and gas pipeline is kept at 23.2 Hz when the value of the Reynolds number of the in-pipe flow ranges from 2.53 × 104 to 1.08 × 107. The first-order intrinsic frequency of the submarine oil and gas pipeline monotonically decreases with the increase of the Reynolds number of the in-pipe flow. In addition, when Ul=0.4m/s, the average standard deviation of the data is only 1.114m/s² with the rise of Ug, indicating that the vibration intensity of the fluid on the subsea oil and gas pipeline increases gradually with the increase of the apparent flow velocity of the liquid phase. By analyzing the multiphase flow problem of oil and gas pipelines, this study is of great significance in improving the efficiency of oil and gas transportation.

Enhanced Deep Learning Method for Natural Gas Pipeline Flow Prediction Based on Integrated Learning

Enhanced Deep Learning Method for Natural Gas Pipeline Flow Prediction Based on Integrated Learning

Experimental study of the effects of a magnetic field/magnetic field-ferromagnetic nanocomposite pour point depressant on wax deposition.

A magnetic field and pour point depressant, as a new avenue for improving the submarine pipeline flow of waxy oils, has attracted increasing attention along with the development of efficient wax mitigation techniques. Although advances have been made recently in understanding the rheological behavior and crystallization properties of waxy oils, the effect of magnetic field and pour point depressants on wax deposition remains an open question. In this work, a ferromagnetic nanocomposite pour point depressant (FNPPD) was prepared. The variations in wax deposition mass and component under the effect of different magnetic treatments and magnetic field-FNPPDs were investigated using cold fingers and high-temperature gas chromatography. It was evident that both the high-intensity and high-frequency magnetic fields generated by the magnet and magnetic coil can effectively reduce the deposition mass and have a long-term magnetic history effect. The synergistic effect of magnetic fields and FNPPDs concurrently reduced the thickness/mass and wax content in the deposition layer, as compared to the individual use of magnetic fields or FNPPDs. The wax precipitation properties and wax crystal morphology of waxy oils under the action of the magnetic field were characterized by differential scanning calorimetry, focused beam reflectance measurement and polarizing microscopy experiments, and the mechanism of the magnetic field was elaborated from the perspective of crystallization kinetics by combining the fitting analysis of Avrami and size-independent growth model.

Feature extraction and pattern recognition of gas pipeline flow noise signals in a strong noisy background.

The purpose of this study is to put forward a feature extraction and pattern recognition method for the flow noise signal of natural gas pipelines in view of the complex situation brought by the rapid development and expansion of urban natural gas infrastructure in China, especially in the case that there are active and abandoned pipelines, metal and nonmetal pipelines, and natural gas, water and power pipelines coexist in the underground of the city. Because the underground situation is unknown, gas leakage incidents caused by natural gas pipeline rupture occur from time to time, posing a threat to personal safety. Therefore, the motivation of this study is to provide a feasible method to accelerate the aging, renewal and transformation of urban natural gas pipelines to ensure the safe operation of urban natural gas pipeline network and promote the high-quality development of urban economy. Through the combination of experimental test and numerical simulation, this study establishes a database of urban natural gas pipeline flow noise signals, and uses principal component analysis (PCA) to extract the characteristics of flow noise signals, and develops a mathematical model for feature extraction. Then, a classification and recognition model based on backpropagation neural network (BPNN) is constructed, which realizes the detection and recognition of convective noise signals. The research results show that the theoretical method based on acoustic feature analysis provides guidance for the orderly and safe construction of urban natural gas pipeline network and ensures its safe operation. The research conclusion shows that through the simulation analysis of 75 groups of gas pipeline flow noise under different working conditions. Combined with the experimental verification of ground flow noise signals, the feature extraction and pattern recognition method proposed in this study has a recognition accuracy of up to 97% under strong noise background, which confirms the accuracy of numerical simulation and provides theoretical basis and technical support for the detection and recognition of urban gas pipeline flow noise.

Comprehensive Analysis of Internal Flow Dynamics in Pipeline Systems

This research delves into the intricate flow dynamics within a gas pipeline, leveraging the small perturbation equations to elucidate the flow scenario. Utilizing the Python programming language, the study derives the numerical solutions for the governing equations of the pipeline's flow field. This is achieved through the successive over-relaxation (SOR) iterative method in tandem with the Neumann boundary conditions. The flow dynamics are subsequently visualized and analyzed using streamlined diagrams and Mach number cloud representations, facilitating the identification of stress concentration points on the pipeline's inner wall. Such insights significantly affect the pipeline's optimal design and strategic reinforcement. Beyond its immediate application, the methodology presented herein offers a robust framework for addressing diverse fluid mechanics simulation challenges. Its versatility extends to realms such as automotive contour design, pipeline leakage simulations, and engine compressor configurations. When confronted with the need to dissect fluid flow and stress dynamics, professionals can harness the Python-based SOR iteration code to derive governing fluid equations, enabling a graphical interpretation through streamlined and Mach number cloud diagrams. This study, thus, underscores a pivotal toolset for fluid mechanics challenges across various engineering domains.

IMPROVEMENT OF METHODS FOR CALCULATION OF GAS-LIQUID SLUG OF FLOW IN PIPELINES

To calculate pressure losses during transportation of gas-liquid fluids in flowlines, it is important to correctly estimate the effective density and viscosity of the mixture, which increases the accuracy of calculating the tangential stresses required to determine hydraulic pressure losses at the liquid-wall boundary. The determining parameter when calculating the effective values of the density and viscosity of the mixture is the coefficient liquid holdup in the cross section of the pipeline. The article analyzes the applicability of empirical methods for modeling two-phase gas-liquid currents when calculating liquid holdup in slug body of a intermittent (slug) flow in horizontal pipelines. A description is given of the mechanistic approach proposed by Zhang to calculate the liquid holdup in the slug body used in one of the most famous modern models of gas-liquid flow — TUFFP Unified model. The results of calculating the actual liquid holdup in the slug body using the TUFFP Unified model hydrodynamic model are presented, showing good consistency of the calculated data with experimental ones for vertically located pipelines, and unsatisfactory consistency for currents in horizontal pipes. The purpose of the article is to improve the methods of calculating the gas-liquid slug structure of the current using the TUFFP Unified model, by improving the accuracy of calculating the liquid holdup in the slug body at the horizontal location of the flowline. The proposal to use in the TUFFP Unified model a new approach to assessing the stable diameter of the gas bubble of the dispersed-bubble flow regime in the body of a liquid slug made it possible to increase the reliability of calculating the liquid holdup in the slug body with a horizontal location of the pipeline.