Horizontal Pipeline Research Articles

Experimental research on self-amplifying density waves in horizontal pipelines of two phase granular slurries: Measurements on the effect of particle diameter and concentration

Self-amplifying density waves in hydraulic transport pipelines is a scarcely researched topic. Density waves are in essence the result of a spatial redistributing effect and clustering of solids in hydraulic transport pipelines. Self-amplifying density waves are very undesirable for practical applications, as these waves increasing the risk of pipeline blockages. The two available experimental studies (Talmon et al., 2007; Matoušek and Krupička, 2013) report conflicting properties of the density waves, such as wave length and wave celerity. This new experimental research aims to shed light on the reported differences, by broadly varying particle size and concentration in a new dedicated experiment. The main highlight of this research is that two separate mechanisms were identified that can cause density waves, and Talmon et al. (2007) and Matoušek and Krupička (2013) in hindsight were studying the two different mechanism respectively. Both wave type mechanisms come into effect at mixture velocities close to the deposit limit velocity, and require a stationary bed layer to initiate. The first mechanism is caused by an imbalance of erosion and sedimentation of the bed layer, which is predominant for fine sand particles (∼242μm and ∼308μm in this research). The second mechanism occurs when the bed layer starts sliding, instead of being eroded, and is specific for larger sand sizes (∼617μm and ∼1.08mm in this research). These two mechanisms are clearly distinguishable, having different wave lengths, celerity, amplitudes and amplification rates. The results also show a clear relationship between the mean concentration of a density wave, the wave amplitude and wave celerity specific for each of the two mechanisms.

CFD-PBM simulation of nanobubble distribution characteristics in horizontal pipeline

CFD-PBM simulation of nanobubble distribution characteristics in horizontal pipeline

Experimental investigation of online solving for critical valve opening for eliminating severe slugging in pipeline-riser systems

In an offshore pipeline-riser system, the critical opening of choke valve, i.e., the maximum permanent opening to eradicate severe slugging, plays an important role in both pipeline design and offshore oil and gas production processes. However, solving critical opening online in an offshore oil field is very difficult because only topside measurements are available and system information such as inlet gas–liquid flow rates and transfer functions are unavailable or far from precise. In order to cope with this problem, manually traversal experiments were first conducted in a large-scale experimental system consists of a 114-m horizontal pipeline, an 18.7-m downward-inclined pipeline with an inclination angle of −5˚ and a 16.3-m riser. Based on the results, a new process variable characterizing cut-off ratio of outflow and a new valve parameter describing the influence of valve on flow were derived. An approximate linear relation between these two parameters was found, with which critical openings can be calculated by processing real-time data. Finally, a control scheme was designed to overcome the calculation errors and solve for critical openings on line. The performance was validated by automatic control experiments.

Experimental Study for Enhancement of Water Flow in Horizontal Pipelines by Using Nanoparticles of Zinc Oxide and Poly Acrylic Acid

Experimental Study for Enhancement of Water Flow in Horizontal Pipelines by Using Nanoparticles of Zinc Oxide and Poly Acrylic Acid

Optimizing pressure drop in 90° bend horizontal pipelines for dense slurry flow: A response surface methodology approach

Optimizing pressure drop in 90° bend horizontal pipelines for dense slurry flow: A response surface methodology approach

CFD Research on Natural Gas Sampling in a Horizontal Pipeline

Accurately determining if the sample parameters from a natural gas pipeline’s sampling system reflect the fluid characteristics of the main pipe has been a significant industry concern for many years. In this paper, samples of natural gas in a horizontal pipeline are investigated. CFD is used in this work and the turbulence is considered in the simulation. Firstly, the critical diameter for particles affected by gravity within such pipeline is determined. And then, the effects of the operation pressure and velocity of sampling branches on sample parameters, and the influence of particle density on these sample parameters, are analyzed. Finally, four different structures of sample branches for natural gas in a horizontal pipeline are compared. It is found that 100 μm is the critical diameter at which particles are affected by gravity; the operating pressure of the sampling branch has a significant impact on the particle mass concentration. The particle density has little impact on the sampling system. Overall, the design of the sampling branches does not cause significant sampling errors. This study provides guidance for optimal sampling in existing natural gas pipelines and enables effective monitoring of particle impurity content and properties in natural gas.

Experimental study on the influence of the riser on the gas-liquid flow in the horizontal pipeline of the offshore pipeline-riser system

The study of gas-liquid interface evolution and pressure fluctuation mechanism in the pipeline-riser system is the key to ensuring the safety of oil and gas transportation. This paper investigates the influence of the riser on the gas-liquid interface in the system with a 1657 m pipeline and risers of 16 m, 22 m, and 29 m. In severe slugging, the differential pressure in the horizontal pipeline exhibits a low-frequency large-amplitude fluctuation consistent with those in the riser. During the gas blowdown of the riser, the pressure fluctuation breaks the force equilibrium of the gas-liquid interface and induces numerous liquid slugs in the horizontal pipeline. A strong correlation is found between the differential pressure in the riser and the slug velocity in the horizontal pipeline by the Spearman Rank coefficient. The correlations between the slug velocity and the gas volume fraction and the void fraction under different riser heights are established, and the errors are 15% and 10%, respectively. The linear relationship between the Strouhal number of liquid slugs and the Lockhart-Martinelli parameter is constructed during the gas blowdown.

Simultaneous measurement of velocity field of liquid–solid particle flow in pipelines and analysis of flow characteristics

The liquid–solid particle flow within a horizontal pipeline is a typical particle-laden flow. The interplay between loaded particles and carrier phase engenders significant complexities in the dynamic behavior of such flows. We investigated the dynamics of a liquid–solid particle flow featuring dilute, slightly buoyant, hundred-micron-sized spherical particles fully suspended in the turbulent flow in a pipe, where Re is 7038. Cases with solid volume fractions of 0, 2.67 × 10-4, 5.33 × 10-4, 8.00 × 10-4, 1.07 × 10-3 and 1.33 × 10-3 were considered in this study. Experimental measurement techniques were utilized to acquire images of particles in the two-phase flow across the entire flow field via optical field feedback. Particle image velocimetry (PIV) and particle tracking velocimetry (PTV) were employed to simultaneously obtain liquid-phase velocity fields and particle trajectories. This approach allowed for a comprehensive depiction of the velocity field of each phase. Subsequently, a detailed explanation and analysis of the flow characteristics of the liquid–solid particle flow were provided based on the distribution of macroscopic velocity fields, the microscopic vorticity field, particle velocity vectors, and velocity slip. As a result, it was found that with the addition of solid particles and an increase in volume concentration, the drag effect of the solid phase and the trend of accumulation near the lower wall caused a decrease in the liquid phase velocity profile and deformation of the parabolic shape. In the liquid–solid particle flow with a volume concentration of 1.33 × 10-3, compared to the single-liquid phase flow, the standard deviation of velocity in the central region increased from 0.0097 m/s to 0.0159 m/s, and in the near-wall region, it increased from 0.0257 m/s to 0.0347 m/s, representing increases of 1.54 times and 1.26 times respectively. The proportion of medium vortices increased from 17 % to 30 %, nearly doubling. This study actively explores the concurrent measurement and flow characteristics of liquid–solid particle flow.

Experimental study of a leakage location method based on plug flow mass transfer characteristics

Leaks in water supply pipes pose a threat to water security. In order to save labor investment in pipeline leak location and to find a method to obtain the leak location by calculating upstream and downstream related data, an experimental study was conducted to investigate the plug flow mass transfer characteristics in horizontal pipelines. The results show that the addition of carbon dioxide gas can better detect the occurrence of small area ruptures in the pipeline. The translational velocity equation for elongated bubbles has better accuracy for both the insoluble gas air and the slightly soluble gas carbon dioxide. The local volumetric mass transfer coefficient shows a better linear relationship with the residual gas volume. The iterative equation derived from such a law can effectively predict the distribution of carbon dioxide concentrations in the pipeline. The study shows that the iterative equation, combined with the carbon dioxide concentration at a point downstream and the bubble translation velocity, can make a good localization judgment of the pipeline rupture point.

Motion Analysis of a Single Capsule in a Horizontal Hydraulic Pipeline

A Computational Fluid Dynamics (CFD) based solver is used to numerically analyze the motion of a single spherical capsule in a horizontal hydraulic pipeline. A novel numerical model is employed with the aid of the dynamic mesh technique for calculating the pressure and the velocity of the moving capsule. The numerical model comprises a 2m long straight test section of 50mm diameter. The results from the numerical model were close to those from the experimental data from the test rig developed in the study. The capsule is assumed to be a point mass rigid body and the coaxial-annular-flow model around the capsule is used to derive the boundary conditions for water flow at the capsule discontinuity region. The results are compared with experimental work done.

Identification of the Structure of Liquid–Gas Flow in a Horizontal Pipeline Using the Gamma-Ray Absorption and a Convolutional Neural Network

Knowledge of the liquid–gas flow regime is important for the proper control of many industrial processes (e.g., in the mining, nuclear, petrochemical, and environmental industries). The latest publications in this field concern the use of computational intelligence methods for flow structure recognition, which include, for example, expert systems and artificial neural networks. Generally, machine learning methods exploit various characteristics of sensors signals in the value, time, frequency, and time–frequency domain. In this work, the convolutional neural network (CNN) VGG-16 is applied for analysis of histogram images of signals obtained for water–air flow by using gamma-ray absorption. The experiments were carried out on the laboratory hydraulic installation fitted with a radiometric measurement system. The essential part of the hydraulic installation is a horizontal pipeline made of metalplex, 4.5 m long, with an internal diameter of 30 mm. The radiometric measurement set used in the investigation consists of a linear Am-241 radiation source with an energy of 59.5 keV and a scintillation detector with a NaI(Tl) crystal. In this work, four types of water–air flow regimes (plug, slug, bubble, and transitional plug–bubble) were studied. MATLAB 2022a software was used to analyze the measurement signal obtained from the detector. It was found that the CNN network correctly recognizes the flow regime in more than 90% of the cases.

The motion state of a spherical detector in a horizontal pipeline under different density ratio

Abstract Pipeline leakage can lead to serious environmental damage and industrial hazards. A spherical detector is a device for detecting pipeline leakage, which can locate the leakage position. To ensure the stable operation of the detector in a variety of media fluids, this paper uses the numerical simulation method to study the motion state of the sphere and the influence of different density fluids on its motion. It is found that the resistance and lift of the sphere under different density fluids are different, which will affect the motion trajectory of the detector and the speed of the stable stage. Therefore, the working environment of fluids with different densities needs to be considered when designing a spherical detector to ensure its stable operation in various fluid media.

Investigation of the kinematics behavior of spherical detector with different diameter ratios in oil pipelines

The spherical detector is an important technical equipment for water supply pipeline leakage detection. Its stable operation inside the pipeline will be affected by the fluid state in the pipeline, and the motion law of detectors with different diameters is different. In this paper, the dynamic analysis is carried out using the numerical simulation method, and the motion of spherical detectors with different diameters in horizontal oil pipelines is simulated. It is found that the flow state of the detector changes from the acceleration stage to the stable stage during the motion process, and with the decrease of the diameter ratio, the pressure difference between the front and back of the detector gradually increases, the thrust shows an upward trend, and the speed shows a greater speed in the stable stage. The motion behavior of the detector under different pipe diameter ratios is obtained, which provides help for the subsequent optimization of the shape design of the micro-leakage internal spherical detector.

Study on the Flow Characteristics of Heavy Oil-Water Two-Phase Flow in the Horizontal Pipeline.

Aiming at the problem of transportation for heavy oil during the middle-later development stages of the Lvda oilfield, based on the self-developed design of a visual circulating flow experimental apparatus for heavy oil-water two-phase flow-the flow regime characteristics and corresponding drag properties of the two-phase flow of Lvda viscous oil, which is simulated by 500# industrial white oil and water in a horizontal pipeline are investigated experimentally. According to the Kelvin-Helmholtz instability theory, the flow pattern transition criteria from stratified flow to annular flow (AF) are proposed. The effects of 0.11-0.90 m/s oil superficial velocities, 0.06-1.49 m/s water superficial velocities, and 0.09-0.93 input water cuts on the drag reduction effect of different flow regimes are analyzed. The experimental results indicated that with the increase of mixing velocity and water volume fraction, stratified flow, AF, oil plug flow, and dispersed oil lump flow are successively observed in the horizontal heavy oil-water two-phase flow, in which AF is the main flow pattern. As the Froude number increases to 4.0, the input water volume fraction does not change any more and remains at about 10% of the total flow rate in the process of converting from stratified flow to AF. The four delivery approaches can archive the reduction of transportation resistance for heavy oil at different degrees, in which the transportation of heavy oil surrounded by a water ring has the best effect of drag reduction. At the optimal working conditions of 0.61 m/s oil superficial velocity, 0.07 m/s water superficial velocity, and 0.10 input water cut, the pressure drop of water annulus conveying for heavy oil is only 1/62.54 of that of separate transport for pure heavy oil under the same oil flow rate.

Experimental study on flow around horizontal multiple pipelines laid on the erodible seabed surface

Experimental study on flow around horizontal multiple pipelines laid on the erodible seabed surface

Calculation of the required methanol consumption during the flow of wet hydrocarbon gas in a horizontal pipeline

One of the main problems that have to be solved during the development of hydrocarbon deposits is the formation of gas hydrates in pipelines. In this regard, the article presents a preventive method to struggle against the formation of gas hydrate deposits on the pipes inner walls associated with the supply of a hydrate formation inhibitor to the gas stream. The research was conducted on the basis of a mathematical model of the wet hydrocarbon gas flow in a horizontal pipeline. The research object is to determine the minimum required consumption of methanol, in which there is no formation of gas hydrate deposits on the channel inner walls. The practical significance of this study is that it is aimed at reducing the risks associated with the formation of gas hydrates in pipelines. The numerical implementation of a mathematical model of natural gas flow in a horizontal channel is based on a sequential solution of a system of four differential equations by the Runge-Kutta method of 4 orders of accuracy, followed by a search for sequential approximations of the minimum inhibitor flow rate, in which the "gas + water ↔ gas hydrate phase" transition process does not occur on the inner surface of the channel. The article presents a calculation of the proportion of a hydrate formation inhibitor in the liquid phase by solving a cubic equation using the Cardano method. Based on the computational experiments results, graphs were constructed and interpreted of the dependencies of the minimum inhibitor consumption on the soil temperature, inlet gas pressure, total water concentration in the gas flow, initial gas temperature and total gas flow rate.

A study of oil–water two-phase flow pattern recognition based on thermal sensors

To understand the flow characteristics and kinetic modelling of oil–water two-phase flow(OWTPF), this paper employs thermal array sensors to identify the flow pattern (FP) in OWTPF horizontal pipelines. Firstly, the thermal array sensor installation was constructed. Secondly, the time-varying characteristics of multi-feature signals were qualitatively analyzed using the adaptive optimal kernel time–frequency representation (AOK-TFR) method and unthresholded recurrence plot (URP) method. Finally, the sparrow search algorithm-support vector machine (SSA-SVM) machine learning algorithm is used for quantitative prediction of multi-feature classification, which leads to high prediction accuracy. The experiment proves that the correct rate of the thermal method in recognizing six types of OWTPF is above 91%, the correct rate of five types of flow is above 97.33%. This paper adopts the thermal method to identify the multiphase FP, which is a major innovation in this paper and also lays the foundation for recognizing the flow characteristics of multiphase flow.

Experiments and predictions for severe slugging of gas-liquid two-phase flows in a long-distance pipeline-riser system

Experiments concerning the flow regimes observed in gas-liquid two-phase flows in a long-distance pipeline-riser system were carried out and analyzed in this paper. The test loop with 0.075 m inner diameter consisted of a 314 m horizontal pipeline, followed by a 25 m downward-inclined pipe, and finally a 21.5 m riser pipe. An industrial-scale global flow regime map including 5 flow regimes was derived from differential pressure measurements in the riser and was used as a reference for improvements. Electrical capacitance volume tomography installed in the horizontal section was used to reconstruct the phase interface and calculate the average gas void fraction (GVF). An appropriate model for this system was selected by comparing the experimental GVF with different, widely used models. The occurrence of severe slugging flow (SS) can be predicted accurately using an improved model involving additional corrections that consider pipeline length, accurate GVF calculation, and gas density. This study supports the development of a suitable SS prediction model enabling safe design, operation, and control of practical systems.

Gas-liquid swirling flow behaviors and liquid-carrying mechanism inside a horizontal pipe

The behaviors of gas-liquid swirling flow under various swirler turns, neglected in previous studies, are essential for swirling flow applications. The role of swirler turns (1, 3, 5) in swirling flow characteristics was systematically investigated in a horizontal pipeline with an inner diameter of 32 mm. The temporal stability and circumferential symmetry of swirling liquid film become better with increasing swirler turns. The periodicity of the swirling liquid film interfacial wave induced by slug flow increases as the swirler turns decrease, while the main wave frequency decreases. Interestingly, for the original slug flow, the downstream void fraction probability density function curves are bimodal with 3 and 5 turns, while it is single-peaked at the swirler with 1 turn. The effectiveness of swirler with 1 turn, 3 turns, and 5 turns in promoting carrying liquid was 100 %, 82.08 %, and 89.22 %, respectively. The mechanism of liquid-carrying was explained in terms of perturbation waves and momentum transfer in the gas-liquid interface. Based on the homogeneous flow model and separated flow model, two predictive models for swirler pressure loss were proposed with maximum errors of 14.67 % and 17.86 %, respectively.

A novel method for accurate pressure drop prediction in horizontal and near horizontal pipes using adaptive neuro fuzzy inference system based model

Effective flow line and piping network design depends on the accurate prediction of pressure drop in multiphase flow for horizontal and near horizontal pipes. Since early 1950, several empirical correlations and mechanistic models have been developed to predict pressure drop. All correlations used by the industry, in addition to their applicability limitations, fall short of providing the necessary precision of pressure drop predictions. However, compared to empirical correlations, the recently developed mechanistic models improved pressure drop prediction. To design and construct more dependable and economical surface piping networks and wells, it is still necessary to improve prediction accuracy. This study uses the Adaptive Neuro-Fuzzy Inference System (ANFIS) to create a model that predicts pressure drop in horizontal and near-horizontal pipelines with greater accuracy and simplicity. Using the ANFIS method, the fuzzy modelling procedure can gather knowledge about a set of data to determine the membership function parameters that will enable the associated fuzzy inference system to track input/output data most effectively. The model was created and tested using field data encompassing various variables. The model was developed using 450 different data sets that were collected from the Asian continent. 113 data sets were used for testing, and a total of 337 data sets were used for training. Trend analysis was carried out during the model development phase prior to the model’s completion. This is performed to make sure the model is stable and to make sure the created model is physically sound and accurately simulates the real physical process. To determine the percentage of error between the predicted value and the actual measured data, statistical analysis was carried out. To compare the performance of the new ANFIS model to earlier empirical correlations and mechanistic models, graphical and statistical techniques were also used. The new model outperformed known correlations and the most recent mechanistic models by a significant margin in producing incredibly accurate pressure drop predictions. The Dukler et al. empirical correlation, Beggs and Brill empirical correlation, Xiao mechanistic model, and Gomez mechanistic model had values of 25.284, 20.940, 30.122, and 20.817, respectively, while the ANFIS model had a value of 13.256 for the lowest average absolute percentage error. Additionally, the Duckler and Beggs & Brill models came in second and third, with values of 0.908 and 0.906, respectively, and the ANFIS model had the highest coefficient of determination at 0.955.