Pipe Diameter Effect on Liquid Loading in Vertical Gas Wells

Kelkar, Mohan; Pereyra, Eduardo; Skopich, Anton; Sarica, Cem

doi:10.2118/164477-ms

Cited by 9 publications

(2 citation statements)

References 8 publications

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“…In order to make such an evaluation, we have gathered an experimental databank (Table 2) of purely large pipe data of low-high gas flow from bubbly to annular flow. The databank consists of the current measurements in a 101.6 mm vertical pipe system (reported in previous sections); as well as the measurements of Zangana [28] and Van der Meulen [29] in 127 mm diameter flow loops at the University of Nottingham; and Skopich et al [30] in a 101.6 mm vertical pipe at the University of Tulsa, Oklahoma. The test facility, located in the PSE Laboratory at Cranfield University, comprises of three sections namely the fluid supply and metering section; test section; and the phase separation section.…”

Section: Void Fraction Correlations and Datamentioning

confidence: 99%

Void fraction development in gas-liquid flow after a U-bend in a vertically upwards serpentine-configuration large-diameter pipe

et al. 2017

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We investigate the effect of a return U-bend on flow behaviour in the vertical upward section of a largediameter pipe. A wire mesh sensor was employed to study the void fraction distributions at axial distances of 5, 28 and 47 pipe diameters after the upstream bottom bend. It was found that, the bottom bend has considerable impacts on up-flow behaviours. In all conditions, contour plots of the crosssectional phase distribution measurement using the wire mesh sensor (WMS) show that centrifugal effect of the U-bend causes appreciable misdistribution in the adjacent straight section. However, flow asymmetry significantly reduces at an axial distance of 47D from the U-bend. Flow regime maps generated from three axial locations showed that, in addition to bubbly, intermittent and annular flows, oscillatory flow occurred particularly when gas and liquid flow rates were relatively low. At this position, the mean void fractions were in agreement with those from other large-pipe studies.Comparisons were made with existing void fraction correlations. Among the correlations surveyed, drift flux-type correlations were found to give the best predictive results.

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Section: Void Fraction Correlations and Datamentioning

confidence: 99%

Void fraction development in gas-liquid flow after a U-bend in a vertically upwards serpentine-configuration large-diameter pipe

et al. 2017

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“…The results suggested that one should not only consider Turner's or Wallis's criteria but also take into account the reservoir behavior when analyzing the liquid loading initiation. Different from Waltrich's research, Skopich et al (2015) did some researches on the influence of pipe diameter on the initiation of liquid loading. 2-in and 4-in ID pipes were used in the two-phase flow experiments.…”

Section: Introductionmentioning

confidence: 99%

An experimental study of liquid unloading in the curve section of horizontal gas wells

Shi

Han

et al. 2021

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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Liquid unloading is a very common and important issue in horizontal gas wells, and the presence of curve sections increases the complexity of the phenomenon and its study. Liquid loading in a gas well will sharply reduce production, therefore, the liquid-unloading onset of different curved pipes is essential to gas production. In this work, liquid-unloading onset experiments were conducted in curved pipes with different curvatures. Then, the critical gas velocity VsgCR can be determined according to the measured pressure gradients, liquid holdup, and liquid film reversal. This work analyzes the factors which will lead to the liquid unloading and explores the trend of the pipe curvature’s influence on the liquid unloading under laboratory conditions. The experimental results show that the critical gas velocity rises with the increase of pipe curvature, the increase is mainly due to the centrifugal force. The present work also compares the predicted results of the OLGA model and Beggs–Brill model with experimental data. The comparison results indicate that both models fit relatively well to the experimental data at the low superficial gas velocity, and both models have poor performance at high superficial gas velocity. The OLGA model fits the experimental data better than the Beggs–Brill model at high superficial gas velocity. The error analysis shows that most of the predicted data is not in good agreement with experimental data. Some errors between experimental data and calculation results are out of the range of 50%.

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Modelling of liquid loading in gas wells using a software-based approach

Abhulimen

Oladipupo

2022

J Petrol Explor Prod Technol

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Liquid loading is the most common operational problem influencing gas well productivity for the petroleum operator. Liquid loading is defined as an operational constraint that is associated with gas wells where the major driving mechanism for hydrocarbon production is by the associated gas-driven mechanisms. Liquid loading occurs when liquid accumulated in the tubing or casing results in the gas velocity lower than the critical value (the minimum velocity required for gas to push the liquid out of the gas well), which overtime leads to a hydrostatic back pressure greater than the formation pressure of the well, thereby limiting the flow of gas into the well. The continuous build-up of pressure from liquid loading eventually minimizes well productivity and expensive work over operations. However, current mathematical models to predict liquid loading are flawed with varying inaccuracies and depending on the models deployed will ultimately lead to loss of production time and well productivity. In our work we present prediction of liquid loading using a software-based model incorporating the particle swarm optimization algorithm, genetic algorithm, and artificial neural network and Bayesian neural network algorithms applications. The results of our research findings show that artificial neural network software-based model with a simulated accuracy of 93% and 92% for test and trained data, respectively, outperformed the particle swarm optimization data-driven model with a simulated sensitivity accuracy of 92% and 83%, and genetic algorithm data-driven models with a simulated accuracy of 89% and 83%. The Bayesian neural network was postulated as a robust model because of its simplicity shown to have simulated accuracy of 77% and 73% for train and test data, respectively. Thus software-based code environment and data-driven model developed and presented in this paper may resolve many of current deficiencies and gaps in the current technical literature to predict liquid loading with high precision offering saving in millions of dollars to the operators.

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Pipe Diameter Effect on Liquid Loading in Vertical Gas Wells

Cited by 9 publications

References 8 publications

Void fraction development in gas-liquid flow after a U-bend in a vertically upwards serpentine-configuration large-diameter pipe

Void fraction development in gas-liquid flow after a U-bend in a vertically upwards serpentine-configuration large-diameter pipe

An experimental study of liquid unloading in the curve section of horizontal gas wells

Modelling of liquid loading in gas wells using a software-based approach

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