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198 results on '"Liao, Ruiquan"'

57. Experimental Study, Characterization and Application of Starch-Graft-Acrylamide Gel for Plugging

Author

Liu Gang, Liao Ruiquan, Cheng Li, Kangwei Zhang, Long Yuan, Zhang Manlai, and Zhen Li

Subjects
lcsh:TN1-997, Materials science, Starch, Scanning electron microscope, microstructure, Microstructure, modified starch gel, Modified starch, chemistry.chemical_compound, Viscosity, plug, chemistry, Chemical engineering, Acrylamide, General Materials Science, Fourier transform infrared spectroscopy, Polyacrylamide gel electrophoresis, lcsh:Mining engineering. Metallurgy, snubbing service
Abstract

During underbalance drilling, completion and workover wells, plugging channeling, blocking preformation and plugging formation water are inevitable problems. Gel is one of the most effective and convenient method to solve the problem. In this study, modified starch gel is synthesized, investigated experimentally and improved for efficient oil and gas field applications. The gel slurry is composed of starch (3.6 wt.%), initiator (0.02 wt.%), acrylamide (14.4 wt.%), cross-linking agent (4.7 wt.%), all of the components are mixed together with water at pH 10 – 11 which viscosity is as low as 35 – 82 mPa.s and desired to form gel. Here the effects of the components, reaction temperature and pH on gelation time and gel viscosity are systematically investigated, and the results showed that the gelation can be controlled in a wide range 30 – 120 min efficiently by pH and initiator. Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope (SEM) are employed to study the molecular structure and microstructure of the gel, respectively. A compact three-dimensional network structure was formed in the gel, which contribute to a good adhesion. The gel has been successfully used in shale gas field which provides a reference for sealing other similar high formation pressure under unbalanced workover treatment. DOI: http://dx.doi.org/10.5755/j01.ms.24.4.18565

Published
2018

78. Research on modifying effects of cellulose on the mechanical properties of chromium gel

Author

Liao Ruiquan, Yin Yuchuan, Cheng Li, Chen Chao, Liu Deji, and Zhang Manlai

Subjects
chemistry.chemical_classification, Toughness, Materials science, Scanning electron microscope, Polyacrylamide, 0211 other engineering and technologies, chemistry.chemical_element, 02 engineering and technology, General Chemistry, Polymer, 021001 nanoscience & nanotechnology, Condensed Matter Physics, Electronic, Optical and Magnetic Materials, Biomaterials, chemistry.chemical_compound, Chromium, Viscosity, chemistry, 021105 building & construction, Materials Chemistry, Ceramics and Composites, Cellulose, Deformation (engineering), Composite material, 0210 nano-technology
Abstract

A chromium gel formed through the cross-linking reaction with partially hydrolyzed polyacrylamide and Cr3+, known as Cr3+ gel, has been demonstrated to use in petroleum engineering for its special mechanical properties in this paper. This study has revealed that the addition of cellulose can successfully enhance the gas sealing ability of a gel slug in a wellbore. Scanning electron microscopy was employed to understand the cross-linked structure of the Cr3+ gel. Furthermore, the mechanical properties were studied, revealing that the maximum tensile strain increased from 2.07 to 3.45 with shear strains increasing from 1.32 to 1.45. Additionally, the cementing strength of modified gel characterized by the maximum pull-out force decreased from 13.1 to 7.2 N. The pull-out force changed smoothly with the displacement due to the viscous resistance increased. In this study, a systemic test method for the mechanical properties of Cr3+ gel was proposed, and the roles of cellulose in enhancing the toughness and viscosity of gel were attained.

Published
2016
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79. Visible Research of Loading Speed in Vertical Gas Well

Author

Liu Jie, Wang Xiuwu, Liao Ruiquan, and Wang Xiaowei

Subjects
Wellbore, General Energy, Chemistry, Loading rate, Formation water, Geotechnical engineering, Rate equation, Mechanics, Water production
Abstract

For gas well under certain conditions, formation water production is inevitable in the later development; Formation water production is harmful to the normal production, it may cause liquid loading, flooding or even stop production. Based on the study of liquid loading and the rate laws of liquid loading, taking corresponding measures for the gas well is important. Simulating formation liquid production of gas wells with single rate under wellbore conditions, observing and measuring liquid loading rate through the experiment, summing up the liquid loading rate law of wellbore, are significant to the stability of gas well.

Published
2015
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80. Prediction of Pressure Gradient in Two and Three-phase Flows in Horizontal Pipes Using an Artificial Neural Network Model

Author

Ribeiro, Joseph Xavier Francisco, Liao, Ruiquan, Aliyu, Aliyu Musa, Liu, Zilong, Ribeiro, Joseph Xavier Francisco, Liao, Ruiquan, Aliyu, Aliyu Musa, and Liu, Zilong

Abstract

Concurrent flow of gas with a mixture of oil and water in production equipment is common necessitating the need for additional investigations to gain more insight and development of more accurate correlations for prediction of flow characteristics including pressure drop. In this study, an experimental study was conducted using air-water and air-water-oil mixtures in a 0.075-m diameter pipe. Superficial gas and liquid velocities ranged from 0.03 to 0.13 m/s and 1.26 to 41.58 m/s respectively. Slug flow was the main flow pattern observed. In addition, transition to annular and annular flow were also observed. Due to the homogeneous nature of the oil-water-air mixture, the three-phase flow was evaluated as a pseudo-two-phase mixture. An Artificial Neural Network (ANN) model developed for the prediction of two- and three- phase pressure drop performed better than all models considered during the evaluation. Generally, it is found that the accuracies for pressure drop were considered adequate.

Published
2019

83. Upward interfacial friction factor in gas and high-viscosity liquid flows in vertical pipes.

Author

Ribeiro, Joseph Xavier Francisco, Liao, Ruiquan, Aliyu, Aliyu Musa, and Liu, Zilong

Subjects
*INTERFACIAL friction, *PIPE flow, *VISCOSITY, *ANNULAR flow, *TRANSITION flow, *ARTIFICIAL neural networks
Abstract

In this study, experiments were carried out in a vertical 60-mm internal diameter pipe with air and oil (viscosities 100–330 mPa s) constituting the gas and liquid phases. Superficial air and oil velocity ranges used were 9.81–59.06 m/s and 0.024–0.165 m/s, respectively. Visual observations and change in slope of pressure drop– V s g plot were used to identify flow pattern transition to annular flow. Using the experimental data as well as other reported data, a new correlation to predict interfacial friction factor in upward gas–viscous liquid annular flow regime was developed. Compared to the performance of 16 existing correlations using higher viscosity liquids, that of the new correlation was better. The performance of another correlation we derived for predictions at both low and higher low viscous showed good agreement with measurements. In addition, a neural network model to predict the interfacial friction factor involving both low and high viscous liquids was developed and it excellently described the experimental data. [ABSTRACT FROM AUTHOR]

Published
2020
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92. Prediction of Pressure Gradient in Two and Three-Phase Flows in Vertical Pipes Using an Artificial Neural Network Model.

Author

Francisco Ribeiro, Joseph Xavier, Liao, Ruiquan, Aliyu, Aliyu Musa, and Liu, Zilong

Subjects
ARTIFICIAL neural networks, PIPE flow, ANNULAR flow, PIPE, GAS flow, PETROLEUM production
Abstract

The concurrent flow of gas with a mixture of oil and water is often observed in production tubing in the petroleum industry. Lack of physical understanding of the several phenomenological characteristics of three-phase flow can lead to unsatisfactory production rates or even oversizing of pipelines. Additional investigations to gain more insight and development of more accurate correlations for prediction of flow characteristics including pressure drop is necessary. In this study, an experimental study was conducted using air-water and air-water-oil mixtures in a 0.075m diameter pipe. Superficial gas and liquid velocities ranged from 0.03 to 0.13 m/s and 1.26 to 41.58 m/s respectively. Slug flow was the main flow pattern observed. In addition, the transition from churn to annular flow and annular were also observed. Due to the homogeneous nature of the oil-water-air mixture, the three-phase flow was evaluated as a pseudo-two-phase mixture. An Artificial Neural Network (ANN) model developed for the prediction of two-phase and three-phase pressure drop performed better than all models considered during the evaluation. Generally, it was found that the accuracies for pressure drop were considered adequate. [ABSTRACT FROM AUTHOR]

Published
2019

96. The Particle Swarm Optimization Algorithm with Adaptive Chaos Perturbation

Author

Liao Ruiquan, Dong Yong, and Li Mengxia

Subjects
Mathematical optimization, education.field_of_study, Computer Networks and Communications, ComputingMethodologies_MISCELLANEOUS, 010401 analytical chemistry, Population, MathematicsofComputing_NUMERICALANALYSIS, Particle swarm optimization, 02 engineering and technology, 01 natural sciences, Swarm intelligence, 0104 chemical sciences, Computer Science Applications, Computational Theory and Mathematics, Simulated annealing, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Particle velocity, Multi-swarm optimization, education, Metaheuristic, Algorithm, Mathematics, Premature convergence
Abstract

Aiming at the two characteristics of premature convergence of particle swarm optimization that the particle velocity approaches 0 and particle swarm congregate, this paper learns from the annealing function of the simulated annealing algorithm and adaptively and dynamically adjusts inertia weights according to the velocity information of particles to avoid approaching 0 untimely. This paper uses the good uniformity of Anderson chaotic mapping and performs chaos perturbation to part of particles based on the information of variance of the population’s fitness to avoid the untimely aggregation of particle swarm. The numerical simulations of five test functions are performed and the results are compared with several swarm intelligence heuristic algorithms. The results shows that the modified algorithm can keep the population diversity well in the middle stage of the iterative process and it can improve the mean best of the algorithm and the success rate of search.

Published
2016
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