The Experts below are selected from a list of 108 Experts worldwide ranked by ideXlab platform
Dongxiao Zhang - One of the best experts on this subject based on the ideXlab platform.
-
Numerical simulation of Proppant transport in hydraulic fracture with the upscaling CFD-DEM method
Journal of Natural Gas Science and Engineering, 2016Co-Authors: Junsheng Zeng, Dongxiao ZhangAbstract:Abstract In this study, the coupled CFD (Computational Fluid Dynamics)-DEM (Discrete Element Method) method is employed to simulate the Proppant transport process in a hydraulic fracturing system. The Particle-Particle and Particle-wall interactions can be captured precisely in the DEM, which could not be fully considered in other methods. However, the DEM is time-consuming if every single Proppant Particle is considered as a discrete element. In order to reduce the computational efforts, the representative Particle model (RPM) is adopted in this work for upscaling the CFD-DEM. Dynamic packing problems of both the uniform and bi-density cases are designed to illustrate the advantage of simulating Proppant transport behaviors with the CFD-DEM, and the upscaling cases are performed with the RPM for comparison. In addition, upscaling issues regarding validation and large-scale applications of the RRM are also discussed. After upscaling, the main characteristics of the packing patterns can be captured, while the time cost is greatly reduced.
Zhang Dongxiao - One of the best experts on this subject based on the ideXlab platform.
-
Numerical simulation of Proppant transport in hydraulic fracture with the upscaling CFD-DEM method
JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING, 2016Co-Authors: Zeng Junsheng, Li Heng, Zhang DongxiaoAbstract:In this study, the coupled CFD (Computational Fluid Dynamics)-DEM (Discrete Element Method) method is employed to simulate the Proppant transport process in a hydraulic fracturing system. The Particle Particle and Particle-wall interactions can be captured precisely in the DEM, which could not be fully considered in other methods. However, the DEM is time-consuming if every single Proppant Particle is considered as a discrete element. In order to reduce the computational efforts, the representative Particle model (RPM) is adopted in this work for upscaling the CFD-DEM. Dynamic packing problems of both the uniform and bi-density cases are designed to illustrate the advantage of simulating Proppant transport behaviors with the CFD-DEM, and the upscaling cases are performed with the RPM for comparison. In addition, upscaling issues regarding validation and large-scale applications of the RRM are also discussed. After upscaling, the main characteristics of the packing patterns can be captured, while the time cost is greatly reduced. (C) 2016 Elsevier B.V. All rights reserved.Ministry of Science and Technology of China [2013AA064501]; National Natural Science Foundation of China [U1262204, U1663208, 51520105005]SCI(E)EIARTICLEliheng@coe.pku.edu.cn264-2773
Jie Zeng - One of the best experts on this subject based on the ideXlab platform.
-
Numerical Investigation on Proppant–Water Mixture Transport in Slot under High Reynolds Number Conditions
Energies, 2020Co-Authors: Tao Zhang, Jianchun Guo, Ruoyu Yang, Jie ZengAbstract:Water hydraulic fracturing involves pumping low viscosity fluid and Proppant mixture into the artificial fracture under a high pumping rate. In that high Reynolds number conditions (HRNCs, Re > 2000), the turbulence effect is one of the key factors affecting Proppant transportation and placement. In this paper, a Eulerian multiphase model was used to simulate the Proppant Particle transport in a parallel slot under HRNCs. Turbulence effects in high pumping rates and frictional stress among the Proppant Particles were taken into consideration, and the Johnson-Jackson wall boundary conditions were used to describe the Particle-wall interaction. The numerical simulation result was validated with laboratory-scale slot experiment results. The simulation results demonstrate that the pattern of the Proppant bank is significantly affected by the vortex near the wellbore, and the whole Proppant transport process can be divided into four stages under HRNCs. Furthermore, the Proppant placement structure and the equilibrium height of Proppant dune under HRNCs are comprehensively discussed by a parametrical study, including injection position, velocity, Proppant density, concentration, and diameter. As the injection position changes from the lower one to the top one, the unpropped area near the entrance decrease by 7.1 times, and the equilibrium height for the primary dune increase by 5.3%. As the velocity of the slurry jet increases from 2 m/s to 5 m/s (Re = 2000–5000), the vortex becomes stronger, so the non-propped area near the inlet increase by 5.3 times, and the equilibrium height decrease by 5.2%. The change of Proppant properties does not significantly change the vortex; however, the equilibrium height is affected by the high-speed flush. Thus, the conventional equilibrium height prediction correlation is not suitable for the HRNCs. Therefore, a modified bi-power law prediction correlation was proposed based on the simulation data, which can be used to accurately predict the equilibrium height of the Proppant bank under HRNCs (mean deviation = 3.8%).
-
Numerical Modeling of the Conductivity of the Particle Monolayer with Reduced Size
Geofluids, 2018Co-Authors: Yuxuan Liu, Wang Jiandong, Jianchun Guo, Haiyan Zhu, Jie ZengAbstract:Fractures filled with a Proppant monolayer play an important role in the hydraulic fracture network. Predicting the conductivity of these fractures is the basis of fracture network optimization. However, little attention has been paid to the conductivity of the Proppant monolayer. The change of conductivity under various conditions is currently not fully understood. Therefore, in this paper, the conductivity variation under different conditions are simulated. The reduction of Particle size was calculated by existing analytical models. The permeability variation was calculated through computational fluid dynamics (CFD) combined with COMSOL Multiphysics. The controlling factors of conductivity under a Proppant monolayer were identified. Simulation results indicate that elastic parameters, closure pressure, and Proppant distribution have significant influence on conductivity, while creep parameters, such as rock viscosity and time, have limited influence on conductivity. Moreover, the changes in permeability, porosity, and tortuosity with variation of embedment were analyzed. Results indicated that with an increase in embedment, the permeability and porosity decrease as expected. The main reduction (nearly half) emerges in the first 20% of Proppant embedment. Furthermore, the permeability of a single Particle deviates largely from the prediction of Carman-Kozeny (CK) equation. The tortuosity of Proppant Particle increases with a decrease in Particle size due to embedment. A modification of the Carman-Kozeny equation is proposed to address this influence.
Yaorong Feng - One of the best experts on this subject based on the ideXlab platform.
-
Migration of variable density Proppant Particles in hydraulic fracture in coal-bed methane reservoir
Journal of Natural Gas Science and Engineering, 2016Co-Authors: Shangyu Yang, Lihong Han, Jianjun Wang, Yaorong FengAbstract:Abstract The well performance in Coal-Bed Methane (CBM) reservoir is highly dependent on the conductivity of hydraulic fracture created to increase well production rate and contact area with the reservoir. Aimed at improving the effective fracture length of hydraulic fracture in CBM reservoir and the seam Proppant concentration, the objective of this paper is to investigate the migration of variable density Proppant Particles in hydraulic fracture and seams using numerical modeling and simulation. In the proposed model, the interaction among fracture Proppant Particles distributed in a pseudo fluid model is taken into consideration. Comparison between the model calculation and field radioactive tracing logging interpretation shows that the proposed model is accurate and reliable in applications. Additionally, we carried out the sensitivity study on the viscosity of fracking fluid, fracture area, Proppant density, injection rate and other factors. It is shown that, with the condition of a confining pressure of 69 MPa and an ambient temperature of 90 °C, the crush value of nutshell Proppant is less than 2%, which meets the field application requirements. Furthermore, with the increase of both fracturing fluid viscosity and injection rate, the propped effective fracture length increases, and lead to a more uniform distribution of Proppants. The increase in Proppant Particle diameter, inversely, results in a decrease in the effective fracture length. As for variable-density Proppant, the effective crack support length would be longer than the single ceramic Proppant, and the Particle distribution of the case with variable density is more uniform.
Junsheng Zeng - One of the best experts on this subject based on the ideXlab platform.
-
Numerical simulation of Proppant transport in hydraulic fracture with the upscaling CFD-DEM method
Journal of Natural Gas Science and Engineering, 2016Co-Authors: Junsheng Zeng, Dongxiao ZhangAbstract:Abstract In this study, the coupled CFD (Computational Fluid Dynamics)-DEM (Discrete Element Method) method is employed to simulate the Proppant transport process in a hydraulic fracturing system. The Particle-Particle and Particle-wall interactions can be captured precisely in the DEM, which could not be fully considered in other methods. However, the DEM is time-consuming if every single Proppant Particle is considered as a discrete element. In order to reduce the computational efforts, the representative Particle model (RPM) is adopted in this work for upscaling the CFD-DEM. Dynamic packing problems of both the uniform and bi-density cases are designed to illustrate the advantage of simulating Proppant transport behaviors with the CFD-DEM, and the upscaling cases are performed with the RPM for comparison. In addition, upscaling issues regarding validation and large-scale applications of the RRM are also discussed. After upscaling, the main characteristics of the packing patterns can be captured, while the time cost is greatly reduced.
