Search

Due to the low permeability of tight reservoirs, throats play a significant role in controlling fluid flow. Although many studies have been conducted to investigate fluid flow in throats in the microscale domain, comparatively fewer works have been devoted to study the effect of adsorption boundary layer (ABL) in throats based on the digital rock method. By considering an ABL, we investigate its effects on fluid flow. We build digital rock model based on computed tomography technology. Then, microscopic pore structures are extracted with watershed segmentation and pore geometries are meshed through Delaunay triangulation approach. Finally, using the meshed digital simulation model and finite element method, we investigate the effects of viscosity and thickness of ABL on microscale flow. Our results demonstrate that viscosity and thickness of ABL are major factors that significantly hinder fluid flow in throats. [ABSTRACT FROM AUTHOR]

• The presence of solid beds in turbulent pipe flows results in secondary fluid motions which impacts particle transport dynamics. • Streamwise vorticity due to corners in the cross-sectional plane of pipes is increased as the pipe bed height increases. • Particles are influenced by the secondary flows, with particles in a half-pipe less likely to concentrate near the upper walls. • The secondary flows also modify the deposition and resuspension rates of particles, particularly near the corners of the bed. Turbulent particle-laden flows in pipes can result in particle deposition leading to the formation of solid beds. The presence of such beds modifies the flow field, resulting in secondary motions in the plane of the pipe cross-section, which in turn impact particle transport. In this work turbulent pipe flows with equal mass flow rates and solid beds of height H b = 0 (full pipe), 0.5 R (three-quarter pipe), and R (half pipe) are predicted using direct numerical simulation, with the beds represented simplistically as flat surfaces. The particulate phase is one-way coupled to the flow at a volume fraction of 10−3 and particle motion is solved for using a Lagrangian point-particle approach. The Reynolds numbers computed based on bulk velocity and equivalent pipe diameter for the full, ¾ and, ½ pipes are 5,300, 5,909 and 7,494, respectively. The same particle size is used in all the simulations and their respective Stokes numbers, based on the shear timescale, are 0.5, 1.2 and 1.9, respectively. The results for flows with beds show that the fluid flow exhibits secondary vortices and an increase in the mean streamwise vorticity caused by corners in the cross-sectional plane of the pipes, with their intensity near the upper curved wall increasing with H b. However, the upper vortices remain relative weak compared to those in lower regions of the pipes. The increase in mean streamwise vorticity in the half pipe is larger than that in the three-quarter pipe near the upper curved wall, while similar near the flat pipe floor due to the resistance of the curved wall to secondary motions. The movement of the particles in the cross-sectional plane is consistent with that of the secondary flows, but with slightly lower velocities. In regions near the wall away from the pipe corners, particle concentration in the half pipe is lower than in the three-quarter pipe, most likely due to its thinner boundary layer. This is reversed for concentration maxima near the pipe corners because of the magnitude of the secondary flows. Finally, the secondary flow changes the deposition or resuspension rate of the particles, particularly near the pipe corners, but these are always less than equivalent rates in the full pipe flow, which is likely caused by the magnitude of the wall unit. [Display omitted] [ABSTRACT FROM AUTHOR]

In practical development of unconventional reservoirs, fracture networks are a highly conductive transport media for subsurface fluid flow. Therefore, it is crucial to clearly determine the fracture properties used in production forecast. However, it is different to calibrate the properties of fracture networks because it is an inverse problem with multi-patterns and high-complexity of fracture distribution and inherent defect of multiplicity of solution. In this paper, in order to solve the problem, the complex fracture model is divided into two sub-systems, namely "Pattern A" and "Pattern B." In addition, the generation method is grouped into two categories. Firstly, we construct each sub-system based on the probability density function of the fracture properties. Secondly, we recombine the sub-systems into an integral complex fracture system. Based on the generation mechanism, the estimation of the complex fracture from dynamic performance and observation data can be solved as an inverse problem. In this study, the Bayesian formulation is used to quantify the uncertainty of fracture properties. To minimize observation data misfit immediately as it occurs, we optimize the updated properties by a simultaneous perturbation stochastic algorithm which requires only two measurements of the loss function. In numerical experiments, we firstly visualize that small-scale fractures significantly contribute to the flow simulation. Then, we demonstrate the suitability and effectiveness of the Bayesian formulation for calibrating the complex fracture model in the following simulation. [ABSTRACT FROM AUTHOR]