The Impacts of Pore Structure and Relative Humidity on Gas Transport in Shale: A Numerical Study by the Image-Based Multi-scale Pore Network Model

Author(s):  
Wenhui Song ◽  
Jun Yao ◽  
Kai Zhang ◽  
Hai Sun ◽  
Yongfei Yang
2019 ◽  
Vol 282 ◽  
pp. 02024
Author(s):  
Muhammad Islahuddin ◽  
Chi Feng ◽  
Steven Claes ◽  
Hans Janssen

Hygric properties can be estimated directly from pore structure information, represented by a network of regularly shaped pores, extracted from a pore structure image to conserve the real topology. On this network, pore-scale models of moisture behaviour determine the hygric properties of moisture storage and transport. The reliability of this approach is validated with a sintered-glass filter. Despite its more limited heterogeneity and pore size range relative to typical porous building materials, it provides a good basis for validating crucial pore-scale moisture processes. Measured storage data compare well to the estimated ad- and desorption moisture retention curves as well as to the saturated and capillary moisture content. Furthermore, the simulated whole-range moisture permeability curve agrees acceptably with measured data. The variation in modelling the pore space as a pore network model is also analysed by considering two distinct pore network extraction methods. The measured and simulated moisture contents agree well for the whole capillary range. Moreover, the resulting transport properties are generally accurate for the whole moisture content range. On the other hand, the estimated vapour permeabilities show notable variations between the two pore network models.


SPE Journal ◽  
2020 ◽  
Author(s):  
Sen Wang ◽  
Qihong Feng ◽  
Farzam Javadpour ◽  
Ming Zha ◽  
Ronghao Cui

Summary The physics of gas transport through shale systems remains ambiguous. Although several theoretical and experimental studies have been reported, most concentrate only on the permeability of shale kerogen. Shales, however, are composed of various proportions of organic matter and inorganic minerals (e.g., calcite and clay). Inorganic pores are larger than organic pores, thus affecting apparent permeability. To accurately predict the apparent permeability of shale, we couple molecular dynamics (MD) and a pore-network model (PNM) to develop a multiscale framework for gas flow through shales. First, we use nonequilibrium MD (NEMD) to study the pressure-driven flow behavior of methane (CH4) through organic, calcite, and clay [montmorillonite (MMT)] nanopores under reservoir conditions, from which, using the slip-corrected Poiseuille equation, we propose a mass-transport model accounting for the contributions of both the adsorbed-phase fluid and bulk fluid. Then, we incorporate these formulations into a shale PNM in which the influences of shale composition and bimodal pore-size distribution (PSD) are taken into account. We also develop an analytical model for the apparent permeability of shale matrix using the bundle-of-capillaries approach. In comparison with previous methods, our proposed models highlight the effect of relatively greater pore sizes in inorganic matrices. This work provides an efficient tool for better understanding gas transport through shale systems at both molecular and pore scales.


Author(s):  
Minxia He ◽  
Yingfang Zhou ◽  
Bintao Chen ◽  
Tao Zhang ◽  
Keliu Wu ◽  
...  

2014 ◽  
Vol 490-491 ◽  
pp. 1560-1564
Author(s):  
Zhao Bin Zhang ◽  
Mian Lin

Buoyancy-driven oil cluster jumping in porous media is studied by a dynamic pore-network model in relation to secondary oil migration. The model has two novel aspects. First, inertia of fluid and surface roughness of throat are taken into account in simulating the jumping process. Second, a probability technique is proposed to let the model allow a longer time step. The numerical results indicate that the dynamic process of buoyancy-driven cluster jumping is caused not only by porous media heterogeneity, but also by fluid inertia and throat surface roughness. Pressure field characteristics in jumping are studied and a cluster-based pressure solving technique is proposed to reduce the computational demanding of pressure solving. Some statistical characteristics, include cluster size distribution and residual oil saturation, are also studied.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Di Zhang ◽  
Xinghao Zhang ◽  
Haohao Guo ◽  
Dantong Lin ◽  
Jay N. Meegoda ◽  
...  

AbstractThe permeability of shale is a significant and important design parameter for shale gas extraction. The shale gas permeability is usually obtained based on Darcy flow using standard laboratory permeability tests done on core samples, that do not account for different transport mechanisms at high pressures and anisotropic effects in shales due to nano-scale pore structure. In this study, the permeability of shale is predicted using a pore network model. The characteristics of pore structure can be described by specific parameters, including porosity, pore body and pore throat sizes and distributions and coordination numbers. The anisotropy was incorporated into the model using a coordination number ratio, and an algorithm that was developed for connections of pores in the shale formation. By predicting hydraulic connectivity and comparing it with several high-pressure permeability tests, the proposed three-dimensional pore network model was verified. Results show that the prediction from the anisotropic pore network model is closer to the test results than that based on the isotropic pore network model. The predicted permeability values from numerical simulation using anisotropic pore network model for four shales from Qaidam Basin, China are quite similar to those measured from laboratory tests. This study confirmed that the developed anisotropic three-dimensional pore network model could reasonably represent the natural gas flow in the actual shale formation so that it can be used as a prediction tool.


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