The effect of pore-structure on hysteresis in relative permeability and capillary pressure: Pore-level modeling

Jerauld, Gary; Salter, S.J.

doi:10.1007/bf00144600

Cited by 390 publications

(229 citation statements)

References 83 publications

(76 reference statements)

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“…As has been noted by many authors [Chatzis and Dullien, 1977;Wilkinson and Willemsen, 1983] the coordination number will influence the network model behavior significantly, both in terms of breakthrough and relative permeability. In order to match the coordination number of a given rock sample, which typically is between 3 and 8 [Jerauld and Salter, 1990], it is possible to remove throats at random from a regular lattice [Dixit et al, 1997[Dixit et al, , 1999, hence reducing the connectivity. The pore and throat size distributions will also affect the estimated macroscopic properties.…”

Section: Introductionmentioning

confidence: 99%

Predictive pore‐scale modeling of two‐phase flow in mixed wet media

Valvatne

Blunt

2004

Water Resources Research

655

591

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[1] We show how to predict flow properties for a variety of porous media using pore-scale modeling with geologically realistic networks. Starting with a network representation of Berea sandstone, the pore size distribution is adjusted to match capillary pressure for different media, keeping the rank order of pore sizes and the network topology fixed. Then predictions of single and multiphase properties are made with no further adjustment of the model. We successfully predict relative permeability and oil recovery for water wet, oil wet, and mixed wet data sets. For water flooding we introduce a method for assigning contact angles to match measured wettability indices. The aim of this work is not simply to match experiments but to use easily acquired data to predict difficult to measure properties. Furthermore, the variation of these properties in the field, due to wettability trends and different pore structures, can now be predicted reliably.

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Section: Introductionmentioning

confidence: 99%

Predictive pore‐scale modeling of two‐phase flow in mixed wet media

Valvatne

Blunt

2004

Water Resources Research

655

591

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“…In this work, both computer-generated networks and real-shale networks using FIB/SEM will be used. For computer-generated networks, it is usually assumed that pore and throat sizes are spatially uncorrelated in the regular-topological networks, but previous studies have found that the size relationship between the adjacent pores and throats has certain effects on the permeability of the networks [24]. In order to guarantee the spatial correlation between pores and throats, a PNM based on the work of Blunt et al [25] in which large pores prefer to be connected with large throats is employed in this study.…”

Section: Gas Flow Model For Nanoporous Kerogenmentioning

confidence: 99%

A 3D coupled model of organic matter and inorganic matrix for calculating the permeability of shale

Cao

Lin

Jiang

et al. 2017

Fuel

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h i g h l i g h t sA new 3D model coupling organic kerogen and inorganic matrix was developed. The sensitivity analysis on the apparent permeability of shale matrix were operated. Ignoring the contribution of kerogen to the permeability of shale will bring great error in most cases. When the TOC is less than 11% and the pressure is greater than 0.1 Mpa, the effect of kerogen distribution is negligible. a r t i c l e i n f o t r a c tMicrostructure-based quantitative computation of the shale permeability is challenging due to the presence of organic matter with nanoporous features. In this study, a new three-dimensional (3D) coupled model is proposed to investigate the micro-scale permeability of organic-rich-shale matrix. The coupled model consists of two subdomains, organic matter and inorganic matrix. They are described by the pore network model (PNM) and continuum model to capture the non-Darcy and Darcy flow, respectively, and the gas flow in the two subdomains are coupled by finite element mortars (Mortar). The convergence error, grid discretization and parallel scheme are also investigated to get the optimal computing parameters for this model. Then, the effects of the total organic content (TOC), kerogen distribution and poresize distribution on the apparent permeability (AP) of shale matrix are studied using the coupled model with computer-generated PNMs. And on the basis of FIB-SEM images, a Longmaxi shale sample from the Sichuan Basin, China is introduced to build a real shale model. Results show that AP is more sensitive to TOC and pore-size distribution than kerogen distribution. Additionally, in order to analyze the necessity of 3D model, a comparison of 3D and two-dimensional (2D) model is made and the error of 2D model is pointed out. The 3D couple model affords a foundation for further upscaling of shale permeability to REV scale and reservoir scale.

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“…After this legendary work, pore-network models, mainly dominated by quasi-static pore-network models, were developed and applied to reservoir engineering and hydrogeology problems. The pore-network modelling opened up a new horizon in understanding the constitutive relations for two-phase flow such as capillary pressure and relative permeability curves [10,11], and at a later stage exploring the transport phenomena in porous media [12]. With further technological developments in micromodel and X-ray imaging facilities and computational infrastructures, quantitative pore-network models were further developed [13].…”

Section: Introductionmentioning

confidence: 99%

Pore-scale modelling techniques: balancing efficiency, performance, and robustness

Niasar

2016

Comput Geosci

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BackgroundPore-scale modelling is now a well-established progressive research field, which has significantly contributed to fundamental understanding of flow and transport in porous media in the last five decades. Examples can be (and not limited to) reservoir engineering [1][2][3][4], environmental hydrogeology [5], paper and pulp industry [6], fuel cells [7], biology, and medical science [8].The first pore-scale model was developed by Fatt in 1956 [9], who simulated the capillary pressure curve as a function of saturation using a pore-network model. After this legendary work, pore-network models, mainly dominated by quasi-static pore-network models, were developed and applied to reservoir engineering and hydrogeology problems. The pore-network modelling opened up a new horizon in understanding the constitutive relations for two-phase flow such as capillary pressure and relative permeability curves [10,11], and at a later stage exploring the transport phenomena in porous media [12]. With further technological developments in micromodel and X-ray imaging facilities and computational infrastructures, quantitative pore-network models were further developed [13]. Almost all pore-network models for different applications share the common principles: they require analytical or semianalytical solutions for a given specific research problem at the pore scale, meaning that the domain geometry requires to be well defined. That implies that the idealization of pore space to interconnected simplified geometries is inevitable.To alleviate this restriction of pore-network models, direct numerical modelling techniques are employed where the equations are solved numerically on the original pore space without any geometrical idealization. The most commonly used method is lattice Boltzmann (LB) modelling. However, there are several other methods such as smoothed particle hydrodynamics (SPH), level set (LS), volume of fluids (VoF), and density functional method (DFM), which can handle the numerical simulation within the exact geometry. Focus of this special issueThis special issue presents reviews of three major direct numerical methods, namely LB, SPH, and DFM, to simulate complex processes in porous media. Liu et al. [14] reviewed simulation of single-phase and multiphase multicomponent flow at pore level using the LB method. They reviewed different LB methods, discussed their advantages and disadvantages, and concluded that one method cannot be necessarily the most preferred one. In another review paper by Tartakovsky et al. [15], the SPH method as a Lagrangian method based on a meshless discretization of partial differential equations is discussed. They present the Navier-Stokes and advection-diffusion-reaction equations, implementation of various boundary conditions, and time integration of the SPH equations, and they discuss applications of the SPH method for modelling porescale multiphase flows and reactive transport in porous and fractured media. In another review paper by Dinariev and Evseev [16], applications of densit...

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The effect of pore-structure on hysteresis in relative permeability and capillary pressure: Pore-level modeling

Cited by 390 publications

References 83 publications

Predictive pore‐scale modeling of two‐phase flow in mixed wet media

Predictive pore‐scale modeling of two‐phase flow in mixed wet media

A 3D coupled model of organic matter and inorganic matrix for calculating the permeability of shale

Pore-scale modelling techniques: balancing efficiency, performance, and robustness

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