Apparent gas permeability in an organic-rich shale reservoir

Song, Wenhui; Ye, Jun; Li, Yang; Sun, Hai; Zhang, Lei; Yang, Yongfei; Zhao, Jianlin; Sui, Hongguang

doi:10.1016/j.fuel.2016.05.011

Cited by 226 publications

(110 citation statements)

References 43 publications

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“…Accurate simulation models of gas transport in SG reservoirs must consider complex gas transport mechanisms and phase behavior in nanopores, as well as different pore types. The gas transport mechanisms in SG reservoirs include viscous flow, Knudsen diffusion, surface diffusion, adsorption and desorption [63]. Recent studies have shown that adsorbed gas and its surface diffusion have profound influence on micro gaseous flow through organic pores in SG reservoirs [56].…”

Section: Research Hotspot Analysis During 2013-2014mentioning

confidence: 99%

An Investigation of the Underlying Evolution of Shale Gas Research’s Domain Based on the Co-Word Network

Li¹,

Liu²,

Siqi³

et al. 2018

Sustainability

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Abstract:With the increasing shortage energy, the exploration and utilization of shale gas (SG) have greatly changed the world's natural gas supply pattern. In this study, based on a bibliometric review of the publications related to SG, by analyzing the co-word networks during the past years, we provide comprehensive analyses on the underlying domain evolution of shale gas research (SGR). Firstly, we visualize the topical development of SGR. We not only identify the key topics at each stage but also reveal their underlying dependence and evolutionary trends. The directions of SGR in the future are implied. Secondly, we find the co-word network has small-world and scale-free characteristics, which are the important mechanisms of driving the evolution of SGR's domain. Thirdly, we analyze China's SGR. We find the co-word network in China's SGR has not yet emerged obvious differentiation. Nevertheless, it has a similar self-organized evolution process with the co-word network of international SGR. Our above results can provide references for the future SGR of scholars, optimization or control of the domain and the strategy/policy of countries or globalization.

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Section: Research Hotspot Analysis During 2013-2014mentioning

confidence: 99%

An Investigation of the Underlying Evolution of Shale Gas Research’s Domain Based on the Co-Word Network

Li¹,

Liu²,

Siqi³

et al. 2018

Sustainability

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“…In order to investigate the effect of TOC on AP, in this section, six cases with different TOC (3.08%, 4.62%, 6.15%, 7.69%, 9.24%, 10.78%) are constructed with the corresponding kerogen block numbers of 10,15,20,25,30,35. For the K iom of 500nD and the pressure boundary condition of 0.2 ± 0.1 MPa, the contour plots of pressure for the six cases are shown in Fig.…”

Section: Effects Of the Total Organic Content (Toc)mentioning

confidence: 99%

“…have noticed the big differences between kerogen and inorganic matrix in shale and treat them separately [10][11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

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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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“…These equations can provide very useful insights, but their accuracy is limited to the experimental conditions used for their derivation. [32][33][34] Lattice Boltzmann (LB) simulations can be applied to obtain transport properties. LB is a mesoscopic approach used to simulate fluid transport, under the assumption of continuum flow.…”

Section: Introductionmentioning

confidence: 99%

A kinetic Monte Carlo approach to study fluid transport in pore networks

Apostolopoulou

Day

Hull

et al. 2017

The Journal of Chemical Physics

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The mechanism of fluid migration in porous networks continues to attract great interest. Darcy's law (phenomenological continuum theory), which is often used to describe macroscopically fluid flow through a porous material, is thought to fail in nano-channels. Transport through heterogeneous and anisotropic systems, characterized by a broad distribution of pores, occurs via a contribution of different transport mechanisms, all of which need to be accounted for. The situation is likely more complicated when immiscible fluid mixtures are present. To generalize the study of fluid transport through a porous network, we developed a stochastic kinetic Monte Carlo (KMC) model. In our lattice model, the pore network is represented as a set of connected finite volumes (voxels), and transport is simulated as a random walk of molecules, which "hop" from voxel to voxel. We simulated fluid transport along an effectively 1D pore and we compared the results to those expected by solving analytically the diffusion equation. The KMC model was then implemented to quantify the transport of methane through hydrated micropores, in which case atomistic molecular dynamic simulation results were reproduced. The model was then used to study flow through pore networks, where it was able to quantify the effect of the pore length and the effect of the network's connectivity. The results are consistent with experiments but also provide additional physical insights. Extension of the model will be useful to better understand fluid transport in shale rocks.

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Apparent gas permeability in an organic-rich shale reservoir

Cited by 226 publications

References 43 publications

An Investigation of the Underlying Evolution of Shale Gas Research’s Domain Based on the Co-Word Network

An Investigation of the Underlying Evolution of Shale Gas Research’s Domain Based on the Co-Word Network

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

A kinetic Monte Carlo approach to study fluid transport in pore networks

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