Study of the permeability characteristics of porous media with methane hydrate by pore network model

The permeability in the methane hydrate reservoir is one of the key parameters in estimating the gas production performance and the flow behavior of gas and water during dissociation.In this paper,a three-dimensional cubic pore-network model based on invasion percolation is developed to study the effect of hydrate particle formation and growth habit on the permeability.The variation of permeability in porous media with different hydrate saturation is studied by solving the network problem.The simulation results are well consistent with the experimental data.The proposed model predicts that the permeability will reduce exponentially with the increase of hydrate saturation,which is crucial in developing a deeper understanding of the mechanism of hydrate formation and dissociation in porous media.

Determination of a Pore Structure Parameter of Porous Media by Analysis of Percolation Network Model

According to the simulation of nitrogen sorption process in porous media with three-dimensional network model, and the analysis for such a process with percolation theory, a new method is proposed to determine a pore structure parameter--mean coordination number of pore network, which represents the connectivity among a great number of pores. Here the 'chamber-throat' model and the Weibull distribution are used to describe the pore geometry and the pore size distribution respectively. This method is based on the scaling law of percolation theory after both effects of sorption thermodynamics and pore size on the sorption hysteresis loops are considered. The results show that it is an effective procedure to calculate the mean coordination number for micro- and meso-porous media.

Anisotropic dynamic permeability model for porous media

Based on the tortuous capillary network model,the relationship between anisotropic permeability and rock normal strain,namely the anisotropic dynamic permeability model(ADPM),was derived and established.The model was verified using pore-scale flow simulation.The uniaxial strain process was calculated and the main factors affecting permeability changes in different directions in the deformation process were analyzed.In the process of uniaxial strain during the exploitation of layered oil and gas reservoirs,the effect of effective surface porosity on the permeability in all directions is consistent.With the decrease of effective surface porosity,the sensitivity of permeability to strain increases.The sensitivity of the permeability perpendicular to the direction of compression to the strain decreases with the increase of the tortuosity,while the sensitivity of the permeability in the direction of compression to the strain increases with the increase of the tortuosity.For layered reservoirs with the same initial tortuosity in all directions,the tortuosity plays a decisive role in the relative relationship between the variations of permeability in all directions during pressure drop.When the tortuosity is less than 1.6,the decrease rate of horizontal permeability is higher than that of vertical permeability,while the opposite is true when the tortuosity is greater than 1.6.This phenomenon cannot be represented by traditional dynamic permeability model.After the verification by experimental data of pore-scale simulation,the new model has high fitting accuracy and can effectively characterize the effects of deformation in different directions on the permeability in all directions.

The impact of heterogeneity and pore network characteristics on single and multi-phase fluid propagation in complex porous media:An X-ray computed tomography study

This study investigates the impact of pore network characteristics on fluid flow through complex and heterogeneous porous media,providing insights into the factors affecting fluid propagation in such systems.Specifically,high-resolution or micro X-ray computed tomography(CT)imaging techniques were utilized to examine outcrop stromatolite samples of the Lagoa Salgada,considered flow analogous to the Brazilian Pre-salt carbonate reservoirs.The petrophysical results comprised two distinct stromatolite depositional facies,the columnar and the fine-grained facies.By generating pore network model(PNM),the study quantified the relationship between key features of the porous system,including pore and throat radius,throat length,coordination number,shape factor,and pore volume.The study found that the less dense pore network of the columnar sample is typically characterized by larger pores and wider and longer throats but with a weaker connection of throats to pores.Both facies exhibited less variability in the radius of the pores and throats in comparison to throat length.Additionally,a series of core flooding experiments coupled with medical CT scanning was designed and conducted in the plug samples to assess flow propagation and saturation fields.The study revealed that the heterogeneity and presence of disconnected or dead-end pores significantly impacted the flow patterns and saturation.Two-phase flow patterns and oil saturation distribution reveal a preferential and heterogeneous displacement that mainly swept displaced fluid in some regions of plugs and bypassed it in others.The relation between saturation profiles,porosity profiles,and the number of fluid flow patterns for the samples was evident.Only for the columnar plug sample was the enhancement in recovery factor after shifting to lower salinity water injection(SB)observed.

Modeling of multiphase flow in low permeability porous media:Effect of wettability and pore structure properties

Multiphase flow in low permeability porous media is involved in numerous energy and environmental applications.However,a complete description of this process is challenging due to the limited modeling scale and the effects of complex pore structures and wettability.To address this issue,based on the digital rock of low permeability sandstone,a direct numerical simulation is performed considering the interphase drag and boundary slip to clarify the microscopic water-oil displacement process.In addition,a dual-porosity pore network model(PNM)is constructed to obtain the water-oil relative permeability of the sample.The displacement efficiency as a recovery process is assessed under different wetting and pore structure properties.Results show that microscopic displacement mechanisms explain the corresponding macroscopic relative permeability.The injected water breaks through the outlet earlier with a large mass flow,while thick oil films exist in rough hydrophobic surfaces and poorly connected pores.The variation of water-oil relative permeability is significant,and residual oil saturation is high in the oil-wet system.The flooding is extensive,and the residual oil is trapped in complex pore networks for hydrophilic pore surfaces;thus,water relative permeability is lower in the water-wet system.While the displacement efficiency is the worst in mixed-wetting systems for poor water connectivity.Microporosity negatively correlates with invading oil volume fraction due to strong capillary resistance,and a large microporosity corresponds to low residual oil saturation.This work provides insights into the water-oil flow from different modeling perspectives and helps to optimize the development plan for enhanced recovery.

Review of permeability evolution model for fractured porous media

The ability to capture permeability of fractured porous media plays a significant role in several engineering applications, including reservoir, mining, petroleum and geotechnical engineering. In order to solve fluid flow and coupled flow-deformation problems encountered in these engineering applications,both empirical and theoretical models had been proposed in the past few decades. Some of them are simple but still work in certain circumstances; others are complex but also need some modifications to be applicable. Thus, the understanding of state-of-the-art permeability evolution model would help researchers and engineers solve engineering problems through an appropriate approach. This paper summarizes permeability evolution models proposed by earlier and recent researchers with emphasis on their characteristics and limitations.

Determining the impact of rectangular grain aspect ratio on tortuosity–porosity correlations of two-dimensional stochastically generated porous media

Tortuosity is an important parameter for char- acterizing transport properties within porous materials and is of interest in a broad range of fields, such as energy storage and conversion materials. One of the parameters that impacts the tortuosity value is the geometry of the solid phase which, in this study, is considered as stochas- tically-placed rectangular particles. Through lattice Boltz- mann modelling （LBM）, we determined the impact of particle aspect ratio on the intrinsic tortuosity-porosity relationships of two-dimensional porous media composed of rectangular particles. These relationships were isolated for materials with grain （particle） aspect ratios of e { 1, 2, 3 } and porosities from [0.55 - 0.95]. We determined that a minimum of 6, 8 and 10 stochastic simulations, respec- tively, were required to calculate these average tortuosity values in laminar flow （Re 〈〈 1）. This novel application of the LBM to study the effects of porosity and aspect ratio of rectangular grains on tortuosity can be used in the tailoring of materials for clean energy.

Prediction of effective diffusivity of porous media using deep learning method based on sample structure information self-amplification

Effective diffusivity is one of the basic transport coefficients used to describe the mass transport capability of a porous medium.In this study,a deep learning method based on a convolutional neural network(CNN)with sam-ple structure information self-amplification is proposed to predict the effective diffusivity of a porous medium,which is considerably influenced by the morphological and topological parameters of the porous medium.In this method,the geometric structures of three-dimensional(3D)porous media are reproduced via a stochastic reconstruction method.Datasets of the effective diffusivities of the reconstructed porous media were first estab-lished by the pore-scale lattice Boltzmann method(LBM)simulation.A large number of geometric structures of 3D porous media are obtained using the proposed sample structure information self-amplification approach.The 3D geometric structure information and corresponding effective diffusivities are directionally applied to a CNN for training and prediction.The effective diffusivities of media with porosities ranging from 0.48 to 0.58 are employed as training datasets,and the effective diffusivities of media with a broader porosity range of 0.39 to 0.79 are predicted by CNN.The CNN model can achieve a fast and accurate prediction of the effective diffusivity.The relative error between the CNN and LBM is 0.026%–8.95%with porosities ranging from 0.39 to 0.79.For a typical case with a porosity of 0.5,the computation time required by the CNN model is only 3×10^(−4) h,while the computation time for the same case is 16.96 h using the LBM.These findings indicate that the proposed deep learning method has a powerful learning ability;it is time-saving,provides accurate predic-tions,and can serve as a promising and powerful tool to predict the transport coefficients of complex porous media.

多孔介质各向异性动态渗透率模型

基于迂曲毛细管网络模型,推导建立了各向异性渗透率与岩石正应变间的关系式,即各向异性动态渗透率模型(ADPM),采用孔隙尺度流动模拟对模型进行了验证,并对单轴应变过程进行了计算,分析了变形过程中影响不同方向渗透率变化的主要因素。研究表明:层状油气藏开采的单轴应变过程中,有效面孔率对各方向的渗透率影响规律一致,随着有效面孔率的减小,渗透率对应变的敏感程度增大;垂直于压缩方向的渗透率对应变的敏感程度随迂曲度的增加而减小,沿压缩方向的渗透率对应变的敏感程度随迂曲度的增加而增大。初始各方向迂曲度相同的层状油气藏,在压力下降的过程中,迂曲度对各方向渗透率变化幅度的相对关系起决定性作用,迂曲度小于1.6时,岩石水平方向渗透率的降幅要高于垂向渗透率,迂曲度大于1.6时则相反,传统动态渗透率模型无法表征这一现象。经孔隙尺度模拟实验数据的验证,新模型拟合精度高,可以有效表征不同方向变形对各方向渗透率的影响。

曲折因子与多孔介质微观结构的定性关系

采用三维网络模型对多孔介质中的两组分气体扩散过程进行了计算机模拟 .在考虑了多孔介质微观结构的前提下 ,分析了外界因素和多孔介质结构对曲折因子的影响 .结果表明 ,曲折因子仅与多孔介质的孔道连通性———网络配位数密切相关 ,而与孔道的几何尺寸、扩散温度、扩散物种及浓度无关 .经过Wicke -Kallenbach定态扩散实验验证了这一定性结论的可靠性 .

新型媒介背景下的信息扩散方式对资产定价的影响研究

随着Web2.0背景下新型媒介的蓬勃发展和信息扩散方式的变革,新型信息传播媒介逐渐深入影响投资者的投资行为。以网络开源信息模型为基础,采用微信指数指标体系建立复杂网络扩散模型,研究Web2.0背景下新型媒介信息传播对资产定价的影响问题。结果表明:Web2.0背景下,微信指数确实会影响资产定价,但微信指数并不包含影响股票收益率的全部信息。同时,相比于网络开源模型,复杂网络扩散模型对于成交量中额外信息的发现能力更强。

Multi-Scale Modeling and Numerical Simulation for CVI Process

We consider the multi-scale modeling of the isothermal chemical vapor infiltration (CVI) process for the fabrication of C/SiC composites. We first present a microscopic model in which the preform is regarded as a two-phase porous media describedby a dynamic pore-scale node-bond network during the fabrication process. We thendevelop a macroscopic model by a upscaling procedure based on the homogenizationtheory.

基于等效孔隙网络模型的水动力弥散数值模拟

等效孔隙网络模型基于统计参数描述多孔介质中复杂的孔隙结构,常用于分析多孔介质中渗流和机械弥散等物质运移过程的微观机理,但对溶质运移过程中分子扩散作用的研究相对较少。该文基于等效孔隙网络模型研究了多孔介质中溶质的对流、分子扩散和机械弥散过程,对多孔介质中溶质的运移规律进行研究。通过对等效孔隙网络模型参数进行敏感性分析,研究了多孔介质孔隙结构特征对有效扩散系数的影响;通过对比仅考虑机械弥散与同时考虑分子扩散和机械弥散的计算结果,讨论了分子扩散对于水动力弥散过程的影响。计算结果表明:有效扩散系数受到孔隙体积与孔喉扩散能力的共同影响,与孔喉曲率负相关,与配位数和连接数比值正相关;分子扩散作用与对流导致的机械弥散过程有耦合作用,分子扩散作用加速了溶质在低流速区域的运移。该文揭示了分子扩散作用影响水动力弥散过程的微观机理,为孔隙网络模型中的溶质运移通量计算提供了理论依据。