Pores integrated fractal (PIF) analysis on transportation in porous media considering spatial distribution of pores and genuine tortuosity

2022 ◽  
Vol 187 ◽  
pp. 122528
Author(s):  
Xiang Yang ◽  
Yanping Du ◽  
Qian Xu ◽  
Feitong Wu ◽  
Tao Zhou ◽  
...  
Keyword(s):  
Porous Media ◽  
Spatial Distribution

scholarly journals A Parallel Stochastic Framework for Reservoir Characterization and History Matching

2011 ◽  
Vol 2011 ◽  
pp. 1-19 ◽  
Author(s):  
Sunil G. Thomas ◽  
Hector M. Klie ◽  
Adolfo A. Rodriguez ◽  
Mary F. Wheeler
Keyword(s):  
Porous Media ◽  
Spatial Distribution ◽  
Multiphase Flow ◽  
History Matching ◽  
Reservoir Characterization ◽  
Well Log ◽  
Species Transport ◽  
Medium Permeability ◽  
Stochastic Framework ◽  
Sensor Information

The spatial distribution of parameters that characterize the subsurface is never known to any reasonable level of accuracy required to solve the governing PDEs of multiphase flow or species transport through porous media. This paper presents a numerically cheap, yet efficient, accurate and parallel framework to estimate reservoir parameters, for example, medium permeability, using sensor information from measurements of the solution variables such as phase pressures, phase concentrations, fluxes, and seismic and well log data. Numerical results are presented to demonstrate the method.

CHARACTERIZATION OF POROUS MEDIA WITH GEOMETRICAL MULTIFRACTALS

Fractals ◽  
1993 ◽  
Vol 01 (04) ◽  
pp. 894-903 ◽  
Author(s):  
ANTOINE SAUCIER ◽  
JIRI MULLER
Keyword(s):  
Porous Medium ◽  
Porous Media ◽  
Spatial Distribution ◽  
Multifractal Spectrum ◽  
Spatial Variations ◽  
Local Porosity

In a porous medium the local porosity often exhibits spatial variations. These variations can be characterized by a multifractal spectrum, as long as suitable scaling characteristics are present. We derive some of the properties of such geometrical multifractals, and discuss how the spatial distribution of a set is related to its multifractal spectrum.

scholarly journals Simulation of the Spatial Distribution of Hydraulic Conductivity in Porous Media through Different Methods

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Zengguang Xu ◽  
Xue Wang ◽  
Junrui Chai ◽  
Yuan Qin ◽  
Yanlong Li
Keyword(s):  
Grain Size ◽  
Porous Media ◽  
Spatial Distribution ◽  
Hydraulic Conductivity ◽  
Pumping Test ◽  
Wide Area ◽  
Test Results ◽  
Seepage Field ◽  
Water Conservancy ◽  
Geological Research

Seepage problems exist in water conservancy projects, groundwater research, and geological research, and hydraulic conductivity is an important factor that affects the seepage field. This study investigates the heterogeneity of hydraulic conductivity. Kriging methods are used to simulate the spatial distribution of hydraulic conductivity, and the application of resistivity and grain size is used to obtain hydraulic conductivity. The results agree with the experimental pumping test results, which prove that the distribution of hydraulic conductivity can be obtained economically and efficiently and in a complex and wide area.

scholarly journals Localization in Flow of Non-Newtonian Fluids Through Disordered Porous Media

2021 ◽  
Vol 9 ◽  
Author(s):  
H. J. Seybold ◽  
U. Eberhard ◽  
E. Secchi ◽  
R. L. C. Cisne ◽  
J. Jiménez-Martínez ◽  
...  
Keyword(s):  
Porous Media ◽  
Spatial Distribution ◽  
Pore Space ◽  
Pore Geometry ◽  
Flow Conditions ◽  
Flow Localization ◽  
Chemical Reactors ◽  
Nonlinear Rheology ◽  
Constitutive Properties ◽  
Disordered Porous Media

We combine results of high-resolution microfluidic experiments with extensive numerical simulations to show how the flow patterns inside a “swiss-cheese” type of pore geometry can be systematically controlled through the intrinsic rheological properties of the fluid. Precisely, our analysis reveals that the velocity field in the interstitial pore space tends to display enhanced channeling under certain flow conditions. This observed flow “localization”, quantified by the spatial distribution of kinetic energy, can then be explained in terms of the strong interplay between the disordered geometry of the pore space and the nonlinear rheology of the fluid. Our results disclose the possibility that the constitutive properties of the fluid can enhance the performance of chemical reactors and chromatographic devices through control of the channeling patterns inside disordered porous media.

Fluorescence macrophotography as a tool to visualise and quantify spatial distribution of deposited colloid tracers in porous media

2007 ◽  
Vol 306 (1-3) ◽  
pp. 118-125 ◽  
Author(s):  
Peter Klauth ◽  
Reimar Bauer ◽  
Carla Ralfs ◽  
Petr Ustohal ◽  
Jan Vanderborght ◽  
...  
Keyword(s):  
Porous Media ◽  
Spatial Distribution

Spatial-distribution dynamics of moisture, temperature, and dielectric characteristics in capillary-porous media

1994 ◽  
Vol 37 (11) ◽  
pp. 1018-1023
Author(s):  
V. V. Zagoskin ◽  
S. G. Kataev ◽  
G. I. Tyul'kov ◽  
V. N. Chernyshov
Keyword(s):  
Porous Media ◽  
Spatial Distribution ◽  
Distribution Dynamics ◽  
Dielectric Characteristics

scholarly journals Flow Path Resistance in Heterogeneous Porous Media Recast into a Graph-Theory Problem

2021 ◽  
Author(s):  
Z. Kanavas ◽  
F. J. Pérez-Reche ◽  
F. Arns ◽  
V. L. Morales
Keyword(s):  
Porous Media ◽  
Spatial Distribution ◽  
Preferential Flow ◽  
Pore Network ◽  
Heterogeneous Porous Media ◽  
Direct Numerical Simulations ◽  
Structural Constraints ◽  
Flow Paths ◽  
Minimum Resistance ◽  
Stagnant Flow

Abstract This work aims to describe the spatial distribution of flow from characteristics of the underlying pore structure in heterogeneous porous media. Thousands of two-dimensional samples of polydispersed granular media are used to (1) obtain the velocity field via direct numerical simulations, and (2) conceptualize the pore network as a graph in each sample. Analysis of the flow field allows us to distinguish preferential from stagnant flow regions and to quantify how channelized the flow is. Then, the graph’s edges are weighted by geometric attributes of their corresponding pores to find the path of minimum resistance of each sample. Overlap between the preferential flow paths and the predicted minimum resistance path determines the accuracy in individual samples. An evolutionary algorithm is employed to determine the “fittest” weighting scheme (here, the channel’s arc length to pore throat ratio) that maximizes accuracy across the entire dataset while minimizing over-parameterization. Finally, the structural similarity of neighboring edges is analyzed to explain the spatial arrangement of preferential flow within the pore network. We find that connected edges within the preferential flow subnetwork are highly similar, while those within the stagnant flow subnetwork are dissimilar. The contrast in similarity between these regions increases with flow channelization, explaining the structural constraints to local flow. The proposed framework may be used for fast characterization of porous media heterogeneity relative to computationally expensive direct numerical simulations. Article Highlights A quantitative assessment of flow channeling is proposed that distinguishes pore-scale flow fields into preferential and stagnant flow regions. Geometry and topology of the pore network are used to predict the spatial distribution of fast flow paths from structural data alone. Local disorder of pore networks provides structural constraints for flow separation into preferential v stagnant regions and informs on their velocity contrast.

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