Scale up of pore-scale transport properties from micro to macro scale; network modelling approach

Bashtani, Farzad; Taheri, Saeed; Kantzas, Apostolos

doi:10.1016/j.petrol.2018.07.001

Cited by 20 publications

(25 citation statements)

References 40 publications

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“…At a low fluid velocity of a given two‐phase system, inertial force is negligible relative to the viscous force (Kundu et al, ). When the system approaches a quasi‐static state, the capillary forces dominates viscous forces (Bashtani et al, ; Fagbemi et al, ; Wildenschild et al, ). Therefore, between t 2 and t 3 with a low fluid velocity in a porous medium, capillary pressure and surface tension dominate, while inertial and viscous forces are negligible.…”

Section: Resultsmentioning

confidence: 99%

Factors Influencing Dynamic Nonequilibrium Effects in Drainage Processes of an Air‐Water Two‐Phase Fine Sandy Medium

Li¹,

He²,

et al. 2019

Water Resources Research

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In efforts to reduce uncertainties about effects of minor changes in the pore structure of porous media on dynamic nonequilibrium effects (DNEs), we monitored water saturation‐capillary pressure relationships in both dynamic flow and static states in stepwise drainage processes of a sandy medium. The acquired data were used to detect DNE and their changes with time in each drainage step and construct new parameters to characterize DNE. Effects of factors affecting water flow—including capillary number, water saturation, rate of change of water saturation with time (△Sw/△t), and the maximum value of this rate (RSMAX)—on the magnitude of the DNE were then determined. Results show that entry pressures are considerably larger under dynamic flow conditions than under static flow conditions, and DNE only occurs when the water saturation exceeds a threshold value in a drainage process. During either a smooth drainage or drainage step, the maximum capillary pressure (PMAX) is reached before the minimum water saturation (SMIN). Moreover, in drainage steps RSMAX occurs before the maximum difference between the capillary pressures associated with the static and dynamic states (DPMAX), except when they start from the saturated state. Accordingly, DNEs in a drainage step are mainly reflected in the time between PMAX and SMIN (△t), DPMAX, the average sum of the squares of the difference between capillary pressures of the static and dynamic states (DPAVE), and the dynamic coefficient τ (which is often used to characterize DNE). Furthermore, our results indicate that the water saturation and its rate of change with time are more important parameters than the capillary number for modeling DNE in a drainage process, and we detected no clear correlation between either maximum or minimum values of τ and the timing of the most significant DNE during drainages. τ appears to characterize DNE effectively in smooth drainage processes, while △t, DPAVE, and DPMAX constitute meaningful supplementary parameters for the characterization of DNE in a drainage step of a stepwise drainage.

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Section: Resultsmentioning

confidence: 99%

Factors Influencing Dynamic Nonequilibrium Effects in Drainage Processes of an Air‐Water Two‐Phase Fine Sandy Medium

Li¹,

He²,

et al. 2019

Water Resources Research

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“…Two primary pore-scale simulation methods are typically used: pore network modeling and lattice Boltzman simulations (Lichtner & Kang, 2007). Pore network modeling, originally developed by Fatt (1956), has emerged as a valuable tool to simulate upscaled mineral reaction rates (e.g., Li et al, 2006;Varloteaux et al, 2013) and porosity-permeability evolution in heterogeneous porous media (e.g., Bashtani et al, 2018;Beckingham, 2017;Nogues et al, 2013). In these models, multidirectional pore networks are discretized on a regular or irregular cubic lattice of nodes (pores) and connections (pore throats).…”

Section: Introductionmentioning

confidence: 99%

Role of Pore and Pore‐Throat Distributions in Controlling Permeability in Heterogeneous Mineral Dissolution and Precipitation Scenarios

Steinwinder

Beckingham

2019

Water Resources Research

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Mineral dissolution and precipitation reactions can significantly alter the porosity and permeability of porous media. While porosity generally increases with dissolution and decreases with precipitation, permeability is controlled by the spatial locations of reactions in discrete pores and pore throats and in the greater pore network. Geochemical reactions have been observed to occur both uniformly and nonuniformly in porous media, driven by parameters such as mineral distribution, grain size, and Peclet and Damkohler numbers. Pore network modeling can be used to simulate the impact of pore‐scale alterations on permeability, requiring only pore and pore‐throat size distributions and pore connectivity. Here, the impact of variations in pore and pore‐throat size distributions on reactive permeability for uniform and nonuniform spatial distributions of reactions is evaluated. A series of pore network models are created and populated with pore and pore‐throat size distributions of varying types (skewed, normal, and uniform) to represent differences in network topology and characterization methods. The impacts of these distributions on reactive permeability are then simulated for uniform and nonuniform reaction conditions by increasing or decreasing pore and pore‐throat sizes in a prescribed manner to reflect dissolution and precipitation, respectively. Overall, simulations reveal that porosity‐permeability evolution varies with reaction scenario and is qualitatively consistent for the different pore and pore‐throat size distributions. Common macroscopic porosity‐permeability relationships work well for some reaction scenarios but are unable to reflect size‐dependent reactions. A new modified version of the Verma‐Pruess relationship is created and able to successfully reflect the porosity‐permeability evolution for size‐dependent reactions.

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“…Then, sub‐segments were distributed in space to reconstruct the main blocks and various scale‐up and averaging methods were employed/developed to obtain porosity, permeability, and capillary pressure curves of the reconstructed blocks. Results were then compared to the ones obtained directly from the network models of the main block and good agreement was observed …”

Section: Introductionmentioning

confidence: 90%

“…Multiphase flow properties, such as capillary pressure, relative permeability, and resistivity index curves of both primary drainage and secondary imbibition of the main blocks are shown in Figures , and , respectively. This information was also calculated for the sub‐segments and it can be found in our previous study …”

Section: Fluid Flow Propertiesmentioning

confidence: 99%

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Scale‐up of pore‐level relative permeability from micro‐ to macro‐scale

Bashtani

Kantzas

2020

Can J Chem Eng

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Scaling up relative permeability curves of wetting and nonwetting phase of drainage and imbibition processes from pore scale to macro scale is a challenge. A new method for scaling up relative permeability from micro‐ to macro‐scale is proposed based on electrical analogy of multiphase fluid flow at pore scale. The method is validated against four synthetic porous media generated using homogeneous and heterogeneous grain size distributions, each of which were cut into eight sub‐segments. Single‐phase and two‐phase flow properties were calculated for the main blocks and the subsequent sub‐segments using random network modelling technique. Then, the subsegments were randomly distributed in space to reconstruct the main blocks and the proposed scale‐up method was employed to calculate the relative permeability curves of the reconstructed blocks. Results were compared to the ones obtained directly from the network model of the original blocks and show good agreement between the calculated and scaled‐up relative permeability curves of primary drainage and secondary imbibition. Furthermore, the model was tested on real media. Eight network models were extracted from pore size distribution of core samples obtained from the Green River basin located in the Mesaverde Formation. Flow properties obtained from the network models were validated against experimental data and good agreement was observed. These network models show a higher level of heterogeneity at micro‐scale. Then, the scale‐up methods were employed in order to reconstruct the macro‐scale sample and predict its properties. Scale‐up methods successfully predict the single‐phase and two‐phase flow properties of the sample.

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Scale up of pore-scale transport properties from micro to macro scale; network modelling approach

Cited by 20 publications

References 40 publications

Factors Influencing Dynamic Nonequilibrium Effects in Drainage Processes of an Air‐Water Two‐Phase Fine Sandy Medium

Factors Influencing Dynamic Nonequilibrium Effects in Drainage Processes of an Air‐Water Two‐Phase Fine Sandy Medium

Role of Pore and Pore‐Throat Distributions in Controlling Permeability in Heterogeneous Mineral Dissolution and Precipitation Scenarios

Scale‐up of pore‐level relative permeability from micro‐ to macro‐scale

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