Pore-scale modeling of reactive transport in wellbore cement under CO2 storage conditions

Raoof, Amir; Nick, Hamidreza M.; Wolterbeek, T.K.T.; Spiers, Christopher J.

doi:10.1016/j.ijggc.2012.09.012

Cited by 103 publications

(77 citation statements)

References 73 publications

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“…Pore scale modeling is attracting an increasing attention in the oil and gas industry during the last decades, and has potential applications in contaminant transport and carbon dioxide storage (Blunt, 2001;Bandara et al, 2011;Mostaghimi et al, 2012;Raeini et al, 2012;Raoof et al, 2012;Blunt et al, 2013). In addition to predicting fundamental flow parameters (e.g., capillary pressure and relative permeability) (Kovscek et al, 1993;Øren et al, 1998;van Dijke & Sorbie, 2002a;Silin & Patzek, 2006;Helland & Skjaeveland, 2006a;Mousavi et al, 2013), pore scale modeling is also capable of investigating the effects of micro-scale phenomena on the macro-scale behaviors, and thus it provides a physically-based approach to upscale multiphase flow in porous media from micro-scale to macroscale (Middleton et al, 2012;Mehmani et al, 2012;Al-Dhahli et al, 2013;Porta et al, 2013).…”

Section: Pore Scale Modelingmentioning

confidence: 99%

Dynamic Capillary Pressure Curves From Pore-Scale Modeling in Mixed-Wet-Rock Images

2013

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Summary In reservoir multiphase-flow processes with high flow rates, both viscous and capillary forces determine the pore-scale fluid configurations, and significant dynamic effects could appear in the capillary pressure/saturation relation. We simulate dynamic and quasistatic capillary pressure curves for drainage and imbibition directly in scanning-electron-microscope (SEM) images of Bentheim sandstone at mixed-wet conditions by treating the identified pore spaces as tube cross sections. The phase pressures vary with length positions along the tube length but remain unique in each cross section, which leads to a nonlinear system of equations that are solved for interface positions as a function of time. The cross-sectional fluid configurations are computed accurately at any capillary pressure and wetting condition by combining free-energy minimization with a menisci-determining procedure that identifies the intersections of two circles moving in opposite directions along the pore boundary. Circle rotation at pinned contact lines accounts for mixed-wet conditions. Dynamic capillary pressure is calculated with volume-averaged phase pressures, and dynamic capillary coefficients are obtained by computing the time derivative of saturation and the difference between the dynamic and static capillary pressure. Consistent with previously reported measurements, our results demonstrate that, for a given water saturation, simulated dynamic capillary pressure curves are at a higher capillary level than the static capillary pressure during drainage, but at a lower level during imbibition, regardless of the wetting state of the porous medium. The difference between dynamic and static capillary pressure becomes larger as the pressure step applied in the simulations is increased. The model predicts that the dynamic capillary coefficient is a function of saturation and is independent of the incremental pressure step, which is consistent with results reported in previous studies. The dynamic capillary coefficient increases with decreasing water saturation at water-wet conditions, whereas, for mixed- to oil-wet conditions, it increases with increasing water saturation. The imbibition simulations performed at mixed- to oil-wet conditions also indicate that the dynamic capillary coefficient increases with decreasing initial water saturation. The proposed modeling procedure provides insights into the extent of dynamic effects in capillary pressure curves for realistic mixed-wet pore spaces, which could contribute to the improved interpretation of core-scale experiments. The simulated capillary pressure curves obtained with the pore-scale model could also be applied in reservoir-simulation models to assess dynamic pore-scale effects on the Darcy scale.

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Section: Pore Scale Modelingmentioning

confidence: 99%

Dynamic Capillary Pressure Curves From Pore-Scale Modeling in Mixed-Wet-Rock Images

2013

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“…PN models have been extensively used in modeling flow and transport in porous media (Blunt 2001;Budek and Szymczak 2012;Li et al 2006;Raoof et al 2012). There are also many studies of bioclogging using PN models.…”

Section: Introductionmentioning

confidence: 99%

Pore-Network Modeling of Solute Transport and Biofilm Growth in Porous Media

Qin

Hassanizadeh

2015

Transp Porous Med

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In this work, a pore-network (PN) model for solute transport and biofilm growth in porous media was developed. Compared to previous studies of biofilm growth, it has two new features. First, the constructed pore network gives a better representation of a porous medium. Second, instead of using a constant mass exchange coefficient for solute transport between water phase and biofilm, a variable coefficient as a function of biofilm volume fraction and Damköhler number was employed. This PN model was verified against direction simulations. Then, a number of case studies were conducted, in order to illustrate the temporal evolutions of medium permeability and biomass content under different operating conditions. Finally, we explored the effects of biofilm morphology and permeability on biofilm growth, as well as non-unique relationship between medium permeability reduction and its porosity change.

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“…Simulation of variably-saturated flow and (multi-component) reactive trans-16 port is highly important in many applications involving both natural (soils, 17 rocks, woods, hard and soft tissues, etc.) and industrial (concrete, bioengi- S w , ii) the relative permeability, k r , as a function of either the saturation 9 or capillary pressure, and iii) the relationship between solute dispersivity or 10 effective diffusion and saturation in solute transport processes.…”

Section: Introductionmentioning

confidence: 99%

“…For each pore, change in solute mass is described by mass bal- 15 ance equations (Lichtner, 1985). Using information on local surface area, and 16 applying an area-normalized reaction rate, a kinetic reaction is calculated for 17 each pore (Raoof and Hassanizadeh, 2010). 18 One shortcoming of a pore-network model is its idealization of the pore 19 space using simple geometries; often, pores are assumed to have uniform 20 circular or square cross-sectional shapes.…”

Section: Introductionmentioning

confidence: 99%

“…PoreFlow has several features which 12 makes it a powerful tool for pore-scale modeling. It allows us to model sev- 13 eral different processes, starting from generation of a pore network model for 14 a specific porous media up to the simulation of c1 drainage and (two-phase) 15 fluid flow and c2 reactive/adsorptive solute or colloid transport (with possible 16 changes in pore sizes), under both saturated and variably saturated condi- 17 tions. c3 In addition, PoreFlow assigns volumes to both pore bodies and pore 18 throats and, unlike other pore network simulators, it refines discretizations of 19 drained pores to simulate flow and transport more accurately in the presence 20 c1 Text added.…”

Section: Introductionmentioning

confidence: 99%

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PoreFlow: A complex pore-network model for simulation of reactive transport in variably saturated porous media

Raoof

Nick

Hassanizadeh

et al. 2013

Computers & Geosciences

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141

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Pore-scale modeling of reactive transport in wellbore cement under CO2 storage conditions

Cited by 103 publications

References 73 publications

Dynamic Capillary Pressure Curves From Pore-Scale Modeling in Mixed-Wet-Rock Images

Dynamic Capillary Pressure Curves From Pore-Scale Modeling in Mixed-Wet-Rock Images

Pore-Network Modeling of Solute Transport and Biofilm Growth in Porous Media

PoreFlow: A complex pore-network model for simulation of reactive transport in variably saturated porous media

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