Improving the Estimations of Petrophysical Transport Behavior of Carbonate Rocks Using a Dual Pore Network Approach Combined with Computed Microtomography

Bauer, Daniela; Youssef, S.; Fleury, Marc; Békri, S.; Rosenberg, Elisabeth; Vizika, O.

doi:10.1007/s11242-012-9941-z

Cited by 90 publications

(78 citation statements)

References 25 publications

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“…The papers in this special issue provide a limited but still diverse overview of applications of pore-scale models that can be used for multi-scale modeling and upscaling (Bauer et al 2012;Tsakiroglou 2012;Kim and Lindquist 2012); dynamics of multiphase flow in porous media (Joekar-Niasar and Hassanizadeh 2012b; Ramstad et al 2012) as well as effects of topological changes of porous media on flow properties (Mousavi and Bryant 2012;Jiang et al 2012;Chareyre et al 2012).…”

Section: Discussionmentioning

confidence: 99%

“…Several fundamental concepts are covered in this issue: fundamental understanding of dynamics of two-phase flow using dynamic pore-network models (Joekar-Niasar and Hassanizadeh (2012b)) or LB simulation (Ramstad et al (2012)), evaluation of petrophysical properties of dual porous media (Bauer et al (2012)), upscalling of two-phase flow (Tsakiroglou (2012)), diagenetic effects of cementation and compaction on porous media flow (Mousavi and Bryant (2012)), and upscaling of reactive transport (Kim and Lindquist (2012)). Moreover, generation of pore networks based on the statistical properties or direct generation of the network are other main lines of research as discussed in Jiang et al (2012) and Chareyre et al (2012).…”

Section: Content Of This Issuementioning

confidence: 99%

“…Moreover, generation of pore networks based on the statistical properties or direct generation of the network are other main lines of research as discussed in Jiang et al (2012) and Chareyre et al (2012). Bauer et al (2012) present a dual-pore-network approach (D-PNM) based on µ-CT images at different length scales of bimodal porous media. Their multiscale method supplements a pore network at the coarser scale with pore elements representing the underlying finer scale (microporosity), and is used to calculate petrophysical properties.…”

Section: Content Of This Issuementioning

confidence: 99%

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Pore-Scale Modeling of Multiphase Flow and Transport: Achievements and Perspectives

2012

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Section: Discussionmentioning

confidence: 99%

Section: Content Of This Issuementioning

confidence: 99%

Section: Content Of This Issuementioning

confidence: 99%

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Pore-Scale Modeling of Multiphase Flow and Transport: Achievements and Perspectives

2012

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“…The invasion percolations were performed using an algorithm developed in-house [16] based on the Washburn equation [69]. This describes the capillary pressure P c required to invade a pore: Figure 1 Schematic showing rock sample data processing and binarization methodology.…”

Section: Invasion Percolationmentioning

confidence: 99%

“…Recently, carbonate saline aquifers have been identified as suitable carbon dioxide sequestration sites due to their high porosity, effective stratigraphic trapping, and global abundance [14,15]. However, in contrast to sandstones, the complex microstructure of carbonates [16] requires a more in-depth investigation before their pore-scale transport can be known.…”

Section: Introductionmentioning

confidence: 99%

Pore Structure Characterization of Indiana Limestone and Pink Dolomite from Pore Network Reconstructions

Freire-Gormaly

Ellis

MacLean

et al. 2015

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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-Carbon sequestration in deep underground saline aquifers holds significant promise for reducing atmospheric carbon dioxide emissions (CO 2 ). However, challenges remain in predicting the long term migration of injected CO 2 . Addressing these challenges requires an understanding of pore-scale transport of CO 2 within existing brine-filled geological reservoirs. Studies on the transport of fluids through geological porous media have predominantly focused on oil-bearing formations such as sandstone. However, few studies have considered pore-scale transport within limestone and other carbonate formations, which are found in potential storage sites. In this work, high-resolution micro-Computed Tomography (microCT) was used to obtain pore-scale structural information of two model carbonates: Indiana Limestone and Pink Dolomite. A modified watershed algorithm was applied to extract pore network from the reconstructed microCT volumetric images of rock samples and compile a list of pore-scale characteristics from the extracted networks. These include statistical distributions of pore size and radius, pore-pore separation, throat radius, and network coordination. Finally, invasion percolation algorithms were applied to determine saturation-pressure curves for the rock samples. The statistical distributions were comparable to literature values for the Indiana Limestone. This served as validation for the network extraction approach for Pink Dolomite, which has not been considered previously. Based on the connectivity and the pore-pore separation, formations such as Pink Dolomite may present suitable storage sites for carbon storage. The pore structural distributions and saturation curves obtained in this study can be used to inform core-and reservoir-scale modeling and experimental studies of sequestration feasibility.Résumé -Caractérisation de la structure de pore de l'Indiana limestone de calcaire et de Pink dolomite provenant des reconstitutions de réseaux de pores -La séquestration du carbone dans les aquifères salins profonds souterrains est très prometteuse pour la réduction des émissions de dioxyde de carbone (CO 2 ) dans l'atmosphère. Cependant, des problèmes demeurent dans la prédiction de la migration à long terme du CO 2 injecté. Relever ces défis nécessite une compréhension du transport de CO 2 à l'échelle du pore dans des réservoirs géologiques existants remplis de saumure. Les études sur le transport des fluides en milieu poreux géologique ont principalement porté sur les formations oléagineuses telles que le grès. Cependant, peu d'études ont

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Investigating the relative permeability behavior of microporosity‐rich carbonates and tight sandstones with multiscale pore network models

et al. 2016

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The relative permeability behavior of rocks with wide ranges of pore sizes is in many cases still poorly understood and is difficult to model at the pore scale. In this work, we investigate the capillary pressure and relative permeability behavior of three outcrop carbonates and two tight reservoir sandstones with wide, multimodal pore size distributions. To examine how the drainage and imbibition properties of these complex rock types are influenced by the connectivity of macropores to each other and to zones with unresolved small‐scale porosity, we apply a previously presented microcomputed‐tomography‐based multiscale pore network model to these samples. The sensitivity to the properties of the small‐scale porosity is studied by performing simulations with different artificial sphere‐packing‐based networks as a proxy for these pores. Finally, the mixed‐wet water‐flooding behavior of the samples is investigated, assuming different wettability distributions for the microporosity and macroporosity. While this work is not an attempt to perform predictive modeling, it seeks to qualitatively explain the behavior of the investigated samples and illustrates some of the most recent developments in multiscale pore network modeling.

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Improving the Estimations of Petrophysical Transport Behavior of Carbonate Rocks Using a Dual Pore Network Approach Combined with Computed Microtomography

Cited by 90 publications

References 25 publications

Pore-Scale Modeling of Multiphase Flow and Transport: Achievements and Perspectives

Pore-Scale Modeling of Multiphase Flow and Transport: Achievements and Perspectives

Pore Structure Characterization of Indiana Limestone and Pink Dolomite from Pore Network Reconstructions

Investigating the relative permeability behavior of microporosity‐rich carbonates and tight sandstones with multiscale pore network models

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