3D Stochastic Modelling of Heterogeneous Porous Media – Applications to Reservoir Rocks

Wu, Kaihua; Dijke, Marinus Izaak Jan Van; Couples, Gary Douglas; Jiang, Zeyun; Ma, Jinxing; Sorbie, Kenneth Stuart; Crawford, John W.; Young, Iain M.; Zhang, Xiaoxian

doi:10.1007/s11242-006-0006-z

Cited by 204 publications

(87 citation statements)

References 75 publications

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“…SEM images were used in a digital rock reconstruction methodology to generate a 3D model of the rock and infer the pore space using the pore architecture modelling (PAM) as developed by Wu et al (2006). 3D models generated by this technique can be used in a multiphase flow simulator to determine the multiphase flow dynamics as well as understand the geometry and topological properties of the pore system.…”

Section: A Proposed Transport Model For the Experimental Systemmentioning

confidence: 99%

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Experimental determination of noble gases and SF6, as tracers of CO2 flow through porous sandstone

et al. 2018

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A B S T R A C TIn order to label the CO 2 injected underground for geological storage and allow it to be differentiated from natural sources, a panoply of additive chemical tracers have been proposed. Yet, the transport of these tracers relative to CO 2 in pore space is currently poorly constrained. This leads to uncertainty as to whether tracers will act as an early warning of CO 2 arrival, or be preferentially retained in the pore space making them ineffective. Here, we present the factors affecting transport of noble gases and SF 6 relative to CO 2 in a porous rock. Using a porous sandstone core, each of the tracers were loaded into a sample loop and injected as discrete gas pulses into a CO 2 carrier stream at five different experiment pressures (10-50 kPag upstream to ambient pressure downstream). Tracer arrival profiles were measured using a quadrupole mass spectrometer. Significantly, our results show that peak arrival times of helium were slower than the other noble gases at each pressure gradient. The differences in peak arrival times between helium and other noble gases increased as the pressure gradient along the system decreased and the curve profiles for each noble gas differ significantly. The heavier noble gases (Kr and Xe) along with SF 6 show an earlier arrival time and a wider curve profile compared to He and Ne curves through the CO 2 carrier gas stream. This shows that Kr and Xe could be substituted for SF 6 , a potent greenhouse gas, in tracer applications. For comparison, CO 2 pulses were passed through a N 2 carrier gas resulting in significantly slower peak arrival times compared to those of noble gases and SF 6 . Hence, all investigated tracers when co-injected with CO 2 could potentially act as early warning tracers of CO 2 arrival, though we find that Kr, Xe and SF 6 will provide the most robust advance warning. Analysis of our experimental results shows that they cannot be explained by a simple one dimensional flow model through a porous medium. We outline a conceptual model that incorporates different preferential flow paths depending on flow velocities of individual gas streams. This model can explain the observed dataset and shows that the flow of noble gases and SF 6 tracers is influenced by pore-scale heterogeneity.

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Section: A Proposed Transport Model For the Experimental Systemmentioning

confidence: 99%

“…7). A digital pore network was extracted from each model before flow simulation was performed (Wu et al, 2006). Primary drainage was assessed through the injection of oil into an initially water-saturated medium and Fig.…”

Section: A Proposed Transport Model For the Experimental Systemmentioning

confidence: 99%

Experimental determination of noble gases and SF6, as tracers of CO2 flow through porous sandstone

et al. 2018

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“…Pore space reconstruction packing of grains followed by geological processes such as sedimentation, compaction, and diagenesis by which sedimentary structures were formed (Øren & Bakke, 2002;Bryant et al, 1993b,a). The third approach is to use a statistical model to generate synthetic 3D structures that capture the properties of two dimensional (2D) thin sections (Wu et al, 2006;Okabe & Blunt, 2007). Besides the 3D representation of the pore spaces, the straight capillary tube bundle model represents the pore space in an alternative simple but physically-sound way (van Dijke & Sorbie, 2002a;Dong et al, 2005;Helland & Skjaeveland, 2006b;Lindquist, 2006).…”

Section: Pore Space Reconstructionmentioning

confidence: 99%

“…proposed; for instance, the multiple-point method or the five-point stencil method using a Markov chain Monte Carlo model (Wu et al, 2006), which reproduce typical patterns of the void space seen in 2D and consequently preserve the long-range connectivity. These statistical methods produce high resolution 3D images derived from their original 2D inputs with similar morphological statistics.…”

Section: Construction Of 3d Pore Spaces From 2d Rock Imagesmentioning

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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“…Several alternative techniques have been developed to statistically generate 3D models of porous media from spatial information derived from simple 2D images, such as thin sections. [5,6] Wu et al [7] describe a non-iterative stochastic reconstruction method, called the pore architecture model (or The analysis of the 3D microstructure of porous materials is of importance in multiple disciplines, such as reservoir engineering and environmental science. We have developed a suite of methods to characterize the geometry and topology of pore systems from 3D images of samples, allowing us to extract pore network representations for use in network flow models that predict single-/multi-phase fluid flow properties.…”

mentioning

confidence: 99%

The Impact of Pore Size and Pore Connectivity on Single‐Phase Fluid Flow in Porous Media

Jiang

Couples

et al. 2010

Adv Eng Mater

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The primary motivation that underlies imaging activities is to use the images to predict physical properties of the materials being investigated. Arguably, predicting fluid flow is one of the most important drivers for many image studies. To improve the prediction of fluid flow in porous media, it is important to understand the factors that control the flow velocities and fluid-phase distributions. Vogel and Roth [1] demonstrate that the geometry and topology of the pore system, which we can consider as being the shapes and connectivities of the pore space components, both play significant roles. If image acquisition and processing introduce artifacts that lead to misrepresentations of the pore-system characteristics, then the prediction of physical properties is likely to be incorrect. Here, we emphasize the importance of accurate determination of both the geometric and topological characteristics of the pore system by investigating how arbitrary alterations of realistic poresystems impact on flow predictions.The morphological properties of the pore space can be difficult to visualize or to quantify. Only a few properties, like the porosity or grain size distribution of the porous medium, can be determined easily in the laboratory. Laboratory measurements of properties can be demanding and expensive, and it is not obvious how to link such measurements with the fundamental controlling factors. In order to progress the research that seeks to identify the factors that govern flow in porous media, and enabled by recent advances in computerized tomography (CT)

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3D Stochastic Modelling of Heterogeneous Porous Media – Applications to Reservoir Rocks

Cited by 204 publications

References 75 publications

Experimental determination of noble gases and SF6, as tracers of CO2 flow through porous sandstone

Experimental determination of noble gases and SF6, as tracers of CO2 flow through porous sandstone

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

The Impact of Pore Size and Pore Connectivity on Single‐Phase Fluid Flow in Porous Media

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