Extending Predictive Capabilities to Network Models

Øren, Pål‐Eric; Bakke, Stig; Arntzen, Ole Jakob

doi:10.2118/38880-ms

Cited by 114 publications

(168 citation statements)

References 61 publications

(68 reference statements)

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“…Lenormand and Zarcone (1984) have taken advantage of the well-defined shapes of capillary tubes in their moulded resin models to compare the results of calculations of two-phase flow in both drainage and imbibition processes with observation results. Micromodel observations have also played a significant role in development of network models for application to multiphase flow (Lenormand et al 1983;Øren and Pinczewski 1991;Øren et al 1992;Li and Yortsos 1995;Bakke and Øren 1997;Øren et al 1998;Sohrabi et al 2000Sohrabi et al , 2001Øren and Bakke 2002).…”

mentioning

confidence: 99%

Visualisation of Residual Oil Recovery by Near-miscible Gas and SWAG Injection Using High-pressure Micromodels

2008

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We present results of high-pressure micromodel visualizations of pore-scale fluid distribution and displacement mechanisms during the recovery of residual oil by nearmiscible hydrocarbon gas and SWAG (simultaneous water and gas) injection under conditions of very low gas-oil IFT (interfacial tension), negligible gravity forces and water-wet porous medium. We demonstrate that a significant amount of residual oil left behind after waterflooding can be recovered by both near-miscible gas and SWAG injection. In particular, we show that in both processes, the recovery of the contacted residual oil continues behind the main gas front and ultimately all of the oil that can be contacted by the gas will be recovered. This oil is recovered by a microscopic mechanism, which is strongly linked to the low IFT between the oil and gas and to the perfect spreading of the oil over water, both of which occur as the critical point of the gas-oil system is approached. Ultimate oil recovery by near-miscible SWAG injection was as high as near-miscible gas injection with SWAG injection using much less gas compared to gas injection. Comparison of the results of SWAG experiments with two different gas fractional flow values (SWAG ratio) of 0.5 and 0.2 shows that fractional flow of the near-miscible gas injected simultaneously with water is not a crucial factor for ultimate oil recovery. This makes SWAG injection an attractive IOR (improved oil recovery) process especially for reservoirs, where continuous and high-rate gas injection is not possible (e.g. due to supply constraint).

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mentioning

confidence: 99%

Visualisation of Residual Oil Recovery by Near-miscible Gas and SWAG Injection Using High-pressure Micromodels

2008

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“…The impact of extracted pore networks from tomographic images on the residual phase saturations can be found in the paper by Sok et al (2002). Oren et al (1998) published their work on computing transport properties using pore network technique. The comparison between digital rock prediction and lab experiments on relative permeability can be found in the publication by Valvatne and Blunt (2004).…”

Section: Mps Reconstruction Of Three-dimensional Pore Space At Microsmentioning

confidence: 99%

MPS-Driven Digital Rock Modeling and Upscaling

Zhang

2015

Math Geosci

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This paper starts with an overview of the application of multiple-point statistics (MPS) to characterizing and modeling heterogeneous rocks with the aid of digital rock technology. An upscaling workflow from microscopic pore space to interwell scales is proposed and discussed by illustrative examples. In this MPS-driven upscaling workflow, training images, which play a key role in MPS modeling, are obtained directly from microscopic rock or borehole images or digital outcrops to capture more realistic heterogeneity of reservoir rocks and formations. Unlike the conventional upscaling method that typically applies a certain averaging scheme to coarsening a fine scale model, which tends to lose heterogeneous features that may be critical to fluid flow, the proposed workflow calls for both top-down and bottom-up approaches. The top-down approach aims to divide heterogeneous rock into different representative element volumes (REV) such that each one is more uniform or less heterogeneous; the bottom-up approach attempts to derive effective transport properties by carrying over the computed dynamic properties through running flow simulation from fine to coarser scales with the help of REV identification. This workflow allows us to couple the static with dynamic modeling to derive scale-dependent effective transport properties while capturing more realistic rock heterogeneity using MPS.

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“…There is mounting evidence that rock networks exhibit much lower coordination numbers Ioannidis et al, 1997;Øren et al, 1997;Ioannidis and Chatzis, 2000;Øren and Bakke, 2002). Lindquist et al (1999Lindquist et al ( , 2000 have generated rock networks directly from reconstructions of X-ray computed micro-tomographic images of Fontainebleau sandstone.…”

Section: Real Rock Networkmentioning

confidence: 99%

Volume Conservation of the Intermediate Phase in Three-Phase Pore-Network Models

et al. 2005

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Quasi-static rule-based network models used to calculate capillary dominated multiphase transport properties in porous media employ equilibrium fluid saturation distributions which assume that pores are fully filled with a single bulk fluid with other fluids present only as wetting and/or spreading films. We show that for drainage dominated three-phase displacements in which a non-wetting fluid (gas) displaces a trapped intermediate fluid (residual oil) in the presence of a mobile wetting fluid (water) this assumption distorts the dynamics of threephase displacements and results in significant volume errors for the intermediate fluid and erroneous calculations of intermediate fluid residual saturations, relative permeabilities and recoveries. The volume errors are associated with the double drainage mechanism which is responsible for the mobilization of waterflood residual oil. A simple modification of the double drainage mechanism is proposed which allows the presence of a relatively small number of partially filled pores and removes the oil volume errors.

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Extending Predictive Capabilities to Network Models

Cited by 114 publications

References 61 publications

Visualisation of Residual Oil Recovery by Near-miscible Gas and SWAG Injection Using High-pressure Micromodels

Visualisation of Residual Oil Recovery by Near-miscible Gas and SWAG Injection Using High-pressure Micromodels

MPS-Driven Digital Rock Modeling and Upscaling

Volume Conservation of the Intermediate Phase in Three-Phase Pore-Network Models

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