Packing states of ideal reservoir sands: Insights from simulation of porosity reduction by grain rearrangement

Weltje, Gert Jan; Alberts, L.

doi:10.1016/j.sedgeo.2011.10.001

Cited by 11 publications

(7 citation statements)

References 94 publications

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“…One reason for this may be the digitization errors of digital objects represented at a resolution of 0.5 mm/voxel. The effect can be supported by the fact that the porosity of 0.355 simulated for glass beads is less than the limit of 0.36 in a random dense packing of spheres (Scott, 1960;Allen, 1985;Yu and Standish, 1991;Weltje and Alberts, 2011). This is probably because the spherical shape of glass beads is not perfectly described at such a resolution (0.9% digitization error), causing a reduction of porosity.…”

Section: Digitization Inaccuracymentioning

confidence: 99%

Validation of a stochastic digital packing algorithm for porosity prediction in fluvial gravel deposits

Liang

Schruff

Jia

et al. 2015

Sedimentary Geology

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Section: Digitization Inaccuracymentioning

confidence: 99%

Validation of a stochastic digital packing algorithm for porosity prediction in fluvial gravel deposits

Liang

Schruff

Jia

et al. 2015

Sedimentary Geology

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“…The random packing is subdivided into random close packing (with shaking) [5,7,17,18] and random loose packing (no shaking) [16,19,20]; it may allow trimming, sliding, rolling, lifting or overlapping of particles [18,21]. The packing models can be divided into static, dynamic and combined [22]. Static models of particle packing are designed to produce a fixed arrangement [6], whereas dynamic models are capable of producing a sequence of arrangements.…”

Section: Packing Propertiesmentioning

confidence: 99%

Monosized sphere packing approach in the nanoporous structure modeling

Burtseva

Pestryakov

Petranovskii

2012

2012 7th International Forum on Strategic Technology (IFOST)

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In many structural models atoms appear as hard monosized spheres. The properties of nanostructured porous matrix filled by adsorbed substance strongly depend on the density of atoms in nanochannels, those can be interpreted as cylinders. The problem of densest packing of monosized spheres in a cylindrical container is considered. It belongs to the optimization problems of Computational Geometry and is known to be NP-hard, i.e. its exact solution cannot be obtained in a polynomial time. Some approaches of the problem, which are applicable for modeling of nanoporous structures, are discussed. The classifications of packing models and known maximal densities are given. Three approaches represent different approximations in the modeling of packing's. Those are: i) the numerical simulation, based on the geometrical properties, wall effects, and determination of stable position of spheres under gravity; ii) the Voronoi-Delaunay network, which models the channel structure in 3D space; and iii) the non-linear mathematical programming methods employed for densest packing search through cylinder height minimizing. These methods can be used for diverse nanoporous structure designs.

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“…Determination of porosity is problematic because it is usually hard to quantify realistically (Denny 2002;Weltje and Alberts 2011). The porosity of sedimentary deposits gets considerably modified due to burial and other diagenetic processes (Worden et al 1997).…”

Section: Introductionmentioning

confidence: 99%

Modelling the effect of grain anisotropy on inter-granular porosity

Katre

Nair

2021

J Petrol Explor Prod Technol

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Porosity is the dominant factor that determines the exploitable capacity of sedimentary reservoir rocks. Generally, pore heterogeneity is poorly represented in subsurface geological models due to the complexity. Granular mixtures produce complex pore space controlled by grain size, grain shape, and grain sorting. Heterogeneities in pore space volume are present at micro- and nanoscales in granular mixtures due to packing conditions resulting from deposition and diagenesis. In the present study, three-dimensional packing models were generated to provide a realistic description of granular mixtures. Accordingly, this study presents static packing models for unit cells idealised for spherical and elongated grains using cubic, orthorhombic, and rhombohedral packing models. Subsequently, the grain shape effects in terms of elongation degree and grain size distribution in terms of the degree of sorting were evaluated. The mixing effect on the inter-granular porosity for each unit cell packing model was analysed. A range of porosity values was derived using grain parameters generated through in-house developed MATLAB codes from digital FESEM images of sandstone samples. Our study demonstrates that actual grain size does not influence porosity, but for real sandstone samples, the sorting and shape of grains affect porosity values. The range of porosity values estimated by this method can be realistic at the basin level as the grain shape effects replicate sediment maturity. The developed method can be adopted in the distributed spatial models on porosity, especially for basin-scale hydrocarbon resource estimation.

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Packing states of ideal reservoir sands: Insights from simulation of porosity reduction by grain rearrangement

Cited by 11 publications

References 94 publications

Validation of a stochastic digital packing algorithm for porosity prediction in fluvial gravel deposits

Validation of a stochastic digital packing algorithm for porosity prediction in fluvial gravel deposits

Monosized sphere packing approach in the nanoporous structure modeling

Modelling the effect of grain anisotropy on inter-granular porosity

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