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Pore-network extraction from micro-computerized-tomography images

Physical Review E · 2009 · Vol. 80(3) · pp. 036307–036307
Dong HuMartin J. Blunt

Abstract

Network models that represent the void space of a rock by a lattice of pores connected by throats can predict relative permeability once the pore geometry and wettability are known. Micro-computerized-tomography scanning provides a three-dimensional image of the pore space. However, these images cannot be directly input into network models. In this paper a modified maximal ball algorithm, extending the work of Silin and Patzek [D. Silin and T. Patzek, Physica A 371, 336 (2006)], is developed to extract simplified networks of pores and throats with parametrized geometry and interconnectivity from images of the pore space. The parameters of the pore networks, such as coordination number, and pore and throat size distributions are computed and compared to benchmark data from networks extracted by other methods, experimental data, and direct computation of permeability and formation factor on the underlying images. Good agreement is reached in most cases allowing networks derived from a wide variety of rock types to be used for predictive modeling.

Enhanced Oil Recovery TechniquesHydrocarbon exploration and reservoir analysisPetroleum Processing and AnalysisInterconnectivityComputationTomographyCharacterisation of pore space in soilLattice (music)WettingGeometryVoid (composites)Computer scienceMaterials science

MeSH terms

AlgorithmsMaterials TestingRadiographic Image Interpretation, Computer-AssistedTomography, X-Ray ComputedPorosity

Funding

  • Imperial College London
Citations
1,225
FWCI
29.76
field-weighted impact
References
42
Percentile
100%
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References
Pore space morphology analysis using maximal inscribed spheres
Physica A Statistical Mechanics and its Applications · 2006 · 471 citations
Reconstructing random media
Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · 1998 · 888 citations
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