Physically representative network models of transport in porous media
- BP Research, Middlesex (United Kingdom)
The authors calculate permeabilities for a class of granular porous media derived from a real, disordered packing of equal spheres. The entire structure, including pore space, of these media is completely specified by the radii and spatial locations of the constituent grains. When geometric nearest neighbor grains are grouped together, the structure may be subdivided into pore bodies and pore throats in a natural and unambiguous way. From this subdivision one can establish a network of flow paths whose geometry and topology are completely specified, so that permeability and other transport coefficients can be calculated directly and without any adjustable parameters. The calculations focus on processes that form porous media, rather than on specific examples of such media. Hence, the approach is essentially predictive, rather than correlative. No additional measurements (such as capillary pressure data or pore system data from thin sections) are required, and correlations between permeability and other properties are not used. Predicted permeabilities match measurements on sandstone sample similar to the model porous media studied here over a wide range of porosity. Geometrical attributes of the network representation of the pore space of the model media are found to be spatially correlated. This departure from randomness significantly affects permeability. The agreement between predictions and measurements suggests that spatial correlation is inherent in granular porous media and that uncorrelated network models are therefore unlikely to be physically representative of such media.
- OSTI ID:
- 6512378
- Journal Information:
- AIChE Journal (American Institute of Chemical Engineers); (United States), Journal Name: AIChE Journal (American Institute of Chemical Engineers); (United States) Vol. 39:3; ISSN 0001-1541; ISSN AICEAC
- Country of Publication:
- United States
- Language:
- English
Similar Records
Quantification of spatial correlation in porous media and its effect on mercury porosimetry
Related Subjects
020300* -- Petroleum-- Drilling & Production
CRYSTAL STRUCTURE
ENERGY SOURCES
FLUIDS
FORECASTING
FOSSIL FUELS
FUEL GAS
FUELS
GAS FUELS
GASES
GRANULAR MATERIALS
MASS TRANSFER
MATERIALS
MATHEMATICAL MODELS
MICROSTRUCTURE
NATURAL GAS
PERMEABILITY
PETROLEUM
POROSITY
POROUS MATERIALS
PRODUCTION
ROCKS
SANDSTONES
SEDIMENTARY ROCKS