Netflow Python library – A free software tool for the generation and analysis of pore or flow networks

State-of-the-art tomographic scanning techniques provide detailed pore-space geometries of natural porous media, which are central for the study of subsurface flow and transport. Due to experimental and computational limitations, the extraction of high-resolution images is limited to relatively smal...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autor principal:	Daniel W. Meyer
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Dendrogram Cluster Heterogeneity Connectivity Porous media Pathway Science Q
Acceso en línea:	https://doaj.org/article/4de3a0b3451e457cbaae660d63b01784
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:4de3a0b3451e457cbaae660d63b01784
record_format	dspace
spelling	oai:doaj.org-article:4de3a0b3451e457cbaae660d63b017842021-11-28T04:32:31ZNetflow Python library – A free software tool for the generation and analysis of pore or flow networks2215-016110.1016/j.mex.2021.101592https://doaj.org/article/4de3a0b3451e457cbaae660d63b017842021-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2215016121003824https://doaj.org/toc/2215-0161State-of-the-art tomographic scanning techniques provide detailed pore-space geometries of natural porous media, which are central for the study of subsurface flow and transport. Due to experimental and computational limitations, the extraction of high-resolution images is limited to relatively small sample volumes. To reduce the amount of data and the physical complexity, pore-space geometries are routinely translated into pore network models. Subsequently, such networks are expanded in space with suitable computational methods to determine effective medium parameters at larger scales relevant in engineering applications. While existing methods can provide networks with effective flow parameters being consistent with experimental data for comparably homogeneous media such as bead packs and sandstones, these methods are inadequate for more complex heterogeneous rocks such as carbonates or become too expensive for large networks. The netflow Python library accompanying this paper extends existing methods by preserving pore clusters that are a key characteristic of heterogeneous rocks. To this end dendrograms are extracted from experimental data and perturbed when generating larger networks. Moreover, the methods included in the netflow library are implemented in computationally efficient ways and enable the generation of large periodic networks that virtually eliminate boundary effects, which interfere in existing methods.• The netflow Python library enables the generation of large irregular networks, as it preserves pore or node clusters which are present in certain natural rock types.• The netflow Python library allows for the generation and flow analysis of boundary-free periodic networks. It further includes methods to convert periodic networks into conventional cubical ones.Daniel W. MeyerElsevierarticleDendrogramClusterHeterogeneityConnectivityPorous mediaPathwayScienceQENMethodsX, Vol 8, Iss , Pp 101592- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Dendrogram Cluster Heterogeneity Connectivity Porous media Pathway Science Q
spellingShingle	Dendrogram Cluster Heterogeneity Connectivity Porous media Pathway Science Q Daniel W. Meyer Netflow Python library – A free software tool for the generation and analysis of pore or flow networks
description	State-of-the-art tomographic scanning techniques provide detailed pore-space geometries of natural porous media, which are central for the study of subsurface flow and transport. Due to experimental and computational limitations, the extraction of high-resolution images is limited to relatively small sample volumes. To reduce the amount of data and the physical complexity, pore-space geometries are routinely translated into pore network models. Subsequently, such networks are expanded in space with suitable computational methods to determine effective medium parameters at larger scales relevant in engineering applications. While existing methods can provide networks with effective flow parameters being consistent with experimental data for comparably homogeneous media such as bead packs and sandstones, these methods are inadequate for more complex heterogeneous rocks such as carbonates or become too expensive for large networks. The netflow Python library accompanying this paper extends existing methods by preserving pore clusters that are a key characteristic of heterogeneous rocks. To this end dendrograms are extracted from experimental data and perturbed when generating larger networks. Moreover, the methods included in the netflow library are implemented in computationally efficient ways and enable the generation of large periodic networks that virtually eliminate boundary effects, which interfere in existing methods.• The netflow Python library enables the generation of large irregular networks, as it preserves pore or node clusters which are present in certain natural rock types.• The netflow Python library allows for the generation and flow analysis of boundary-free periodic networks. It further includes methods to convert periodic networks into conventional cubical ones.
format	article
author	Daniel W. Meyer
author_facet	Daniel W. Meyer
author_sort	Daniel W. Meyer
title	Netflow Python library – A free software tool for the generation and analysis of pore or flow networks
title_short	Netflow Python library – A free software tool for the generation and analysis of pore or flow networks
title_full	Netflow Python library – A free software tool for the generation and analysis of pore or flow networks
title_fullStr	Netflow Python library – A free software tool for the generation and analysis of pore or flow networks
title_full_unstemmed	Netflow Python library – A free software tool for the generation and analysis of pore or flow networks
title_sort	netflow python library – a free software tool for the generation and analysis of pore or flow networks
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/4de3a0b3451e457cbaae660d63b01784
work_keys_str_mv	AT danielwmeyer netflowpythonlibraryafreesoftwaretoolforthegenerationandanalysisofporeorflownetworks
_version_	1718408314419675136

Netflow Python library – A free software tool for the generation and analysis of pore or flow networks

Ejemplares similares