Image of A plugin for computing the pore/grain network tortuosity of a porous medium from 2D/3D MicroCT image

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A plugin for computing the pore/grain network tortuosity of a porous medium from 2D/3D MicroCT image

Tortuosity is an important geometrical parameter of the pore or grain network in a porous medium. Here we present and discuss an implementation of a plugin to estimate the pore/grain network tortuosity of a porous medium sample. The tortuosity is estimated according to the geometric reconstruction algorithm that can be applied to 2D or 3D μCT image samples. To illustrate the tortuosity plugin features, applications are given i) for the 2D case: three synthetic image samples being one horizontal straight line, one diagonal straight line and a curved line, and additionally it is considered a Dolomite Silurian rock sample, ii) for the 3D case: the pore network of a Berea and Fontainebleau sandstone and a Grosmont carbonte reservoir core samples; the grain network of a distal-radius trabecular bone sample and, finally, the pore network of a Rhodic Ferralsol soil sample. Some comments and discussions about the tortuosity estimated with the current algorithm are also addressed.

Ketersediaan
84551.136Perpustakaan BIG (Eksternal Harddisk)Tersedia
Informasi Detail
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Penerbit
Amsterdam : Elsevier.,
Deskripsi Fisik
14 hlm PDF, 6.599 KB
Bahasa
Inggris
ISBN/ISSN
2590-1974
Klasifikasi
551.136
Tipe Isi
text
Tipe Media
-
Tipe Pembawa
-
Edisi
Vol.5, March 2020
Subjek
Porous media
Tortuosity
ImageJ plugin
Reservoir rocks
Trabecular bone
Soil
Info Detail Spesifik
-
Pernyataan Tanggungjawab
Versi lain/terkait

Tidak tersedia versi lain

Lampiran Berkas
  • A plugin for computing the pore/grain network tortuosity of a porous medium from 2D/3D MicroCT image
    Tortuosity is an important geometrical parameter of the pore or grain network in a porous medium. Here we present and discuss an implementation of a plugin to estimate the pore/grain network tortuosity of a porous medium sample. The tortuosity is estimated according to the geometric reconstruction algorithm that can be applied to 2D or 3D μCT image samples. To illustrate the tortuosity plugin features, applications are given i) for the 2D case: three synthetic image samples being one horizontal straight line, one diagonal straight line and a curved line, and additionally it is considered a Dolomite Silurian rock sample, ii) for the 3D case: the pore network of a Berea and Fontainebleau sandstone and a Grosmont carbonte reservoir core samples; the grain network of a distal-radius trabecular bone sample and, finally, the pore network of a Rhodic Ferralsol soil sample. Some comments and discussions about the tortuosity estimated with the current algorithm are also addressed.
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