DOAJ Open Access 2024

SkyScan 1172 X-ray micro-CT scanner of well-core digital modeling for geophysical analysis of landscape polystructures

Marsel A. Kadyrov Mikhail D. Zavatsky E. Yu Neelova Andrey A. Ponomarev Maksim S. Bikalenko

Abstrak

The present study deals with algorithms for the acquisition of a well-core digital model that is used in the Digital Well-Core technology or “Digital Petrophysics.” The study involved the initial implementation stage of this technology: identification of geometric dimensions of a sample and spatial scanning resolution, as well as of scanning and reconstruction settings to examine a well core in a SkyScan 1172 X-ray micro-CT system. Well-core samples 30 mm wide (7 µm/pixel resolution), 10 mm wide (4 µm/pixel resolution) and 5 mm wide (1.5 µm/pixel resolution) were examined by X-ray micro-computed tomography. The porosity coefficient of all samples was measured by the water-saturation and weighing method. The digital models were used to estimate the porosity coefficient compared to the standard method. The results demonstrated that the best convergence of micro-CT and standard method data was achieved with 5-mm samples at a 1.5 µm/pixel scan resolution. A study on digital model optimization through noise reduction in the NRecon standard software was also conducted and discovered that the best convergence of porosity coefficients was attained when smoothing was set at 8. The scanning and reconstruction settings proposed for well-core samples can be used to implement the Digital Well-Core technology.

Topik & Kata Kunci

Penulis (5)

M

Marsel A. Kadyrov

M

Mikhail D. Zavatsky

E

E. Yu Neelova

A

Andrey A. Ponomarev

M

Maksim S. Bikalenko

Format Sitasi

Kadyrov, M.A., Zavatsky, M.D., Neelova, E.Y., Ponomarev, A.A., Bikalenko, M.S. (2024). SkyScan 1172 X-ray micro-CT scanner of well-core digital modeling for geophysical analysis of landscape polystructures. https://doi.org/10.1080/24749508.2022.2131959

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Informasi Jurnal
Tahun Terbit
2024
Sumber Database
DOAJ
DOI
10.1080/24749508.2022.2131959
Akses
Open Access ✓