TY - JOUR

T1 - A two-scale geostatistical approach for elastic properties estimation

AU - Lisitsa, V.

AU - Bazaikin, Ya

AU - Khachkova, T.

AU - Kolyukhin, D.

AU - Reshetova, G.

AU - Gurevich, B.

AU - Lebedev, M.

N1 - Funding Information: The research was supported by the Russian Science Foundation grant no. No. 17-17-01128. BG and ML thank the sponsors of the Curtin Reservoir Geophysics Consortium (CRGC) for financial support. The authors thank the National Geosequestration Laboratory (NGL) for providing access to the X-ray microscope VersaXRM-500 (Zeiss-Xradia Ltd). The National Geosequestration Laboratory is a collaboration between Curtin University, The University of Western Australia and CSIRO established to conduct and deploy critical research and development to enable commercial-scale carbon storage options. Funding for this facility was provided by the Australian Federal Government. Publisher Copyright: © 2017 SEG.

PY - 2017/8/17

Y1 - 2017/8/17

N2 - We present a new multi-scale numerical methodology to estimate of elastic properties of core samples. This approach combines the geostatistics to estimate distribution of effective cementing material, computational topology for automatic grain detection, and numerical upscaling. The main idea of the approach is to start from the microscopic images and finely-resolved CT-scans to estimate distribution of the grain surface roughness, distance between grins, and cementing material. After that using numerical upscaling generate distribution effective properties of cement but for the model with flat grain-to-grain contacts. At the last step we embed the effective cement into a mid-scale CT-scans, where grins are represented as convex polyhedrons obtained by means of computational topology.

AB - We present a new multi-scale numerical methodology to estimate of elastic properties of core samples. This approach combines the geostatistics to estimate distribution of effective cementing material, computational topology for automatic grain detection, and numerical upscaling. The main idea of the approach is to start from the microscopic images and finely-resolved CT-scans to estimate distribution of the grain surface roughness, distance between grins, and cementing material. After that using numerical upscaling generate distribution effective properties of cement but for the model with flat grain-to-grain contacts. At the last step we embed the effective cement into a mid-scale CT-scans, where grins are represented as convex polyhedrons obtained by means of computational topology.

UR - http://www.scopus.com/inward/record.url?scp=85121859596&partnerID=8YFLogxK

U2 - 10.1190/segam2017-17762866.1

DO - 10.1190/segam2017-17762866.1

M3 - Conference article

AN - SCOPUS:85121859596

SP - 3706

EP - 3710

JO - SEG Technical Program Expanded Abstracts

JF - SEG Technical Program Expanded Abstracts

SN - 1052-3812

T2 - Society of Exploration Geophysicists International Exposition and 87th Annual Meeting, SEG 2017

Y2 - 24 September 2017 through 29 September 2017

ER -