Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6922434 | Computers & Geosciences | 2016 | 11 Pages |
Abstract
Microtomography provides detailed 3D internal structures of materials in micro- to tens of nano-meter resolution and is quickly turning into a new technology for studying petrophysical properties of rocks. An important step is the upscaling of these properties as micron or sub-micron resolution can only be achieved on the sample-scale of millimeters or even less than a millimeter. We have developed a computational workflow for the analysis of microstructures including the upscaling of material properties. Computations of properties are first performed using conventional material science simulations at micro to nano-scale. The subsequent upscaling of these properties is done by a novel renormalization procedure based on percolation theory. In this paper we discuss the computational challenges arising from the workflow, which include: 1) characterization of microtomography for extremely large data sets; 2) computational fluid dynamics simulations at pore-scale for permeability estimation; 3) solid mechanical computations at pore-scale for estimating elasto-plastic properties; 4) Extracting critical exponents from derivative models for scaling laws. We conclude that significant progress in each of these challenges is necessary to transform microtomography from the current research problem into a robust computational big data tool for multi-scale scientific and engineering problems.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Jie Liu, Gerald G. Pereira, Qingbin Liu, Klaus Regenauer-Lieb,