Rock properties from micro-CT images: Digital rock transforms for resolution, pore volume, and field of view. (December 2019)

• Record Type: Journal Article
• Authors: Saxena, Nishank; Hows, Amie; Hofmann, Ronny; Alpak, Faruk O.; Dietderich, Jesse; Appel, Matthias; Freeman, Justin; De Jong, Hilko
• Is Part Of: Advances in water resources. Volume 134(2019)
• Publication Date: 2019-12
• Subjects: Digital rock -- Porosity -- Permeability -- Numerical simulations; Hydrology -- Periodicals; Hydrodynamics -- Periodicals; Hydraulic engineering -- Periodicals; 551.48
• DOI: 10.1016/j.advwatres.2019.103419
• Languages: English
• ISSNs: 0309-1708

Abstract

Highlights: Theoretical framework that defines the impact of image resolution, segmentation, and field of view on porosity and permeability derived using micro-CT images. Novel transforms to estimate porosity and permeability using micro-CT images without the need of laboratory measurement or higher resolution images. Method applicable to other natural and synthetic porous media. Abstract: Digital Rock Physics is a promising approach for achieving more, cheaper, and faster rock property characterization of digital images of rock samples. To successfully deliver on this potential, we must correctly interpret the digitally derived properties in the context of the limitations imposed by imaging constraints. To this end, we show that a combination of limited image resolution, a biased segmentation of images with coarse resolution, and a finite field of view of images, generated by the present micro-Computed Tomography (micro-CT) technology, leads to systematic underestimation of porosity (down to a factor of 0.5) and overestimation of permeability (up to a factor of 10) calculated using the Digital Rock Physics (DRP). We demonstrate these imaging limitations can be overcome by identifying good measures of image resolution and representative elementary volume and applying appropriate transforms. These transforms expand the operating envelop of DRP. Transforms for finite image resolution and limited field of view can be estimated directly from the micro-CT images. However, implementation of transforms related to errors in image segmentation require either a higher resolution image (e.g., nano-computed tomography, scanning electron microscopy) or laboratory measured constraints (Mercury injection capillary pressure, NMR porosity). Additionally, we suggest how insights from these transforms can be used to define operating envelopes and optimize imaging resolution and field of view to achieve more reliable results from digital rock characterization and simulations.