Final PhD Seminar

Predicting Permeability and Threshold Pressure in Low-Resolution Micro-CT Images of Heterogeneous Laminated Sandstone

Date & time

Tue 7 Feb 2017, 10.30–11.30am

Location

Room:

Seminar Rm 3.17

Audience

Members of RSPE welcome
Mr Pieter Botha
Department of Applied Mathematics, RSPE, The Australian National University

Subsurface oil and gas reservoirs and fresh water aquifer systems are characterised by geological characteristics such as grain size and porosity, as well as a range of petrophysical properties such as permeability and capillary pressure, all of which contribute to fluid flow behaviour during resource extraction and fluid injection and storage. Modern X-ray micro-Computed Tomography (µCT) imaging of cores, in combination with petrophysical simulation software, often referred to as Digital Rock Physics, is fast becoming a standard tool for augmenting reservoir characterisation and modelling. Due to the nature of µCT imaging and the associated analytical equipment, sample size is limited and governs the attainable resolution. The research objective is to investigate the relationships between geological characteristics and petrophysical properties of heterogeneous laminated sandstone with the aim to develop a predictive workflow to estimate fluid flow properties for low-resolution images of larger rock volumes where they cannot be computed directly because of insufficient image resolution. I investigate two 25 mm diameter and 80 mm tall core samples of heterogeneous sandstone, for which 5 µm/voxel resolution is required to compute permeability and threshold pressure directly. Results show good agreement between statistical predictions of these petrophysical properties made from characteristics computed from intermediate-resolution images at 16 µm/voxel and low-resolution images at ~60 µm/voxel (similar to typical whole core image resolutions). The statistical models to predict permeability and threshold pressure from the low-resolution images include open pore fraction and formation factor as predictor characteristics. Although binarized images at this resolution do not completely capture the pore system, I infer that these characteristics implicitly contain information about the critical fluid flow pathways, which control permeability and threshold pressure. Formation factor in particular is set to take into account the intermediate gray scale values, which increases in abundance with decreasing image resolution and is spatially located predominantly at the grain-pore boundaries, and therefore inherently contain information about the pore system length scale.

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