Multi-scale Digital Imaging for Porous Material Permeability
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Solution Overview
Problem
Current methods for computing two-phase and three-phase relative permeabilities in porous materials are inefficient, inaccurate, and difficult to reproduce due to the heterogeneity of materials and limited imaging resolutions, leading to challenges in characterizing multiphase flow behavior and estimating reservoir productivity.
Innovation Solution
A method and system that utilize multi-scale digital imaging and numerical simulations, such as computational fluid dynamics, to compute absolute permeabilities and relative permeabilities by reconstructing three-dimensional digital representations of porous materials at various resolutions, allowing for the upscaled computation of physical properties without the need for expensive laboratory experiments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional laboratory experiments are used to measure relative permeabilities, then measurement accuracy can be achieved, but time consumption and cost increase significantly
Solution Approach 1:
The patent creates digital replicas (virtual models) of porous materials through 3D reconstruction from imaging data. These digital copies enable virtual experiments that compute relative permeabilities without physical laboratory testing, dramatically reducing time and cost while maintaining measurement accuracy through numerical simulations
Solution Approach 2:
The patent replaces physical laboratory measurement systems with computational simulation systems. Instead of conducting actual fluid flow experiments through porous materials, the system uses numerical methods to solve flow equations on reconstructed digital models, substituting mechanical/physical processes with computational ones
2Measurement precision
If high-resolution imaging is used to capture porous material microstructure, then measurement precision improves, but device complexity and data processing requirements increase
Solution Approach 1:
The patent divides the imaging process into multiple resolution levels (coarse and fine resolutions). Different regions of the porous material are imaged at appropriate resolutions based on their importance, reducing overall data complexity while maintaining precision where needed. This segmented approach balances measurement accuracy with manageable device and data requirements
3Manufacturing precision
If multi-scale imaging is employed to capture different microstructure sizes, then manufacturing precision of digital models improves, but device complexity and processing time increase
Solution Approach 1:
The patent implements a nested multi-scale imaging approach where coarse-resolution images provide the overall structure and fine-resolution images capture detailed microfeatures. The fine-scale details are nested within the coarse-scale framework, creating a hierarchical digital model that achieves high manufacturing precision while managing device complexity through structured data organization
Solution Approach 2:
The patent adds the resolution scale as an additional dimension to the imaging process. Instead of using a single resolution level, the system captures data at multiple resolution levels, effectively transitioning from a one-dimensional (single resolution) to a two-dimensional (multi-resolution) imaging approach, which improves digital model accuracy while providing structured data for efficient processing
Data Source
AI summary
A method for computing physical properties of materials, such as two-phase and three-phase relative permeabilities through a porous material, is described. The method employs single or multi-scale digital images of a representative sample which capture one or multiple fractionations of a micro-structure size cascade at the respective, required imaging resolutions. At a high resolution, the method computes basic physical properties, such as absolute permeabilities with a numerical method such as computational fluid dynamics solving the Navier-Stokes equation, and capillary pressure with simulations solving Young-Laplace equation. Saturation states of multiple fluids are combined to derive capillary pressure relationships at low resolutions when necessary. Upscaled physical properties, such as upscaled relative permeabilities corresponding to the low resolutions, are subsequently computed using the composition of multiple permeable facies at corresponding upscaled saturations determined by upscaled capillary pressure, honoring upscaled governing laws of the physical property, such as Darcy's law.