MicroCT Analysis

Science ProblemDemanding for tools to better understand processes in fluidrock systems related to geologic sequestration of CO2 by using quantitative image analysis methods for automated measurements of experimental data as the calculation of material interfaces, quantification of CO2 during flow, recovery of material structures, etc. Other activities involve material interface reconstruction in simulation and deriving measurements (wetted surface area etc.) and methods for tracking boundaries to analyze pore region evolution. 

Permeability (K) is a fundamental measure for Earth scientists to determine the fluid flow through a porous material, and standard equations to estimate K lacks pore geometry. Previous work by Hazen included empirical formulation of K for saturated sands based on empirical coefficients and particle size. The main problem of this approach is that the particles are supposed to be quite homogeneous and to present fine grains. First Kozeny, then Carman proposed improvements to permeability calculation and postulated a new semiempirical, semitheoretical formulation known as KozenyCarman (KC)  this model considers geometry by including surface area per unit volume of particles in the formula. Further improvements are necessary to cope with limitations of KC formula, e.g. KC is only valid for laminar flow. Moreover, permeability is often associated to hydraulic conductivity because the water properties, e.g. viscosity, density, are well known and instruments use the flow of water through the material to calculate permeability. More about instruments . Information about permeability importance to oil industry. In a nutshell, our research consists in building algorithms that takes the INPUT: hundreds/thousands of slices, encoding tridimensional represention of solid objects and provides the OUTPUT: measurements of material porosity, permeability estimates, granularity of material, visualization of structures as pore network  

ApproachOne of the most challenge questions posed to material sciences is to determine permeability of materials with complex structure. Can we invent new formulations to calculate permeability regarding geometrical information about the structure? 
Synthetic beads: microCT images of porous materials are seldom composed by homogeneous particles, and they also present artifacts that can interfere in the calculation of permeability.
In order to isolate permeability models from issues associated to CT imaging and granularity, we generate synthetic datasets of randomly distributed sphere packing using numerical simulation of Stokes flow. The simulation algorithm
creates numerical constructions of jammed backed bead beds, with identical and nonoverlapping spheres, and following algorithms proposed by Salvatore Torquato, later modified by Todd Weisgraber (LLNL).
Link to further information and C++ code used in our experiments.
The use of synthetic beads is only the first step toward describing porous media, using a new descriptor based on topological analysis: maxflow curves
Pore network: Derived measures: a) effective pore radii: radius of a sphere of equivalent volume; b) effective throat radii = radius of a circle of equivalente area Fluid permeability curves: More about permeability curves  

ResultsThe extraction of Reeb graphs through which we represent the pore network allowed the extraction two main descriptors: flow curve and capacity. 
Synthetic beads:
Flow diagram Experimental data:  
Impact
 
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