• Energy Research

Abstract Coal seam gas (CSG) is gaining global interests due to its natural abundance and environmental benefits in comparison to more traditional energy sources. However, due to its significant heterogeneity and complex porous structure, it is challenging to characterise and thus predict petrophysical properties. Moreover, the fracture network of coal poses a major challenge for direct numerical simulations on segmented images collected from X-ray micro-computed tomography (μCT). The segmentation of coal images is problematic and often results in misclassification of coal features that subsequently causes numerical instabilities. This paper aims to develop an advanced image analysis method and a novel discrete fracture network model to circumvent these issues. Coal μCT data are utilised for the acquisition of structural parameters and then discrete fracture networks are built to reconstruct representative coal images. The modelling method mimics the cleat formation process and reproduces particular cleat network patterns. The reconstructed network preserves the key attributes of coal, i.e. connectivity and cleat structure, while not being limited in terms of size and/or resolution. Furthermore, direct numerical simulations based on lattice Boltzmann method are performed on the cleat network realisations to evaluate coal permeability. We find that directional permeabilities result in different system scaling effects because of the dependence on the underlying structure of the cleat network. The developed method facilitates the evaluation of the relationship between coal cleat structure and resulting flow properties, which are steps forward in the evaluation of coal petrophysical properties at the core scale.

AbstractWe present experimental results based on computed x-ray microtomography (CMT) for quantifying capillary trapping mechanisms as a function of fluid properties using several pairs of analog fluids to span a range of potential supercritical CO2-brine conditions. Our experiments areconducted in a core-flood apparatus using synthetic porous media and we investigate capillary trapping by measuring trapped non-wetting phase area as a function of varying interfacial tension, viscosity, and fluid flow rate. Experiments are repeated for a single sintered glass bead core using three different non-wetting phase fluids, and varying concentrations of surfactants, to explore and separate the effects of interfacial tension, viscosity, and fluid flow rate. Analysis of the data demonstrates distinct and consistent differences in the amount of initial (i.e. following CO2 injection) and residual (i.e. following flood or WAG scheme) non-wetting phase occupancy as a function of fluid properties and flow rate. Further experimentation and analysis is needed, but these preliminary results indicate trends that can guide design of injection scenarios such that both initial and residual trapped gas occupancy is optimized.

AbstractProton exchange membrane fuel cells, consuming hydrogen and oxygen to generate clean electricity and water, suffer acute liquid water challenges. Accurate liquid water modelling is inherently challenging due to the multi-phase, multi-component, reactive dynamics within multi-scale, multi-layered porous media. In addition, currently inadequate imaging and modelling capabilities are limiting simulations to small areas (<1 mm2) or simplified architectures. Herein, an advancement in water modelling is achieved using X-ray micro-computed tomography, deep learned super-resolution, multi-label segmentation, and direct multi-phase simulation. The resulting image is the most resolved domain (16 mm2with 700 nm voxel resolution) and the largest direct multi-phase flow simulation of a fuel cell. This generalisable approach unveils multi-scale water clustering and transport mechanisms over large dry and flooded areas in the gas diffusion layer and flow fields, paving the way for next generation proton exchange membrane fuel cells with optimised structures and wettabilities.

Abstract In coal seam gas (CSG) reservoirs, the underlying fracture networks play a critical role in controlling flow pathways of methane and water phases. Thus, study of flow in fracture networks via different numerical modelling methods is of importance. Compared to direct flow simulation, the Fracture Pipe Network Model (FPNM) is an effective means of modelling fluid flow in a fracture network due to its computational efficiency. However, constructing FPNM for authentic samples is challenging due to the limited fracture data at the core scale. In addition, application of FPNM for coal is challenging due to its complex internal fracture network. With X-ray micro-computed tomography (micro-CT) imaging, internal fracture network of coal samples can be visualised non-destructively, providing deterministic input data for FPNM. However, analysing fractures individually and characterising network connectivity based on micro-CT images are difficult, due to complex interactions, irregular fracture geometry, resolution limitation and image noises. In this paper, we develop a framework for constructing image-based FPNM for real fractured coal cores for fast prediction of permeability. Compared with conventional FPNM, each pipe element of our improved FPNM has the identical properties (orientations, length, aperture and roughness) with its corresponding data from the real sample. By comparing permeability values obtained from FPNMs, micro-CT images and voxelised DFNs, we conclude that FPNM can effectively estimate the permeability of original fracture networks while requiring significantly lower computational cost that make it a suitable framework for expensive multi-phase multiphysics flow simulations.

Abstract Geological carbon sequestration is being considered worldwide as a means of mitigating anthropogenic emission of greenhouse gases. During sequestration, carbon dioxide (CO 2 ) gas effluent is captured from coal-fired power plants or other concentrated emission sources and injected into saline aquifers or depleted oil reservoirs for long term storage. In an effort to fully understand and optimize CO 2 trapping efficiency, the capillary mechanisms that immobilize subsurface CO 2 were analyzed at the pore-scale. Pairs of proxy fluids representing the potential range of in-situ conditions of supercritical CO 2 (nonwetting fluid) and brine (wetting fluid) were used during experimentation. The two fluids were imbibed and drained from a flow cell apparatus containing a sintered glass bead core. Fluid parameters (such as interfacial tension and fluid viscosities) and flow rate were altered to characterize their relative impact on capillary trapping. Computed x-ray microtomography (microCT) was used to quantify immobilized nonwetting fluid volumes after imbibition and drainage events. MicroCT-analyzed data suggests that capillary trapping in sintered glass bead (a mildly consolidated porous medium) is dictated by the capillary number ( Ca ), the viscosity ratio ( M ), and the Bond number ( Bo ) of the system, reflecting that all three viscous, capillary, and gravity forces affect the displacement process to varying degree as their relative importance changes. The amount of residual trapped nonwetting phase was observed to increase with increasing nonwetting fluid viscosity, and with decreasing density difference of the fluids; this suggests that CO 2 sequestration can potentially be engineered for optimal trapping through alterations to the viscosity or density of supercritical CO 2 .