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Sandstone reservoir rocks are important for numerous applications, such as oil and gas recovery, CO2 storage and groundwater aquifers, and understanding how reservoir rock properties influence the dynamics of fluids and gases within reservoir rocks is essential yet difficult to predict. Heterogeneity complicates the identification of viable areas of recovery, potential areas of migration and groundwater catchment planning. To improve accuracy in reservoir flow models further analysis of the impact of heterogeneous reservoir rock properties on fluid transport is required. Pore network analysis is key in understanding fundamental concepts of fluid flow behaviour as pore network geometry is a dominant control on the effectiveness of fluid transport within a reservoir and is strongly associated with porosity and permeability. Despite this, there has been limited research into how heterogeneous rock properties influence fluid flow behaviour at the pore scale and analysis is commonly focused on samples which have homogeneous grain size and mineralogy. Heterogeneity in sandstone reservoir rocks can be categorised into three main types; 1) sedimentary, 2) structural, and 3) diagenetic. This thesis focuses on sedimentary heterogeneities, which are influenced by the environmental conditions at the time of sediment deposition, and the main aim of this thesis is to quantify the effect of heterogeneity in grain size and mineralogy on pore network geometry (pore diameter, porosity), fluid flow behaviour and mineral dissolution in the pore network. Ten synthetic, glass bead pack samples were designed based on naturally occurring sedimentary heterogeneities identified in cores from the Triassic Sherwood Sandstone and the Permian Rotliegend Group and used in pore-scale permeability experiments which validate the results from 3D visual analysis and simulations conducted in the Avizo Fire software and CFD simulations conducted in the ANSYS Fluent software. The experimental methodology for the pore-scale permeability experiments was designed and developed to enable reliable and accurate measurements of flow rate and pressure difference over a 3D customised bead pack sample. In order to achieve this, two degassing techniques were employed to fully purge trapped bubbles of air which occurred in the system/sample. The experiments produce reliable and repeatable data which are in agreement with results from the literature and permeability calculated using the Kozeny-Carman model, Avizo Fire simulations and ANSYS Fluent CFD simulations. The results from the experiments and simulations confirm the widely held view that bead size and heterogeneity in bead size influences the pore network geometry, fluid flow behaviour and permeability of a sample. In samples with homogeneous bead size, increasing bead size (54.5%) corresponds to larger mean pore diameter size (35.2%), a larger range in mean pore diameter size, less uniform distribution in pore diameter size, and greater porosity (0.74-3.47%). Less uniformity in pore diameter size increases tortuosity (2.65%) and facilitates high velocity preferential pathways which increases permeability (52.2-98.5% across all homogeneous samples and techniques). The effect of bead size heterogeneity is determined by the arrangement of the bead size (e.g. smaller beads changing to larger beads) and the mean pore diameter size and range of mean pore diameter size is lower (7.7%) and the distribution of pore diameter size is more uniform when smaller beads transition to larger beads. This is due to the reduction in pore space due to a poorer degree of sorting and increased packing density as smaller beads are able to invade the pore space between the larger beads. Greater uniformity in pore diameter size results in more consistent fluid flow (multiple, well distributed, smaller, low velocity flow pathways) and higher permeability (0.60-55.9% across all techniques) when fluid flow passes a transition from smaller beads to larger beads. The onset of non-Darcy flow was analysed in the samples with differing homogeneous bead size and heterogeneous bead size and the results suggest that the critical Reynold's number (the Reynold's number which corresponds with the onset of non-Darcy flow) is determined by pore size and greater pore size corresponds to a larger critical Reynold's number due to larger pores being more able to facilitate high velocity flow. In the samples with heterogeneous bead size different factors influence the critical Reynold's number and the critical Reynold's number decreases with decreasing tortuosity when fluid flow passes a transition from smaller beads to larger beads and the critical Reynold's number decreases due to increasing heterogeneity and decreasing permeability when flow flow crosses a transition from larger beads to smaller beads. The beta factor was also calculated and increases with decreasing bead size and the results from the samples with homogeneous bead size suggest that beta factor increases with decreasing permeability. The results from samples which present mineralogical heterogeneity show that the addition of kaolinite and dolomite reduces the mean pore diameter size (56.8-68.0%), the range of mean pore diameter size and the porosity (2.2-3.8%). Kaolinite results in a greater reduction in mean pore diameter size (68.0%) and increases the range of mean pore diameter size and this is due to the size and distribution of kaolinite which is more randomly distributed throughout the sample due to its greater range in particle size (0-63um). The impact of kaolinite is reduced when it occurs with dolomite as dolomite content restricts the distribution of kaolinite and this is due to the shape and size of the dolomite grains. Angular grains of dolomite occupy pore cavities and wedge alongside beads which is more destructive to porosity and limits accumulations of kaolinite to fewer pores. Increased variation in pore diameter size is related to increased tortuosity and longer fluid flow pathways which increases access to reactive minerals and increases dissolution. Kaolinite content is most destructive to permeability (73.4-88.0%), in comparison to dolomite content, as it increases heterogeneity in pore diameter size and reduces pore space the most. The impact of kaolinite on permeability is less severe when kaolinite occurs with dolomite as dolomite limits the random distribution of kaolinite throughout the pore network which limits heterogeneity. The permeability of the samples which contain dolomite was reduced after acidic flow despite evidence of mineral dissolution and this is interpreted to occur as a result of small particles becoming detached during dissolution and becoming lodged in pores and pore throats. Heterogeneity in bead size and mineralogy decreases the mean pore diameter size (31.6-65.4%) and porosity (3.7-5.7%), increases the range in mean pore diameter (20.3-26.0%) and reduces permeability (75.7%), in comparison to the bead pack samples which present mineralogical heterogeneity. The bead pack sample which presents heterogeneity in bead size and mineralogy displays comparable pore diameter, porosity and permeability results to the crushed rock sample which indicates that bead pack samples can present realistic pore network geometries. Dolomite dissolution increases (1.4-2.4%) when bead size is heterogeneous and permeability is reduced (76.6%) after acidic flow and the reduction in permeability is greater (44.1%) when heterogeneous bead size and mineralogy occur in a sample together and this is due to local variations in permeability which in turn can result in local fluctuations in reaction rates and mineral dissolution. Local fluctuations in reaction rates and dissolution may enhance the variations in permeability after acidic flow or create a series of permeability contrasts where regions of higher permeability enable a higher rate of reactions and dissolution and the regions of low permeability are less able to facilitate fluid and particle transport meaning that the pore space becomes clogged more easily which reduces permeability further.

Long-term maintenance of skeletal muscle is important for tissue health and function. Muscle stem cells, also termed satellite cells, are quiescent muscle progenitors residing within the muscle tissue and are indispensable for postnatal muscle growth and regeneration. Once activated by injury, satellite cells convert to proliferating myoblasts, which eventually differentiate and fuse to generate muscle fibres. Heparan sulphate proteoglycans, such as the syndecans, are expressed in satellite cells and contribute to regulation of several growth factor signalling pathways in addition to regulating cell-cell and cell-matrix adhesion. Previous studies have shown that genetic ablation of syndecan-3, a transmembrane heparan sulphate proteoglycan expressed in satellite cells and myoblasts, dramatically improves muscle regenerative potential in ageing and in pathological conditions such as muscular dystrophy. However, the molecular mechanisms underlying syndecan-3 function in muscle regeneration are poorly understood. In this project, I used an unbiased approach based on proteomics and bioinformatics to identify syndecan-3- regulated signalling pathways in myoblasts. I then validated the proteomics and bioinformatics results using traditional biochemistry and cell biology techniques. Interesting results were obtained from a global phosphoproteomic analysis of a control myoblast cell line compared to a syndecan-3 knockdown myoblast cell line. A general trend was observed in syndecan-3 knockdown myoblasts where the insulin/PI3K/mTOR signalling pathway was over-activated in serum-starved syndecan-3 knockdown myoblasts compared to control myoblasts. However, the same insulin/PI3K/mTOR signalling pathway showed a reduced response to serum stimulation in syndecan-3 knockdown myoblasts compared to control myoblasts. Therefore, I investigated the role of syndecan-3 in the regulation of insulin signalling in myoblasts. Results from insulin stimulation experiments in C2C12 and primary satellite cell-derived myoblasts revealed that syndecan-3 regulates the insulin signalling pathway likely by inhibiting AKT activation and consequently regulates the balance between myoblast proliferation and differentiation. These results indicate a novel role for syndecan3 in the regulation of insulin signalling during myogenesis.