• Energy Research

The effective thermal conductivity enhancement of carbon fiber composites is investigated in this contribution using a three-dimensional numerical method. First a more realistic three-dimensional distribution of fibers dispersed in a matrix phase is reproduced by a developed random generation-growth method to eliminate the overrated inter-fiber contacts by the two-dimensional simulations. The energy transport governing equations are then solved through the three-dimensional structures using a high-efficiency lattice Boltzmann scheme. The resultant predictions agree well with the available experimental data. Compared with the existing theoretical models, the present method does not depend upon empirical parameters which have to be determined case by case, so that it is useful for design and optimization for new materials, beyond prediction and analysis just for existing composites.

The effective thermal conductivity enhancement of carbon fiber composites is investigated in this contribution using a three-dimensional numerical method. First a more realistic three-dimensional distribution of fibers dispersed in a matrix phase is reproduced by a developed random generation-growth method to eliminate the overrated inter-fiber contacts by the two-dimensional simulations. The energy transport governing equations are then solved through the three-dimensional structures using a high-efficiency lattice Boltzmann scheme. The resultant predictions agree well with the available experimental data. Compared with the existing theoretical models, the present method does not depend upon empirical parameters which have to be determined case by case, so that it is useful for design and optimization for new materials, beyond prediction and analysis just for existing composites.

Field operations report that at least half of the fracturing fluid used in shale reservoirs is trapped. These trapped fluids can trigger various geochemical interactions. However, the impact of these interactions on well performance is still elusive. We modeled a hydraulic fracture stage where we simulated the initial conditions by injecting the fracturing fluid and shutting the well to allow the fluids to soak into the formation. Our results suggest a positive correlation between the dissolution and precipitation rates and the carbonate content of the rock. In addition, we observed that gas and load recovery are overestimated when geochemical interactions are overlooked. We also observed promising results for sea water as a good alternative fracturing fluid. Moreover, we observed better performance for cases with lower-saline connate water. The reactions of carbonates outweigh the reactions of clays in most cases. Sensitivity analysis suggests that the concentration of SO4, K and Na ions in the fracturing fluid, and the illite and calcite mineral content, along with the reservoir temperature, are the key factors affecting well performance. In conclusion, geochemical interactions should be considered for properly modeling the fate of the fracturing fluids and their impact on well performance.

Field operations report that at least half of the fracturing fluid used in shale reservoirs is trapped. These trapped fluids can trigger various geochemical interactions. However, the impact of these interactions on well performance is still elusive. We modeled a hydraulic fracture stage where we simulated the initial conditions by injecting the fracturing fluid and shutting the well to allow the fluids to soak into the formation. Our results suggest a positive correlation between the dissolution and precipitation rates and the carbonate content of the rock. In addition, we observed that gas and load recovery are overestimated when geochemical interactions are overlooked. We also observed promising results for sea water as a good alternative fracturing fluid. Moreover, we observed better performance for cases with lower-saline connate water. The reactions of carbonates outweigh the reactions of clays in most cases. Sensitivity analysis suggests that the concentration of SO4, K and Na ions in the fracturing fluid, and the illite and calcite mineral content, along with the reservoir temperature, are the key factors affecting well performance. In conclusion, geochemical interactions should be considered for properly modeling the fate of the fracturing fluids and their impact on well performance.

Gas flow in shale is associated with both organic matter (OM) and inorganic matter (IOM) which contain nanopores ranging in size from a few to hundreds of nanometers. In addition to the noncontinuum effect which leads to an apparent permeability of gas higher than the intrinsic permeability, the surface diffusion of adsorbed gas in organic pores also can influence the apparent permeability through its own transport mechanism. In this study, a generalized lattice Boltzmann model (GLBM) is employed for gas flow through the reconstructed shale matrix consisting of OM and IOM. The Expectation-Maximization (EM) algorithm is used to assign the pore size distribution to each component, and the dusty gas model (DGM) and generalized Maxwell-Stefan model (GMS) are adopted to calculate the apparent permeability accounting for multiple transport mechanisms including viscous flow, Knudsen diffusion and surface diffusion. Effects of pore radius and pressure on permeability of both IOM and OM as well as effects of Langmuir parameters on OM are investigated. Moreover, the effect of total organic content and distribution on the apparent permeability of the reconstructed shale matrix is also studied. It is found that the distribution of OM and IOM has a negligible influence on apparent permeability, whereas the total organic content and the surface diffusion play a significant role in gas transport in shale matrix. 19 pages, 17 Figures

Gas flow in shale is associated with both organic matter (OM) and inorganic matter (IOM) which contain nanopores ranging in size from a few to hundreds of nanometers. In addition to the noncontinuum effect which leads to an apparent permeability of gas higher than the intrinsic permeability, the surface diffusion of adsorbed gas in organic pores also can influence the apparent permeability through its own transport mechanism. In this study, a generalized lattice Boltzmann model (GLBM) is employed for gas flow through the reconstructed shale matrix consisting of OM and IOM. The Expectation-Maximization (EM) algorithm is used to assign the pore size distribution to each component, and the dusty gas model (DGM) and generalized Maxwell-Stefan model (GMS) are adopted to calculate the apparent permeability accounting for multiple transport mechanisms including viscous flow, Knudsen diffusion and surface diffusion. Effects of pore radius and pressure on permeability of both IOM and OM as well as effects of Langmuir parameters on OM are investigated. Moreover, the effect of total organic content and distribution on the apparent permeability of the reconstructed shale matrix is also studied. It is found that the distribution of OM and IOM has a negligible influence on apparent permeability, whereas the total organic content and the surface diffusion play a significant role in gas transport in shale matrix. 19 pages, 17 Figures