The focus of this work is on the behavior of hydrocarbon-gas viscosity and gas density. The viscosity of hydrocarbon gases is a function of pressure, temperature, density, and molecular weight, while the gas density is a function of pressure, temperature, and molecular weight. This work presents new approaches for the prediction of gas viscosity and gas density for hydrocarbon gases over practical ranges of pressure, temperature, and composition. These correlations can be used for any hydrocarbon-gas production or transportation operations.In this work, we created a large database of measured gas viscosity and gas density. This database was used to evaluate existing models for gas viscosity and gas density. We also provide new models for gas density and gas viscosity, as well as optimization of existing models, using our new database.The objectives of this research are as follows:• To create a large-scale database of measured gas-viscosity and gas-density data. This database will contain all the information necessary to establish the applicability of various models for gas density and gas viscosity over a wide range of pressures and temperatures.• To evaluate a number of existing models for gas viscosity and gas density.• To develop new models for gas viscosity and gas density using our research database; these models are proposed and validated.For this study, we created a large database from existing sources available in the literature. The properties in our database include composition, viscosity, density, temperature, pressure, pseudoreduced properties, and the gas compressibility factor. We use this database to evaluate the applicability of existing models used to determine hydrocarbon-gas viscosity and hydrocarbon-gas density (or, more specifically, the gas z-factor). Finally, we developed new models and calculation approaches to estimate the hydrocarbon-gas viscosity, and we also provide an optimization of the existing equations of state (EOS) typically used for for the calculation of the gas z-factor. Introduction Hydrocarbon-Gas Viscosity. NIST-SUPERTRAP Algorithm.The state-of-the-art mechanism for the estimation of gas viscosity is most likely the computer program SUPERTRAP, developed at the U.S. Natl. Inst. of Standards and Technology (NIST). 1 SU-PERTRAP was developed from pure-component and mixture data and is stated to provide estimates within engineering accuracy from the triple point of a given substance to temperatures of 1,340.33°F and pressures of 44,100 psia. Because the SUPER-TRAP algorithm requires the composition for a particular sample, it generally would not be suitable for applications in which only the mixture gas gravity and compositions of any contaminants are known. Carr et al. Correlation.Carr et al. 2 developed a two-step procedure to estimate hydrocarbon-gas viscosity. The first step is to determine the gas viscosity at atmospheric conditions (i.e., a reference condition). Once estimated, the viscosity at atmospheric pressure is then adjusted to conditions at temperature and pressu...

The study of cardiac energetics commonly involves the use of isolated muscle preparations (papillary muscles or trabeculae carneae). Their contractile performance has been observed to vary inversely with thickness. This inverse dependence has been attributed, almost without exception, to inadequate diffusion of oxygen into the centers of muscles of large diameter. It is thus commonly hypothesized that the radius-dependent diminution of performance reflects the development of an anoxic core. We tested this hypothesis theoretically by solving a modification of the diffusion equation, in which the rate of oxygen consumption is a sigmoidal function of the partial pressure of oxygen. The model demonstrates that sufficiently thick muscles, operating at sufficiently high rates of oxygen demand or sufficiently low ambient partial pressures of oxygen, will indeed show diminished energetic performance, whether indirectly indexed as stress (force per cross-sectional area) development or as the rate of heat production. However, such simulated behavior requires the adoption of extreme parameter values, often differing by an order of magnitude from their experimental equivalents. We thus conclude that the radius-dependent diminution of muscle performance in vitro cannot be attributed entirely to an insufficient supply of oxygen via diffusion.

The goal of hydraulic stimulation is to increase formation permeability in the near vicinity of a well. However, there remain technical challenges around measuring the outcome of this operation. During two enhanced geothermal system stimulations in South Australia, Paralana in 2011 and Habanero in 2003, extensive catalogs of microseismicity were recovered. It is often assumed that shear failure of existing fractures is the main mechanism behind both the induced earthquakes and any permeability enhancement. This underpins a common notion that the seismically active volume is also the stimulated reservoir. Here we compute the density of earthquake hypocenters and provide evidence that, under certain conditions, this spatiotemporal quantity is a reasonable proxy for pore pressure increase. We then apply an inverse modeling approach that uses the earthquake observations and a modified reservoir simulator to estimate the parameters of a permeability evolution relation. The regime implied by the data indicates that most permeability enhancement occurred very near to the wellbore and was not coincident with the bulk of the seismicity, whose volume was about 2 orders of magnitude larger. Thus, we conclude that, in some cases, it is possible for permeability enhancement and induced seismicity to be decoupled, in which case the seismically active volume is a poor indicator of the stimulated reservoir. Our results raise serious questions about the effectiveness of hydroshearing as a stimulation mechanism in enhanced geothermal system. This study extends our understanding of the complex processes linking earthquakes, fluid pressure, and permeability in both natural and engineered settings.

Depletion of interstitial cells of Cajal (ICC) networks is known to occur in several gastrointestinal motility disorders. Although confocal microscopy can effectively image and visualize the spatial distribution of ICC networks, current descriptors of ICC depletion are limited to cell numbers and volume computations. Spatial changes in ICC network structural properties have not been quantified. Given that ICC generate electrical signals, the organization of a network may also affect physiology. In this study, six numerical metrics were formulated to automatically determine complex ICC network structural properties from confocal images: density, thickness, hole size, contact ratio, connectivity and anisotropy. These metrics were validated and applied in proof-of-concept studies to quantitatively determine jejunal ICC network changes in mouse models with decreased (5-HT 2B receptor knockout (KO)) and normal (Ano1 KO) ICC numbers, and during post-natal network maturation. Results revealed a novel remodelling phenomenon occurring during ICC depletion, namely a spatial rearrangement of ICC and the preferential longitudinal alignment. In the post-natal networks, an apparent pruning of the ICC network was demonstrated. The metrics developed here enabled the first detailed quantitative analyses of structural changes that may occur in ICC networks during depletion and development.

This dissertation presents the development of a method for quantitative integration of seismic (elastic) anisotropy attributes with reservoir performance data as an aid in characterization of systems of natural fractures in hydrocarbon reservoirs. This new method incorporates stochastic Discrete Feature Network (DFN) fracture modeling techniques, DFN model based fracture system hydraulic property and elastic anisotropy modeling, and non-linear inversion techniques, to achieve numerical integration of production data and seismic attributes for iterative refinement of initial trend and fracture intensity estimates. Although DFN modeling, flow simulation, and elastic anisotropy modeling are in themselves not new technologies, this dissertation represents the first known attempt to integrate advanced models for production performance and elastic anisotropy in fractured reservoirs using a rigorous mathematical inversion. The following new developments are presented:• Forward modeling and sensitivity analysis of the upscaled hydraulic properties of realistic DFN fracture models through use of effective permeability modeling techniques. iv• Forward modeling and sensitivity analysis of azimuthally variant seismic attributes based on the same DFN models.• Development of a combined production and seismic data objective function and computation of sensitivity coefficients.• Iterative model-based non-linear inversion of DFN fracture model trend and intensity through minimization of the combined objective function.This new technique is demonstrated on synthetic models with single and multiple fracture sets as well as differing background (host) reservoir hydraulic and elastic properties. Results on these synthetic control models show that, given a well conditioned initial DFN model and good quality field production and seismic observations, the integration procedure results in convergence of both fracture trend and intensity in models with both single and multiple fracture sets. Tests show that for a single fracture set convergence is accelerated when the combined objective function is used as compared to a similar technique using only production data in the objective function.Tests performed on multiple fracture sets show that, without the addition of seismic anisotropy, the model fails to converge. These tests validate the importance of the new process for use in more realistic reservoir models.

Multi-scale modeling has become a productive strategy for quantifying interstitial cells of Cajal (ICC) network structure-function relationships, but the lack of large-scale ICC network imaging data currently limits modeling progress. The SNESIM (Single Normal Equation Simulation) algorithm was utilized to generate realistic virtual images of small real wild-type (WT) and 5-HT2B-receptor knockout (Htr2b−/−) mice ICC networks. Two metrics were developed to validate the performance of the algorithm: (i) network density, which is the proportion of ICC in the tissue; (ii) connectivity, which reflects the degree of connectivity of the ICC network. Following validation, the SNESIM algorithm was modified to allow variation in the degree of ICC network depletion. ICC networks from a range of depletion severities were generated, and the electrical activity over these networks was simulated. The virtual ICC networks generated by the original SNESIM algorithm were similar to that of their real counterparts. The electrical activity simulations showed that the maximum current density magnitude increased as the network density increased. In conclusion, the SNESIM algorithm is an effective tool for generating realistic virtual ICC networks. The modified SNESIM algorithm can be used with simulation techniques to quantify the physiological consequences of ICC network depletion at various physical scales.

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Background Manometry is commonly used for diagnosis of esophageal and anorectal motility disorders. In the colon, manometry is a useful tool, but clinical application remains uncertain. This uncertainty is partly based upon the belief that manometry cannot reliably detect non-occluding colonic contractions and, therefore, cannot identify reliable markers of dysmotility. This study tests the ability of manometry to record pressure signals in response to non-lumen-occluding changes in diameter, at different rates of wall movement and with content of different viscosities. Methods A numerical model was built to investigate pressure changes caused by localized, non-lumen-occluding reductions in diameter, similar to those caused by contraction of the gut wall. A mechanical model, consisting of a sealed pressure vessel which could produce localized reductions in luminal diameter, was used to validate the model using luminal segments formed from; i) natural latex; and ii) sections of rabbit proximal colon. Fluids with viscosities ranging from 1mPa.s to 6800mPa.s and luminal contraction rates over the range 5 – 20 mmHg/s were studied. Key Results Manometry recorded non-occluding reductions in diameter, provided that they occurred with sufficiently viscous content. The measured signal was linearly dependent on the rate of reduction in luminal diameter and also increased with increasing viscosity of content (R2= 0.62 and 0.96 for 880 and 1760 mPa.s respectively). Conclusions & Inferences Manometry reliably registers non-occluding contractions in the presence of viscous content, and is therefore a viable tool for measuring colonic motility. Interpretation of colonic manometric data, and definitions based on manometric results, must consider the viscosity of luminal content.