Reliable predictions of reservoir flow response corresponding to various recovery schemes require a realistic geological model of heterogeneity and an understanding of its relationship with the flow properties. This dissertation presents results on the implementation of a novel approach for the integration of dynamic data into reservoir models that combines stochastic techniques for simultaneous calibration of geological models and multiphase flow functions associated with porelevel spatial representations of porous media. In this probabilistic approach, a stochastic simulator is used to model the spatial distribution of a discrete number of rock types identified by rock/connectivity indexes (CIs). Each CI corresponds to a particular pore network structure with a characteristic connectivity. Primary drainage and imbibition displacement processes are modeled on the 3-D pore networks to generate multiphase flow functions corresponding to networks with different CIs. During history matching, the stochastic simulator perturbs the spatial distribution of the CIs to match the simulated pressures and flow rates to historic data, while preserving the geological model of heterogeneity. This goal is accomplished by applying a probabilistic approach for gradual deformation of spatial distribution of rock types characterized by different CIs. Perturbation of the CIs in turn results in the update of all the flow functions including the effective permeability, porosity of the rock, the relative permeabilities and capillary pressure. The convergence rate of the proposed method is comparable to other current techniques with the distinction of enabling consistent updates to all the flow functions. The resultant models are geologically consistent in terms of all the flow functions, and consequently, predictions obtained using these models are likely to be more accurate. To compare and contrast this comprehensive approach to reservoir modeling against other approaches that rely on modeling and perturbing only the permeability field, a realistic case study is presented with implementation of both approaches. Comparison is made with the history-matched model obtained only by perturbing permeability. It is argued that reliable predictions of future production can only be made when the entire suite of flow functions is consistent with the real reservoir.

Microscale fluid processes are an increasingly important subgroup of fluid mechanics. Applications for heat transfer and micro-electro-mechanical devices use flows on the scale of less than one hundred microns. This study is part of a larger work in which a multiphase, high shear environment is studied in a microchannel that has a depth of approximately 130 μm. Velocities are obtained using non-invasive imaging schemes. Laser induced fluorescent Particle Image Velocimetry (PIV) is used to analyze the velocity distribution in the microchannel. Multiple image processing techniques are used to optimize the images for correlation calculations. Velocity profiles for three flow rates and three void fractions (one of which is zero) are developed experimentally. The effect of the microbubbles on the PIV analysis is shown to flatten the profile through one primary mechanism and possibly a secondary, less dominant mechanism. / Graduation date: 2006

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Simulating the exact chaotic turbulent flow field about any geometry is a dilemma between accuracy and computational resources, which has been continuously studied for just over a hundred years. This thesis is a complete walk-through of the entire process utilized to approximate the flow ingested by a Sevik-type rotor based on solutions to the Reynolds Averaged Navier-Stokes equations (RANS). The Multiple Reference Frame fluid model is utilized by the code of ANSYS-FLUENT and results are validated by experimental wake data. Three open rotor configurations are studied including a uniform inflow and the rotor near a plate with and without a thick boundary layer. Furthermore, observations are made to determine the variation in velocity profiles of the ingested turbulent flow due to varying flow conditions. / by Felipe Ferreira Lachowski. / Thesis (M.S.C.S.)--Florida Atlantic University, 2013. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.

Hydrocarbon reserves are generally produced through wells drilled into reservoir pay zones. During production, gas liberation from the oil phase occurs due to pressure decline in the wellbore. Thus, we expect multiphase flow in some sections of the wellbore. As a multi-phase/multi-component gas-oil mixture flows from the reservoir to the surface, pressure, temperature, composition, and liquid holdup distributions are interrelated. Modeling these multiphase flow parameters is important to design production strategies such as artificial lift procedures. A wellbore fluid flow model can also be used for pressure transient test analysis and interpretation. Considering heat exchange in the wellbore is important to compute fluid flow parameters accurately. Modeling multiphase fluid flow in the wellbore becomes more complicated due to heat transfer between the wellbore fluids and the surrounding formations. Due to mass, momentum, and energy exchange between the wellbore and the reservoir, the wellbore model should be coupled with a numerical reservoir model to simulate fluid flow accurately. This model should be non-isothermal to consider the effect of temperature. Our research shows that, in some cases, ignoring compositional effects may lead to errors in pressure profile prediction for the wellbore. Nearly all multiphase wellbore simulations are currently performed using the "black oil" approach. The primary objective of this study was to develop a non-isothermal wellbore simulator to model transient fluid flow and temperature and couple the model to a reservoir simulator called General Purpose Adaptive Simulator (GPAS). The coupled wellbore/reservoir simulator can be applied to steady state problems, such as production from, or injection to a reservoir as well as during transient phenomena such as well tests to accurately model wellbore effects. Fluid flow in the wellbore may be modeled either using the blackoil approach or the compositional approach, as required by the complexity of the fluids. The simulation results of the new model were compared with field data for pressure gradients and temperature distribution obtained from wireline conveyed pressure recorder and acoustic fluid level measurements for a gas/oil producer well during a buildup test. The model results are in good agreement with the field data. Our simulator gave us further insights into the wellbore dynamics that occur during transient problems such as phase segregation and counter-current multiphase flow. We show that neglecting these multiphase flow dynamics would lead to unreliable results in well testing analysis.

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