944 resultados para ES-SAGD. pressure drop. heavy oil. reservoir modeling and simulation


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Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. ^ There are two issues in using HLPNs—modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. ^ For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. ^ For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. ^ The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.^

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Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. There are two issues in using HLPNs - modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.

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Crop models are simplified mathematical representations of the interacting biological and environmental components of the dynamic soil–plant–environment system. Sorghum crop modeling has evolved in parallel with crop modeling capability in general, since its origins in the 1960s and 1970s. Here we briefly review the trajectory in sorghum crop modeling leading to the development of advanced models. We then (i) overview the structure and function of the sorghum model in the Agricultural Production System sIMulator (APSIM) to exemplify advanced modeling concepts that suit both agronomic and breeding applications, (ii) review an example of use of sorghum modeling in supporting agronomic management decisions, (iii) review an example of the use of sorghum modeling in plant breeding, and (iv) consider implications for future roles of sorghum crop modeling. Modeling and simulation provide an avenue to explore consequences of crop management decision options in situations confronted with risks associated with seasonal climate uncertainties. Here we consider the possibility of manipulating planting configuration and density in sorghum as a means to manipulate the productivity–risk trade-off. A simulation analysis of decision options is presented and avenues for its use with decision-makers discussed. Modeling and simulation also provide opportunities to improve breeding efficiency by either dissecting complex traits to more amenable targets for genetics and breeding, or by trait evaluation via phenotypic prediction in target production regions to help prioritize effort and assess breeding strategies. Here we consider studies on the stay-green trait in sorghum, which confers yield advantage in water-limited situations, to exemplify both aspects. The possible future roles of sorghum modeling in agronomy and breeding are discussed as are opportunities related to their synergistic interaction. The potential to add significant value to the revolution in plant breeding associated with genomic technologies is identified as the new modeling frontier.

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The oil companies in the area in general are looking for new technologies that can increase the recovery factor of oil contained in reservoirs. These investments are mainly aimed at reducing the costs of projects which are high. Steam injection is one of these special methods of recovery in which steam is injected into the reservoir in order to reduce the viscosity of the oil and make it more mobile. The process assisted gravity drainage steam (SAGD) using steam injection in its mechanism, as well as two parallel horizontal wells. In this process steam is injected through the horizontal injection well, then a vapor chamber is formed by heating the oil in the reservoir and, by the action of gravitational forces, this oil is drained down to where the production well. This study aims to analyze the influence of pressure drop and heat along the injection well in the SAGD process. Numerical simulations were performed using the thermal simulator STARS of CMG (Computer Modeling Group). The parameters studied were the thermal conductivity of the formation, the flow of steam injection, the inner diameter of the column, the steam quality and temperature. A factorial design was used to verify the influence of the parameters studied in the recovery factor. We also analyzed different injection flow rates for the model with pressure drop and no pressure drop, as well as different maximum flow rates of oil production. Finally, we performed an economic analysis of the two models in order to check the profitability of the projects studied. The results showed that the pressure drop in injection well have a significant influence on the SAGD process.

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The oil companies in the area in general are looking for new technologies that can increase the recovery factor of oil contained in reservoirs. These investments are mainly aimed at reducing the costs of projects which are high. Steam injection is one of these special methods of recovery in which steam is injected into the reservoir in order to reduce the viscosity of the oil and make it more mobile. The process assisted gravity drainage steam (SAGD) using steam injection in its mechanism, as well as two parallel horizontal wells. In this process steam is injected through the horizontal injection well, then a vapor chamber is formed by heating the oil in the reservoir and, by the action of gravitational forces, this oil is drained down to where the production well. This study aims to analyze the influence of pressure drop and heat along the injection well in the SAGD process. Numerical simulations were performed using the thermal simulator STARS of CMG (Computer Modeling Group). The parameters studied were the thermal conductivity of the formation, the flow of steam injection, the inner diameter of the column, the steam quality and temperature. A factorial design was used to verify the influence of the parameters studied in the recovery factor. We also analyzed different injection flow rates for the model with pressure drop and no pressure drop, as well as different maximum flow rates of oil production. Finally, we performed an economic analysis of the two models in order to check the profitability of the projects studied. The results showed that the pressure drop in injection well have a significant influence on the SAGD process.

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We have modeled numerically the seismic response of a poroelastic inclusion with properties applicable to an oil reservoir that interacts with an ambient wavefield. The model includes wave-induced fluid flow caused by pressure differences between mesoscopic-scale (i.e., in the order of centimeters to meters) heterogeneities. We used a viscoelastic approximation on the macroscopic scale to implement the attenuation and dispersion resulting from this mesoscopic-scale theory in numerical simulations of wave propagation on the kilometer scale. This upscaling method includes finite-element modeling of wave-induced fluid flow to determine effective seismic properties of the poroelastic media, such as attenuation of P- and S-waves. The fitted, equivalent, viscoelastic behavior is implemented in finite-difference wave propagation simulations. With this two-stage process, we model numerically the quasi-poroelastic wave-propagation on the kilometer scale and study the impact of fluid properties and fluid saturation on the modeled seismic amplitudes. In particular, we addressed the question of whether poroelastic effects within an oil reservoir may be a plausible explanation for low-frequency ambient wavefield modifications observed at oil fields in recent years. Our results indicate that ambient wavefield modification is expected to occur for oil reservoirs exhibiting high attenuation. Whether or not such modifications can be detected in surface recordings, however, will depend on acquisition design and noise mitigation processing as well as site-specific conditions, such as the geologic complexity of the subsurface, the nature of the ambient wavefield, and the amount of surface noise.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The pipe flow of a viscous-oil-gas-water mixture such as that involved in heavy oil production is a rather complex thereto-fluid dynamical problem. Considering the complexity of three-phase flow, it is of fundamental importance the introduction of a flow pattern classification tool to obtain useful information about the flow structure. Flow patterns are important because they indicate the degree of mixing during flow and the spatial distribution of phases. In particular, the pressure drop and temperature evolution along the pipe is highly dependent on the spatial configuration of the phases. In this work we investigate the three-phase water-assisted flow patterns, i.e. those configurations where water is injected in order to reduce friction caused by the viscous oil. Phase flow rates and pressure drop data from previous laboratory experiments in a horizontal pipe are used for flow pattern identification by means of the 'support vector machine' technique (SVM).

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The chemical and physical properties of a Brazilian heavy oil submitted to plasma treatment were investigated by H-1 low-and high-field nuclear magnetic resonance (NMR) combined to the characterization of rheological properties, thermogravimetry and measurement of basic sediments and water (BSW) content. The crude oil was treated in a dielectric barrier discharge plasma reactor, using natural gas, CO2 or H-2 as working gas. The results indicated a large drop in the water content of the plasma-treated samples as compared to the crude oil, giving rise to a reduction in the viscosity. No significant chemical change was produced in the oil portion itself, as observed by H-1 NMR. The water contents determined by H-1 low-field NMR analyses agreed well with those obtained by BSW, indicating the low-field NMR methods as a useful tool for following the effects of plasma treatments on heavy oils, allowing the separation of the effects caused on the water and oil fractions. (C) 2011 Elsevier Ltd. All rights reserved.

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The use of the core-annular flow pattern, where a thin fluid surrounds a very viscous one, has been suggested as an attractive artificial-lift method for heavy oils in the current Brazilian ultra-deepwater production scenario. This paper reports the pressure drop measurements and the core-annular flow observed in a 2 7/8-inch and 300 meter deep pilot-scale well conveying a mixture of heavy crude oil (2000 mPa.s and 950 kg/m3 at 35 C) and water at several combinations of the individual flow rates. The two-phase pressure drop data are compared with those of single-phase oil flow to assess the gains due to water injection. Another issue is the handling of the core-annular flow once it has been established. High-frequency pressure-gradient signals were collected and a treatment based on the Gabor transform together with neural networks is proposed as a promising solution for monitoring and control. The preliminary results are encouraging. The pilot-scale tests, including long-term experiments, were conducted in order to investigate the applicability of using water to transport heavy oils in actual wells. It represents an important step towards the full scale application of the proposed artificial-lift technology. The registered improvements in terms of oil production rate and pressure drop reductions are remarkable.

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In refrigeration systems a small amount of compressor lubricant is entrained in the refrigerant and circulated through the system, where some is retained in each component. The suction line to the compressor has the largest potential for oil retention. This paper presents results from an experimental apparatus that has been constructed to circulate POE (polyolester) oil and R410A at a controlled mass flux, OCR (oil in circulation ratio), and apparent superheat, and to directly measure the pressure drop and mass of oil retained in horizontal and vertical suction lines. The bulk vapor velocity and overall void fraction are determined from direct mass and temperature measurements. The oil retention, pressure drop, and flow regimes near the minimum ASHRAE recommended mass flux condition are explored. It was found that oil retention begins to increase sharply even above the minimum recommended flux, so conditions near the minimum should be avoided. Two relationships were developed to predict the oil retention in the vertical and horizontal suction lines. The average error from the predictions method was 10.9% for the vertical tube, and 7.9% for the horizontal tube.

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Continuous steam injection is one of heavy oil thermal recovery methods used in the Brazilian Northeast because of high occurrence of heavy oil reservoir. In this process, the oil into the reservoir is heated while reduces, substantially, its viscosity and improves the production. This work analyzed how the shaly sand layers influenced in the recovery. The studied models were synthetics, but the used reservoir data can be extrapolated to real situations of Potiguar Basin. The modeling was executed using the STARS - Steam Thermal and Advanced Process Reservoir Simulator - whose version was 2007.10. STARS is a tool of CMG Computer Modeling Group. The study was conducted in two stages, the first we analyzed the influence of reservoir parameters in the thermal process, so some of these were studied, including: horizontal permeability of the reservoir and the layer of shaly sand, ratio of horizontal permeability to vertical permeability, the influence of capillary pressure layer of shaly sand and as the location and dimensions of this heterogeneity can affect the productivity of oil. Among the parameters studied the horizontal permeability of the reservoir showed the most significant influence on the process followed by diversity. In the second stage three models were selected and studied some operational parameters such as injection rate, distance between wells, production time and completion intervals. Among the operating parameters studied the low rate and intermediate distances between wells showed the best recoveries

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Continuous steam injection is one of heavy oil thermal recovery methods used in the Brazilian Northeast because of high occurrence of heavy oil reservoir. In this process, the oil into the reservoir is heated while reduces, substantially, its viscosity and improves the production. This work analyzed how the shaly sand layers influenced in the recovery. The studied models were synthetics, but the used reservoir data can be extrapolated to real situations of Potiguar Basin. The modeling was executed using the STARS - Steam Thermal and Advanced Process Reservoir Simulator - whose version was 2007.10. STARS is a tool of CMG Computer Modeling Group. The study was conducted in two stages, the first we analyzed the influence of reservoir parameters in the thermal process, so some of these were studied, including: horizontal permeability of the reservoir and the layer of shaly sand, ratio of horizontal permeability to vertical permeability, the influence of capillary pressure layer of shaly sand and as the location and dimensions of this heterogeneity can affect the productivity of oil. Among the parameters studied the horizontal permeability of the reservoir showed the most significant influence on the process followed by diversity. In the second stage three models were selected and studied some operational parameters such as injection rate, distance between wells, production time and completion intervals. Among the operating parameters studied the low rate and intermediate distances between wells showed the best recoveries

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The study of non-Newtonian flow in plate heat exchangers (PHEs) is of great importance for the food industry. The objective of this work was to study the pressure drop of pineapple juice in a PHE with 50 degrees chevron plates. Density and flow properties of pineapple juice were determined and correlated with temperature (17.4 <= T <= 85.8 degrees C) and soluble solids content (11.0 <= X(s) <= 52.4 degrees Brix). The Ostwald-de Waele (power law) model described well the rheological behavior. The friction factor for non-isothermal flow of pineapple juice in the PHE was obtained for diagonal and parallel/side flow. Experimental results were well correlated with the generalized Reynolds number (20 <= Re(g) <= 1230) and were compared with predictions from equations from the literature. The mean absolute error for pressure drop prediction was 4% for the diagonal plate and 10% for the parallel plate.

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Dissertação para obtenção do Grau de Mestre em Engenharia Geológica (Georrecursos)