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


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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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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 purpose of this paper is to develop a second-moment closure with a near-wall turbulent pressure diffusion model for three-dimensional complex flows, and to evaluate the influence of the turbulent diffusion term on the prediction of detached and secondary flows. A complete turbulent diffusion model including a near-wall turbulent pressure diffusion closure for the slow part was developed based on the tensorial form of Lumley and included in a re-calibrated wall-normal-free Reynolds-stress model developed by Gerolymos and Vallet. The proposed model was validated against several one-, two, and three-dimensional complex flows.

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Statistical comparison of oil samples is an integral part of oil spill identification, which deals with the process of linking an oil spill with its source of origin. In current practice, a frequentist hypothesis test is often used to evaluate evidence in support of a match between a spill and a source sample. As frequentist tests are only able to evaluate evidence against a hypothesis but not in support of it, we argue that this leads to unsound statistical reasoning. Moreover, currently only verbal conclusions on a very coarse scale can be made about the match between two samples, whereas a finer quantitative assessment would often be preferred. To address these issues, we propose a Bayesian predictive approach for evaluating the similarity between the chemical compositions of two oil samples. We derive the underlying statistical model from some basic assumptions on modeling assays in analytical chemistry, and to further facilitate and improve numerical evaluations, we develop analytical expressions for the key elements of Bayesian inference for this model. The approach is illustrated with both simulated and real data and is shown to have appealing properties in comparison with both standard frequentist and Bayesian approaches

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Rupture of vulnerable atheromatous plaque in the carotid and coronary arteries often leads to stroke and heart attack respectively. The mechanism of blood flow and plaque rupture in stenotic arteries is still not fully understood. A three dimensional rigid wall model was solved under steady state conditions and unsteady conditions by assuming a time-varying inlet velocity profile to investigate the relative importance of axial forces and pressure drops in arteries with asymmetric stenosis. Flow-structure interactions were investigated for the same geometry and the results were compared with those retrieved with the corresponding 2D cross-section structural models. The Navier-Stokes equations were used as the governing equations for the fluid. The tube wall was assumed hyperelastic, homogeneous, isotropic and incompressible. The analysis showed that the three dimensional behavior of velocity, pressure and wall shear stress is in general very different from that predicted by cross-section models. Pressure drop across the stenosis was found to be much higher than shear stress. Therefore, pressure may be the more important mechanical trigger for plaque rupture other than shear stress, although shear stress is closely related to plaque formation and progression.