Estudo de sistemas multicomponentes no processo de injeção cíclica de vapor

In Brazilian Northeast there are reservoirs with heavy oil, which use steam flooding as a recovery method. This process allows to reduce oil viscosity, increasing its mobility and consequently its oil recovery. Steam injection is a thermal method and can occurs in continues or cyclic form. Cyclic steam stimulation (CSS) can be repeated several times. Each cycle consisting of three stages: steam injection, soaking time and production phase. CSS becomes less efficient with an increase of number of cycles. Thus, this work aims to study the influence of compositional models in cyclic steam injection and the effects of some parameters, such like: flow injection, steam quality and temperature of steam injected, analyzing the influence of pseudocomponents numbers on oil rate, cumulative oil, oil recovery and simulation time. In the situations analyzed was compared the model of fluid of three phases and three components known as Blackoil . Simulations were done using commercial software (CMG), it was analyzed a homogeneous reservoir with characteristics similar to those found in Brazilian Northeast. It was observed that an increase of components number, increase the time spent in simulation. As for analyzed parameters, it appears that the steam rate, and steam quality has influence on cumulative oil and oil recovery. The number of components did not a lot influenced on oil recovery, however it has influenced on gas production

Estudo de modelos composicionais de óleo na injeção contínua de vapor

The objective of the thermal recovery is to heat the resevoir and the oil in it to increase its recovery. In the Potiguar river basin there are located several heavy oil reservoirs whose primary recovery energy provides us with a little oil flow, which makes these reservoirs great candidates for application of a method of recovery advanced of the oil, especially the thermal. The steam injection can occur on a cyclical or continuous manner. The continuous steam injection occurs through injection wells, which in its vicinity form a zone of steam that expands itself, having as a consequence the displace of the oil with viscosity and mobility improved towards the producing wells. Another possible mechanism of displacement of oil in reservoirs subjected to continuous injection of steam is the distillation of oil by steam, which at high temperatures; their lighter fractions can be vaporized by changing the composition of the oil produced, of the oil residual or to shatter in the amount of oil produced. In this context, this paper aims to study the influence of compositional models in the continuous injection of steam through in the analysis of some parameters such as flow injection steam and temperature of injection. Were made various leading comparative analysis taking the various models of fluid, varying from a good elementary, with 03 pseudocomponents to a modeling of fluids with increasing numbers of pseudocomponents. A commercial numerical simulator was used for the study from a homogeneous reservoir model with similar features to those found in northeastern Brazil. Some conclusions as the increasing of the simulation time with increasing number of pseudocomponents, the significant influence of flow injection on cumulative production of oil and little influence of the number of pseudocomponents in the flows and cumulative production of oil were found

Chiquinha Gonzaga e o Maxixe

Pós-graduação em Música - IA

Resgates e abandonos do passado na prática musical litúrgica católica no Brasil entre os pontificados de Pio X e Bento XVI (1903-2013)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

String Quartet n degrees 02 by Villa-Lobos: a dialogue with the cyclic form of Franck, Debussy and Ravel

This article investigates Villa-Lobos's String Quartet n degrees 02, an early work by this composer, written according cyclic sonata principles, as developed by Cesar Franck and systematized by Vincent d'Indy. Another important source are the string quartets composed by Franck (1889), Debussy (1893) and Ravel (1903), which possibly served as compositional models to Villa-Lobos. In this light, the themes of the Exposition in the first movement were analyzed and this procedure reveals some harmonic and rhythmic aspects throughout all the other movements.

Type Systems for Distributed Programs: Components and Sessions

Modern software systems, in particular distributed ones, are everywhere around us and are at the basis of our everyday activities. Hence, guaranteeing their cor- rectness, consistency and safety is of paramount importance. Their complexity makes the verification of such properties a very challenging task. It is natural to expect that these systems are reliable and above all usable. i) In order to be reliable, compositional models of software systems need to account for consistent dynamic reconfiguration, i.e., changing at runtime the communication patterns of a program. ii) In order to be useful, compositional models of software systems need to account for interaction, which can be seen as communication patterns among components which collaborate together to achieve a common task. The aim of the Ph.D. was to develop powerful techniques based on formal methods for the verification of correctness, consistency and safety properties related to dynamic reconfiguration and communication in complex distributed systems. In particular, static analysis techniques based on types and type systems appeared to be an adequate methodology, considering their success in guaranteeing not only basic safety properties, but also more sophisticated ones like, deadlock or livelock freedom in a concurrent setting. The main contributions of this dissertation are twofold. i) On the components side: we design types and a type system for a concurrent object-oriented calculus to statically ensure consistency of dynamic reconfigurations related to modifications of communication patterns in a program during execution time. ii) On the communication side: we study advanced safety properties related to communication in complex distributed systems like deadlock-freedom, livelock- freedom and progress. Most importantly, we exploit an encoding of types and terms of a typical distributed language, session π-calculus, into the standard typed π- calculus, in order to understand their expressive power.

Estudo de sistemas multicomponentes no processo de injeção cíclica de vapor

In Brazilian Northeast there are reservoirs with heavy oil, which use steam flooding as a recovery method. This process allows to reduce oil viscosity, increasing its mobility and consequently its oil recovery. Steam injection is a thermal method and can occurs in continues or cyclic form. Cyclic steam stimulation (CSS) can be repeated several times. Each cycle consisting of three stages: steam injection, soaking time and production phase. CSS becomes less efficient with an increase of number of cycles. Thus, this work aims to study the influence of compositional models in cyclic steam injection and the effects of some parameters, such like: flow injection, steam quality and temperature of steam injected, analyzing the influence of pseudocomponents numbers on oil rate, cumulative oil, oil recovery and simulation time. In the situations analyzed was compared the model of fluid of three phases and three components known as Blackoil . Simulations were done using commercial software (CMG), it was analyzed a homogeneous reservoir with characteristics similar to those found in Brazilian Northeast. It was observed that an increase of components number, increase the time spent in simulation. As for analyzed parameters, it appears that the steam rate, and steam quality has influence on cumulative oil and oil recovery. The number of components did not a lot influenced on oil recovery, however it has influenced on gas production

Estudo de modelos composicionais de óleo na injeção contínua de vapor

The objective of the thermal recovery is to heat the resevoir and the oil in it to increase its recovery. In the Potiguar river basin there are located several heavy oil reservoirs whose primary recovery energy provides us with a little oil flow, which makes these reservoirs great candidates for application of a method of recovery advanced of the oil, especially the thermal. The steam injection can occur on a cyclical or continuous manner. The continuous steam injection occurs through injection wells, which in its vicinity form a zone of steam that expands itself, having as a consequence the displace of the oil with viscosity and mobility improved towards the producing wells. Another possible mechanism of displacement of oil in reservoirs subjected to continuous injection of steam is the distillation of oil by steam, which at high temperatures; their lighter fractions can be vaporized by changing the composition of the oil produced, of the oil residual or to shatter in the amount of oil produced. In this context, this paper aims to study the influence of compositional models in the continuous injection of steam through in the analysis of some parameters such as flow injection steam and temperature of injection. Were made various leading comparative analysis taking the various models of fluid, varying from a good elementary, with 03 pseudocomponents to a modeling of fluids with increasing numbers of pseudocomponents. A commercial numerical simulator was used for the study from a homogeneous reservoir model with similar features to those found in northeastern Brazil. Some conclusions as the increasing of the simulation time with increasing number of pseudocomponents, the significant influence of flow injection on cumulative production of oil and little influence of the number of pseudocomponents in the flows and cumulative production of oil were found

Logic-based schedulability analysis for compositional hard real-time embedded systems

Over the past decades several approaches for schedulability analysis have been proposed for both uni-processor and multi-processor real-time systems. Although different techniques are employed, very little has been put forward in using formal specifications, with the consequent possibility for mis-interpretations or ambiguities in the problem statement. Using a logic based approach to schedulability analysis in the design of hard real-time systems eases the synthesis of correct-by-construction procedures for both static and dynamic verification processes. In this paper we propose a novel approach to schedulability analysis based on a timed temporal logic with time durations. Our approach subsumes classical methods for uni-processor scheduling analysis over compositional resource models by providing the developer with counter-examples, and by ruling out schedules that cause unsafe violations on the system. We also provide an example showing the effectiveness of our proposal.

Using self organizing maps on compositional data

Self-organizing maps (Kohonen 1997) is a type of artificial neural network developedto explore patterns in high-dimensional multivariate data. The conventional versionof the algorithm involves the use of Euclidean metric in the process of adaptation ofthe model vectors, thus rendering in theory a whole methodology incompatible withnon-Euclidean geometries.In this contribution we explore the two main aspects of the problem:1. Whether the conventional approach using Euclidean metric can shed valid resultswith compositional data.2. If a modification of the conventional approach replacing vectorial sum and scalarmultiplication by the canonical operators in the simplex (i.e. perturbation andpowering) can converge to an adequate solution.Preliminary tests showed that both methodologies can be used on compositional data.However, the modified version of the algorithm performs poorer than the conventionalversion, in particular, when the data is pathological. Moreover, the conventional ap-proach converges faster to a solution, when data is \well-behaved".Key words: Self Organizing Map; Artificial Neural networks; Compositional data

Modelling structural zeros in compositional data

This analysis was stimulated by the real data analysis problem of householdexpenditure data. The full dataset contains expenditure data for a sample of 1224 households. The expenditure is broken down at 2 hierarchical levels: 9 major levels (e.g. housing, food, utilities etc.) and 92 minor levels. There are also 5 factors and 5 covariates at the household level. Not surprisingly, there are a small number of zeros at the major level, but many zeros at the minor level. The question is how best to model the zeros. Clearly, models that tryto add a small amount to the zero terms are not appropriate in general as at least some of the zeros are clearly structural, e.g. alcohol/tobacco for households that are teetotal. The key question then is how to build suitable conditional models. For example, is the sub-composition of spendingexcluding alcohol/tobacco similar for teetotal and non-teetotal households?In other words, we are looking for sub-compositional independence. Also, what determines whether a household is teetotal? Can we assume that it is independent of the composition? In general, whether teetotal will clearly depend on the household level variables, so we need to be able to model this dependence. The other tricky question is that with zeros on more than onecomponent, we need to be able to model dependence and independence of zeros on the different components. Lastly, while some zeros are structural, others may not be, for example, for expenditure on durables, it may be chance as to whether a particular household spends money on durableswithin the sample period. This would clearly be distinguishable if we had longitudinal data, but may still be distinguishable by looking at the distribution, on the assumption that random zeros will usually be for situations where any non-zero expenditure is not small.While this analysis is based on around economic data, the ideas carry over tomany other situations, including geological data, where minerals may be missing for structural reasons (similar to alcohol), or missing because they occur only in random regions which may be missed in a sample (similar to the durables)

Multivariate ARIMA Compositional Time Series Analysis

A compositional time series is obtained when a compositional data vector is observed atdifferent points in time. Inherently, then, a compositional time series is a multivariatetime series with important constraints on the variables observed at any instance in time.Although this type of data frequently occurs in situations of real practical interest, atrawl through the statistical literature reveals that research in the field is very much in itsinfancy and that many theoretical and empirical issues still remain to be addressed. Anyappropriate statistical methodology for the analysis of compositional time series musttake into account the constraints which are not allowed for by the usual statisticaltechniques available for analysing multivariate time series. One general approach toanalyzing compositional time series consists in the application of an initial transform tobreak the positive and unit sum constraints, followed by the analysis of the transformedtime series using multivariate ARIMA models. In this paper we discuss the use of theadditive log-ratio, centred log-ratio and isometric log-ratio transforms. We also presentresults from an empirical study designed to explore how the selection of the initialtransform affects subsequent multivariate ARIMA modelling as well as the quality ofthe forecasts

Compositional analysis of bivariate discrete probabilities

A joint distribution of two discrete random variables with finite support can be displayed as a two way table of probabilities adding to one. Assume that this table hasn rows and m columns and all probabilities are non-null. This kind of table can beseen as an element in the simplex of n · m parts. In this context, the marginals areidentified as compositional amalgams, conditionals (rows or columns) as subcompositions. Also, simplicial perturbation appears as Bayes theorem. However, the Euclideanelements of the Aitchison geometry of the simplex can also be translated into the tableof probabilities: subspaces, orthogonal projections, distances.Two important questions are addressed: a) given a table of probabilities, which isthe nearest independent table to the initial one? b) which is the largest orthogonalprojection of a row onto a column? or, equivalently, which is the information in arow explained by a column, thus explaining the interaction? To answer these questionsthree orthogonal decompositions are presented: (1) by columns and a row-wise geometric marginal, (2) by rows and a columnwise geometric marginal, (3) by independenttwo-way tables and fully dependent tables representing row-column interaction. Animportant result is that the nearest independent table is the product of the two (rowand column)-wise geometric marginal tables. A corollary is that, in an independenttable, the geometric marginals conform with the traditional (arithmetic) marginals.These decompositions can be compared with standard log-linear models.Key words: balance, compositional data, simplex, Aitchison geometry, composition,orthonormal basis, arithmetic and geometric marginals, amalgam, dependence measure,contingency table

Compositional Time Series: An Application

The composition of the labour force is an important economic factor for a country.Often the changes in proportions of different groups are of interest.I this paper we study a monthly compositional time series from the Swedish LabourForce Survey from 1994 to 2005. Three models are studied: the ILR-transformed series,the ILR-transformation of the compositional differenced series of order 1, and the ILRtransformationof the compositional differenced series of order 12. For each of thethree models a VAR-model is fitted based on the data 1994-2003. We predict the timeseries 15 steps ahead and calculate 95 % prediction regions. The predictions of thethree models are compared with actual values using MAD and MSE and the predictionregions are compared graphically in a ternary time series plot.We conclude that the first, and simplest, model possesses the best predictive power ofthe three models

Compositional evolution with mass transfer in closed systems

Evolution of compositions in time, space, temperature or other covariates is frequentin practice. For instance, the radioactive decomposition of a sample changes its composition with time. Some of the involved isotopes decompose into other isotopes of thesample, thus producing a transfer of mass from some components to other ones, butpreserving the total mass present in the system. This evolution is traditionally modelledas a system of ordinary di erential equations of the mass of each component. However,this kind of evolution can be decomposed into a compositional change, expressed interms of simplicial derivatives, and a mass evolution (constant in this example). A rst result is that the simplicial system of di erential equations is non-linear, despiteof some subcompositions behaving linearly.The goal is to study the characteristics of such simplicial systems of di erential equa-tions such as linearity and stability. This is performed extracting the compositional differential equations from the mass equations. Then, simplicial derivatives are expressedin coordinates of the simplex, thus reducing the problem to the standard theory ofsystems of di erential equations, including stability. The characterisation of stabilityof these non-linear systems relays on the linearisation of the system of di erential equations at the stationary point, if any. The eigenvelues of the linearised matrix and theassociated behaviour of the orbits are the main tools. For a three component system,these orbits can be plotted both in coordinates of the simplex or in a ternary diagram.A characterisation of processes with transfer of mass in closed systems in terms of stability is thus concluded. Two examples are presented for illustration, one of them is aradioactive decay