De gata borralheira a Cinderela :nova espacialidade decorrente do desenvolvimento turístico, diferenciada pelo estilo de vida em Ponta Negra, Natal, RN

The transformations economical, social and politics in you finish them decades of the century XX brought changes that didn't just limit to the production system. The flexible accumulation took many workers lost her/it their workstations and they look for her/it new survival forms, migrating for administrative activities, of services rendered and for the tourist activity of small and medium load. The State has been investing in the implantation of plans of tourist development in order to create favorable conditions for the reproduction of the tourist activity in Brazil, mainly in the Northeast. A space when it starts to present a predominant economical activity suffers a restructuring in their social and economical relationships. The restructuring of these relationships takes to the construction of a new espacialidade. In the city of Christmas, in Rio Grande do Norte, the neighborhood of Black Tip is the most representative of the public investments for the tourist development. After intense process of tourist urbanization, Black Tip passed interfering in the global context consolidating as the tourist locus in the city. The tourist urbanization of the neighborhood took to the transformation of the space in merchandise that is sold and consumed as such. The recreation of fragments of other cultures brought by social actors, resulting from migratory processes stimulated by the tourist development, it has been presenting ruled social relationships in the informational technology, consumption of global goods and in the fragmentation of the urban space characterized by the internationalization and cosmopolitização. That process has been masking the inequalities partners and cultural as well as the territorial appropriation for an economical elite. The spaces are being appropriate for investors of the tourist section, private investors, agents and real estate producers, where the inequality is not just economical, but also cultural. The local population, mainly of the urban fraction of the Town of Black Tip, it doesn't participate of the productive process in function of the little or any professional qualification and he/she doesn't also have access to the consumption process. To the native ones it remains the fight for the preservation of his/her cultural identity and for the survival

Desenvolvimento de um sistema Inteligente para a análise de cartas dinamométricas no método de elevação por bombeio mecânico

The artificial lifting of oil is needed when the pressure of the reservoir is not high enough so that the fluid contained in it can reach the surface spontaneously. Thus the increase in energy supplies artificial or additional fluid integral to the well to come to the surface. The rod pump is the artificial lift method most used in the world and the dynamometer card (surface and down-hole) is the best tool for the analysis of a well equipped with such method. A computational method using Artificial Neural Networks MLP was and developed using pre-established patterns, based on its geometry, the downhole card are used for training the network and then the network provides the knowledge for classification of new cards, allows the fails diagnose in the system and operation conditions of the lifting system. These routines could be integrated to a supervisory system that collects the cards to be analyzed

Processamento Inteligente de Sinais de Pressão e Temperatura Adquiridos Através de Sensores Permanentes em Poços de Petróleo

Originally aimed at operational objectives, the continuous measurement of well bottomhole pressure and temperature, recorded by permanent downhole gauges (PDG), finds vast applicability in reservoir management. It contributes for the monitoring of well performance and makes it possible to estimate reservoir parameters on the long term. However, notwithstanding its unquestionable value, data from PDG is characterized by a large noise content. Moreover, the presence of outliers within valid signal measurements seems to be a major problem as well. In this work, the initial treatment of PDG signals is addressed, based on curve smoothing, self-organizing maps and the discrete wavelet transform. Additionally, a system based on the coupling of fuzzy clustering with feed-forward neural networks is proposed for transient detection. The obtained results were considered quite satisfactory for offshore wells and matched real requisites for utilization

Sistema inteligente para apoio à decisão na operação de uma malha de escoamento de petróleo

The petroleum production pipeline networks are inherently complex, usually decentralized systems. Strict operational constraints are applied in order to prevent serious problems like environmental disasters or production losses. This paper describes an intelligent system to support decisions in the operation of these networks, proposing a staggering for the pumps of transfer stations that compose them. The intelligent system is formed by blocks which interconnect to process the information and generate the suggestions to the operator. The main block of the system uses fuzzy logic to provide a control based on rules, which incorporate knowledge from experts. Tests performed in the simulation environment provided good results, indicating the applicability of the system in a real oil production environment. The use of the stagger proposed by the system allows a prioritization of the transfer in the network and a flow programming

Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR

This Thesis presents the elaboration of a methodological propose for the development of an intelligent system, able to automatically achieve the effective porosity, in sedimentary layers, from a data bank built with information from the Ground Penetrating Radar GPR. The intelligent system was built to model the relation between the porosity (response variable) and the electromagnetic attribute from the GPR (explicative variables). Using it, the porosity was estimated using the artificial neural network (Multilayer Perceptron MLP) and the multiple linear regression. The data from the response variable and from the explicative variables were achieved in laboratory and in GPR surveys outlined in controlled sites, on site and in laboratory. The proposed intelligent system has the capacity of estimating the porosity from any available data bank, which has the same variables used in this Thesis. The architecture of the neural network used can be modified according to the existing necessity, adapting to the available data bank. The use of the multiple linear regression model allowed the identification and quantification of the influence (level of effect) from each explicative variable in the estimation of the porosity. The proposed methodology can revolutionize the use of the GPR, not only for the imaging of the sedimentary geometry and faces, but mainly for the automatically achievement of the porosity one of the most important parameters for the characterization of reservoir rocks (from petroleum or water)