Nova técnica para obtenção de fraturas com altíssima condutividade em poços de petróleo

Increase hydrocarbons production is the main goal of the oilwell industry worldwide. Hydraulic fracturing is often applied to achieve this goal due to a combination of attractive aspects including easiness and low operational costs associated with fast and highly economical response. Conventional fracturing usually involves high-flowing high-pressure pumping of a viscous fluid responsible for opening the fracture in the hydrocarbon producing rock. The thickness of the fracture should be enough to assure the penetration of the particles of a solid proppant into the rock. The proppant is driven into the target formation by a carrier fluid. After pumping, all fluids are filtered through the faces of the fracture and penetrate the rock. The proppant remains in the fracture holding it open and assuring high hydraulic conductivity. The present study proposes a different approach for hydraulic fracturing. Fractures with infinity conductivity are formed and used to further improve the production of highly permeable formations as well as to produce long fractures in naturally fractured formations. Naturally open fractures with infinite conductivity are usually encountered. They can be observed in rock outcrops and core plugs, or noticed by the total loss of circulation during drilling (even with low density fluids), image profiles, pumping tests (Mini-Frac and Mini Fall Off), and injection tests below fracturing pressure, whose flow is higher than expected for radial Darcian ones. Naturally occurring fractures are kept open by randomly shaped and placed supporting points, able to hold the faces of the fracture separate even under typical closing pressures. The approach presented herein generates infinite conductivity canal held open by artificially created parallel supporting areas positioned both horizontally and vertically. The size of these areas is designed to hold the permeable zones open supported by the impermeable areas. The England & Green equation was used to theoretically prove that the fracture can be held open by such artificially created set of horizontal parallel supporting areas. To assess the benefits of fractures characterized by infinite conductivity, an overall comparison with finite conductivity fractures was carried out using a series of parameters including fracture pressure loss and dimensionless conductivity as a function of flow production, FOI folds of increase, flow production and cumulative production as a function of time, and finally plots of net present value and productivity index

Dispersões sólidas de sinvastatina: preparação, caracterização, no estado sólido utilizando técnicas emergentes e estudo de estabilidade

This thesis aimed to assess the increase in solubility of simvastatin (SINV) with solid dispersions using techniques such as kneading (MA), co-solvent evaporation (ES), melting carrier (FC) and spray dryer (SD). Soluplus (SOL), PEG 6000 (PEG), PVP K-30 (PVP) e sodium lauryl sulphate (LSS) were used as carriers. The solid dispersions containing PEG [PEG-2(SD)], Soluplus [SOL-2(MA)] and sodium lauryl sulphate [LSS-2(ES)] were presented with a greater increase in solubility (5.02, 5.60 and 5.43 times respectively); analyses by ANOVA between the three groups did not present significant difference (p<0.05). In the phase solubility study, the calculation of the Gibbs free energy (ΔG) revealed that the spontaneity of solubilisation of SINV occurred in the order SOL>PEG >PVP 75%>LSS, always 80%. The phase diagrams of PEG and LSS presented solubilization stoichiometry of type 1:1 (type AL). The diagrams with PVP and SOL tend to 1:2 stoichiometry (type AL + AP). The stability coefficients (Ks) of the phase diagrams revealed that the most stable reactions occurred with LSS and PVP. The solid dispersions were characterized by Fourier transform infrared (FTIR), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), particle size distribution (PSD), near-infrared spectroscopy imaging (NIR-CI) and X-ray diffraction of the powder using the Topas software (PDRX-TOPAS). The solid dispersion PEG-2(SD) presented the greatest homogeneity and the lowest degree of crystallinity (18.2%). The accelerated stability study revealed that the solid dispersions are less stable than SINV, with PEG-2(SD) being the least stable, confirmed by FTIR and DSC. The analyses by PDRX-TOPAS revealed the amorphous character of the dispersions and the mechanism of increasing solubility

Diagnóstico para implantação do sistema de gestão ambiental em postos revendedores de combustíveis no município de Paranamirim RN: um estudo de caso

natural resources that still enjoy, in the certainty that if we do not, could culminate at the end of that remains. The environmental contamination by fuels in the retail service of oil and biofuels, has been a subject of growing research in Brazil, due to the large pollution potential of this activity. The aim of this study was to evaluate the importance of implementing the Environmental Management System (EMS) in fuel retail service stations in the city of Parnamirim-RN, but also describe the current situation the same as licensing and environmental characterization; identify existing barriers to implementation of EMS on the costs, technologies, knowledge, vision, present the potential benefits for the implementation of the EMS (social, economic and environmental), to identify the existence of plans for future action to implement the EMS , as a subsidy to promote the implementation of it. The methodology was developed through analysis of documents provided by the environmental agency responsible for licensing of retail service stations and fuel pala ANP. For data collection, we used the questionnaire was applied directly to managers or managers of sub-stations. Data were collected in 12 of 30 posts in the municipality. For purposes of data treatment was performed a descriptive analysis with respect to the opinion of twelve managers (respondents). The data acquired, according to the Likert scale were tabulated and analyzed using software SPSS 17.0 and Excel 2003, it was generated tables and graphs to observe the behavior of the data. The results showed that most respondents have a schooling level higher (58.3%) of the jobs surveyed 50% work on average 6 to 10 years and 41.6% are in operation for over 11 years , 75.0% do not have a license to operate and 12 stations, 58.3% were sued for not having a license to operate and are therefore in full commercial activity, 83% of jobs have some practice environmentally responsible, 75% agree in making planning future action to implement 8 the EMS in their ventures, 70% in full agreement that the high cost is a form of impediment to implementation of EMS; 66.67% agreed that resistance to change is an impediment to implementation of EMS; 90.91% agreed that the implementation of EMS is very complex, 80% of respondents agreed in a very significant environmental legislation is also a key factor preventing the implementation of EMS is noteworthy that 100% of respondents agreed that the knowledge about the use of the EMS will help to solve environmental problems in the fuel retail service stations, the implementation of the EMS will benefit with increased efficiency of resources applied to the findings by the agreement of 91.66% of respondents, where only 8, 33% disagreed, there was also a percentage of 100%, agreed that the company's image will be a great benefit, but also a contribution to solving environmental problems in the fuel retail service stations. Thus, the importance of the implementation of EMS in the fuel retail service stations in the city of Parnamirim-RN, with an urgent need to be deployed. And the bodies responsible for policy on state-run and supervise more tightly and action, this type of activity, in order to regulate the sustainable functioning of retail service stations of fuel, thus promoting a better quality of life for the population of the municipality of natal-RN

Produção pesqueira artesanal: diagnóstico ergonômico e bases para um planejamento nutricional situado e a promoção da saúde dos jangadeiros

The traditional fishing with rafts is characterized by unpredictability, high stakes and inadequate work conditions. The extensive working hours, physical wear, inadequate nutrition, unsanitary conditions, lack of salvage equipment and instruments suitable working, added by the presence of changes in the nutritional status of fisherman, that contribute to the picture of insecurity in high seas, injuries and health. This study aimed to analyze the activity of the fisherman s from Ponta Negra, Natal / RN, and check the conditions of supply of these fishermen and their implications on health and development of their work. To this finality, was used a methodology based on the ergonomic work analysis employing techniques such as observational and interactional conversational action, listening to the answers, observation protocols, photographic and video records. The script conversational dynamic action was developed from literature searches about the artisanal fisheries, culture and food habits of this population, and analyzes the overall situation of focus and two reference situations. To collect data on the usual diet of fisherman as well as quantitative and qualitative analysis that was used for data analysis and 24h recall the Food Frequency Questionnaire (FFQ). The impact of this power to the health of fisherman was evaluated performing a nutritional assessment. The results revealed that the fishermen carry out their activities with poor working conditions, health and nutrition. Feeding practices of these fishermen undertake development work, making it even more stressful, as well contributing to the emergence of Chronic Noncommunicable Diseases. The management of the activity, as well as the current structure of the vessel, also contributes to the adoption of inappropriate feeding practices during the shipment of catch. The results of this indicate the need for adequate interventions in order to assist in recovery and / or maintenance of health of fisherman minimizing reflections of nutritional disorders for the development activity by improving the quality of life in this population

Análise e classificação de imagens de lesões da pele por atributos de cor, forma e textura utilizando máquina de vetor de suporte

The skin cancer is the most common of all cancers and the increase of its incidence must, in part, caused by the behavior of the people in relation to the exposition to the sun. In Brazil, the non-melanoma skin cancer is the most incident in the majority of the regions. The dermatoscopy and videodermatoscopy are the main types of examinations for the diagnosis of dermatological illnesses of the skin. The field that involves the use of computational tools to help or follow medical diagnosis in dermatological injuries is seen as very recent. Some methods had been proposed for automatic classification of pathology of the skin using images. The present work has the objective to present a new intelligent methodology for analysis and classification of skin cancer images, based on the techniques of digital processing of images for extraction of color characteristics, forms and texture, using Wavelet Packet Transform (WPT) and learning techniques called Support Vector Machine (SVM). The Wavelet Packet Transform is applied for extraction of texture characteristics in the images. The WPT consists of a set of base functions that represents the image in different bands of frequency, each one with distinct resolutions corresponding to each scale. Moreover, the characteristics of color of the injury are also computed that are dependants of a visual context, influenced for the existing colors in its surround, and the attributes of form through the Fourier describers. The Support Vector Machine is used for the classification task, which is based on the minimization principles of the structural risk, coming from the statistical learning theory. The SVM has the objective to construct optimum hyperplanes that represent the separation between classes. The generated hyperplane is determined by a subset of the classes, called support vectors. For the used database in this work, the results had revealed a good performance getting a global rightness of 92,73% for melanoma, and 86% for non-melanoma and benign injuries. The extracted describers and the SVM classifier became a method capable to recognize and to classify the analyzed skin injuries

Sistema inteligente para diagnóstico de patologias na laringe utilizando máquinas de vetor de suporte

The human voice is an important communication tool and any disorder of the voice can have profound implications for social and professional life of an individual. Techniques of digital signal processing have been used by acoustic analysis of vocal disorders caused by pathologies in the larynx, due to its simplicity and noninvasive nature. This work deals with the acoustic analysis of voice signals affected by pathologies in the larynx, specifically, edema, and nodules on the vocal folds. The purpose of this work is to develop a classification system of voices to help pre-diagnosis of pathologies in the larynx, as well as monitoring pharmacological treatments and after surgery. Linear Prediction Coefficients (LPC), Mel Frequency cepstral coefficients (MFCC) and the coefficients obtained through the Wavelet Packet Transform (WPT) are applied to extract relevant characteristics of the voice signal. For the classification task is used the Support Vector Machine (SVM), which aims to build optimal hyperplanes that maximize the margin of separation between the classes involved. The hyperplane generated is determined by the support vectors, which are subsets of points in these classes. According to the database used in this work, the results showed a good performance, with a hit rate of 98.46% for classification of normal and pathological voices in general, and 98.75% in the classification of diseases together: edema and nodules

Método Fuzzy para auxílio ao diagnóstico de câncer de mama em ambiente inteligente de telediagnóstico colaborativo para apoio à tomada de decisão

Breast cancer, despite being one of the leading causes of death among women worldwide is a disease that can be cured if diagnosed early. One of the main techniques used in the detection of breast cancer is the Fine Needle Aspirate FNA (aspiration puncture by thin needle) which, depending on the clinical case, requires the analysis of several medical specialists for the diagnosis development. However, such diagnosis and second opinions have been hampered by geographical dispersion of physicians and/or the difficulty in reconciling time to undertake work together. Within this reality, this PhD thesis uses computational intelligence in medical decision-making support for remote diagnosis. For that purpose, it presents a fuzzy method to assist the diagnosis of breast cancer, able to process and sort data extracted from breast tissue obtained by FNA. This method is integrated into a virtual environment for collaborative remote diagnosis, whose model was developed providing for the incorporation of prerequisite Modules for Pre Diagnosis to support medical decision. On the fuzzy Method Development, the process of knowledge acquisition was carried out by extraction and analysis of numerical data in gold standard data base and by interviews and discussions with medical experts. The method has been tested and validated with real cases and, according to the sensitivity and specificity achieved (correct diagnosis of tumors, malignant and benign respectively), the results obtained were satisfactory, considering the opinions of doctors and the quality standards for diagnosis of breast cancer and comparing them with other studies involving breast cancer diagnosis by FNA.

Sistema híbrido para detecção e diagnóstico de falhas em sistemas dinâmicos

The industries are getting more and more rigorous, when security is in question, no matter is to avoid financial damages due to accidents and low productivity, or when it s related to the environment protection. It was thinking about great world accidents around the world involving aircrafts and industrial process (nuclear, petrochemical and so on) that we decided to invest in systems that could detect fault and diagnosis (FDD) them. The FDD systems can avoid eventual fault helping man on the maintenance and exchange of defective equipments. Nowadays, the issues that involve detection, isolation, diagnose and the controlling of tolerance fault are gathering strength in the academic and industrial environment. It is based on this fact, in this work, we discuss the importance of techniques that can assist in the development of systems for Fault Detection and Diagnosis (FDD) and propose a hybrid method for FDD in dynamic systems. We present a brief history to contextualize the techniques used in working environments. The detection of fault in the proposed system is based on state observers in conjunction with other statistical techniques. The principal idea is to use the observer himself, in addition to serving as an analytical redundancy, in allowing the creation of a residue. This residue is used in FDD. A signature database assists in the identification of system faults, which based on the signatures derived from trend analysis of the residue signal and its difference, performs the classification of the faults based purely on a decision tree. This FDD system is tested and validated in two plants: a simulated plant with coupled tanks and didactic plant with industrial instrumentation. All collected results of those tests will be discussed

Técnicas de computação natural para segmentação de imagens médicas

Image segmentation is one of the image processing problems that deserves special attention from the scientific community. This work studies unsupervised methods to clustering and pattern recognition applicable to medical image segmentation. Natural Computing based methods have shown very attractive in such tasks and are studied here as a way to verify it's applicability in medical image segmentation. This work treats to implement the following methods: GKA (Genetic K-means Algorithm), GFCMA (Genetic FCM Algorithm), PSOKA (PSO and K-means based Clustering Algorithm) and PSOFCM (PSO and FCM based Clustering Algorithm). Besides, as a way to evaluate the results given by the algorithms, clustering validity indexes are used as quantitative measure. Visual and qualitative evaluations are realized also, mainly using data given by the BrainWeb brain simulator as ground truth

Aplicação de sistemas multi-classificadores no diagnóstico de falhas em motores de indução trifásicos

Equipment maintenance is the major cost factor in industrial plants, it is very important the development of fault predict techniques. Three-phase induction motors are key electrical equipments used in industrial applications mainly because presents low cost and large robustness, however, it isn t protected from other fault types such as shorted winding and broken bars. Several acquisition ways, processing and signal analysis are applied to improve its diagnosis. More efficient techniques use current sensors and its signature analysis. In this dissertation, starting of these sensors, it is to make signal analysis through Park s vector that provides a good visualization capability. Faults data acquisition is an arduous task; in this way, it is developed a methodology for data base construction. Park s transformer is applied into stationary reference for machine modeling of the machine s differential equations solution. Faults detection needs a detailed analysis of variables and its influences that becomes the diagnosis more complex. The tasks of pattern recognition allow that systems are automatically generated, based in patterns and data concepts, in the majority cases undetectable for specialists, helping decision tasks. Classifiers algorithms with diverse learning paradigms: k-Neighborhood, Neural Networks, Decision Trees and Naïves Bayes are used to patterns recognition of machines faults. Multi-classifier systems are used to improve classification errors. It inspected the algorithms homogeneous: Bagging and Boosting and heterogeneous: Vote, Stacking and Stacking C. Results present the effectiveness of constructed model to faults modeling, such as the possibility of using multi-classifiers algorithm on faults classification

Um método para localização facial Invariante a rotação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Um estudo do aumento da capacidade de sistemas 3g WCDMA usando técnicas 3.5G de expansão do enlace reverso

The introduction of new digital services in the cellular networks, in transmission rates each time more raised, has stimulated recent research that comes studying ways to increase the data communication capacity and to reduce the delays in forward and reverse links of third generation WCDMA systems. These studies have resulted in new standards, known as 3.5G, published by 3GPP group, for the evolution of the third generation of the cellular systems. In this Masters Thesis the performance of a 3G WCDMA system, with diverse base stations and thousand of users is developed with assists of the planning tool NPSW. Moreover the performance of the 3.5G techniques hybrid automatic retransmission and multi-user detection with interference cancellation, candidates for enhance the WCDMA uplink capacity, is verified by means of computational simulations in Matlab of the increase of the data communication capacity and the reduction of the delays in the retransmission of packages of information

Localização de um robô móvel usando odometria e marcos naturais

Several methods of mobile robot navigation request the mensuration of robot position and orientation in its workspace. In the wheeled mobile robot case, techniques based on odometry allow to determine the robot localization by the integration of incremental displacements of its wheels. However, this technique is subject to errors that accumulate with the distance traveled by the robot, making unfeasible its exclusive use. Other methods are based on the detection of natural or artificial landmarks present in the environment and whose location is known. This technique doesnt generate cumulative errors, but it can request a larger processing time than the methods based on odometry. Thus, many methods make use of both techniques, in such a way that the odometry errors are periodically corrected through mensurations obtained from landmarks. Accordding to this approach, this work proposes a hybrid localization system for wheeled mobile robots in indoor environments based on odometry and natural landmarks. The landmarks are straight lines de.ned by the junctions in environments floor, forming a bi-dimensional grid. The landmark detection from digital images is perfomed through the Hough transform. Heuristics are associated with that transform to allow its application in real time. To reduce the search time of landmarks, we propose to map odometry errors in an area of the captured image that possesses high probability of containing the sought mark

Escalabilidade Paralela de um Algoritmo de Migração Reversa no Tempo (RTM) Pré-empilhamento

The seismic method is of extreme importance in geophysics. Mainly associated with oil exploration, this line of research focuses most of all investment in this area. The acquisition, processing and interpretation of seismic data are the parts that instantiate a seismic study. Seismic processing in particular is focused on the imaging that represents the geological structures in subsurface. Seismic processing has evolved significantly in recent decades due to the demands of the oil industry, and also due to the technological advances of hardware that achieved higher storage and digital information processing capabilities, which enabled the development of more sophisticated processing algorithms such as the ones that use of parallel architectures. One of the most important steps in seismic processing is imaging. Migration of seismic data is one of the techniques used for imaging, with the goal of obtaining a seismic section image that represents the geological structures the most accurately and faithfully as possible. The result of migration is a 2D or 3D image which it is possible to identify faults and salt domes among other structures of interest, such as potential hydrocarbon reservoirs. However, a migration fulfilled with quality and accuracy may be a long time consuming process, due to the mathematical algorithm heuristics and the extensive amount of data inputs and outputs involved in this process, which may take days, weeks and even months of uninterrupted execution on the supercomputers, representing large computational and financial costs, that could derail the implementation of these methods. Aiming at performance improvement, this work conducted the core parallelization of a Reverse Time Migration (RTM) algorithm, using the parallel programming model Open Multi-Processing (OpenMP), due to the large computational effort required by this migration technique. Furthermore, analyzes such as speedup, efficiency were performed, and ultimately, the identification of the algorithmic scalability degree with respect to the technological advancement expected by future processors

Compressão Seletiva de Imagens Coloridas com Detecção Automática de Regiões de Interesse

There has been an increasing tendency on the use of selective image compression, since several applications make use of digital images and the loss of information in certain regions is not allowed in some cases. However, there are applications in which these images are captured and stored automatically making it impossible to the user to select the regions of interest to be compressed in a lossless manner. A possible solution for this matter would be the automatic selection of these regions, a very difficult problem to solve in general cases. Nevertheless, it is possible to use intelligent techniques to detect these regions in specific cases. This work proposes a selective color image compression method in which regions of interest, previously chosen, are compressed in a lossless manner. This method uses the wavelet transform to decorrelate the pixels of the image, competitive neural network to make a vectorial quantization, mathematical morphology, and Huffman adaptive coding. There are two options for automatic detection in addition to the manual one: a method of texture segmentation, in which the highest frequency texture is selected to be the region of interest, and a new face detection method where the region of the face will be lossless compressed. The results show that both can be successfully used with the compression method, giving the map of the region of interest as an input