Wilson da Mata

Determination of multiple direction of arrival in antennas arrays with radial basis functions

Abstract This work presents a new proposal for the direction of arrival detection for more than one signal arriving simultaneously on an antennas array of linear or planar geometry using intelligent algorithms. The direction of arrival (DOA) estimator is developed using the techniques of digital conventional beamforming, blind source separation (BSS) and the neural estimator modular structure of radial basis functions (MRBF). The developed MRBF has its capabilities extended due to the interaction with BSS technique, which makes an estimation of the steering vectors of the multiple plane waves that reach the array at the same frequency, that is, it separates mixed signals without a priori information.

Intelligent system for feature extraction of oil slick in SAR images: speckle filter analysis

The development of automatic techniques for oil slick identification on the sea surface, captured through remote sensing images, cause a positive impact to a complete monitoring of the oceans and seas. C-band SAR (ERS-1, ERS-2, Radarsat and Envisat projects) is well adapted to detect ocean pollution because the backscatter is reduced by oil slick. This work propose a system for segmentation and feature extraction of oil slicks candidates based on techniques of digital image processing (filters, gradients, mathematical morphology) and artificial neural network (ANN). Different algorithms of speckle filtering are tested and a comparison for the considered system is presented. The process is thought to possess a level of automatization that minimizes the intervention of a human operator, being possible the processing of larger amount data. The focus of the work is to present a study detailed for feature extraction block proposed (architecture used and computational tools).

Optimization of the Oil Production Fields Submitted the Water Injection, Using the Algorithm NSGA-II

This paper presents the implementation of a system based on genetic algorithm multiobjective optimizer NSGA-II (Non-Dominated Sorting Genetic Algorithm), which offers a decision support tool and automates the search for alternatives to the development of the oilfield submitted to water injection process. Each alternative refers to how an oil field, known and defined, is put into production, that is, with respect to the determination of number and the disposition of producers wells and injectors in the field. The implementation of the algorithm is to find the production settings, in the long run, which provide the highest net present value (VPL), obtained from the initial investment cost, the price of oil, oil production and operation costs paid during the production time, thus increasing the production of oil in the field, reducing operating costs and the time in the decision-making process.

Predição Não-Linear De Curvas De Produção De Petróleo Via Redes Neurais Recorrentes

Uma das atividades essenciais na engenharia de petroleo e a estimativa de producao de oleo existente nas reservas petroliferas. O calculo dessas reservas e crucial para a determinacao da viabilidade economica de sua explotacao. Atualmente, a industria do petroleo tem se deparado com problemas para analisar a producao enquanto facilidades operacionais disponibilizam um volume de informacoes que crescem exponencialmente. Tecnicas convencionais de modelagem de reservatorios como simulacao matematica e visualizacao estao bem desenvolvidas e disponiveis. A proposta deste trabalho e o uso de tecnicas inteligentes, como as redes neurais artificiais, para a predicao de producao de petroleo e comparar seus resultados com os obtidos pela simulacao numerica, metodo bastante utilizado na pratica para a realizacao de predicao do comportamento da producao de petroleo. As redes neurais artificiais serao usadas devido a sua capacidade de aprendizado, adaptacao e interpolacao

Identificação De Manchas De Óleo Na Superfície Marinha Através De Imagens De SAR: Classificador RBF

Oil spill on the sea, accidental or not, generates enormous negative consequences for the affected area. The development of automatic techniques for identification of oil spots on the sea surface, captured through Radar images, assist in a complete monitoring of the oceans and seas. However spots of different origins can be visualized in this type of imaging, which is a very difficult task. The system proposed in this work, based on techniques of digital image processing and artificial neural network, has the objective to identify the analyzed spot and to discern between oil and other generating phenomena of spot. The classifier algorithm (Radial Basis Function Network) is presented and comented. The final performance of the system is presented by ROC curve, and SP product. The true positive rates are considered agreed with the literature about oil slick detection through SAR images presents. Keywords— Oil spill, Oil slick, Neural Classifier, Intelligent Systems, SAR. Resumo— Derramamentos de óleo sobre o mar, mesmo que acidentais, geram enormes conseqüências negativas para a área afetada. O desenvolvimento de técnicas automáticas para a identificação de manchas de óleo sobre a superf́ıcie marinha, capturadas através de imagens de Radar, auxiliam num completo monitoramento dos oceanos e mares. Contudo, manchas de diferentes origens podem ser visualizadas nesse tipo de produção de imagem, tornando o monitoramento dif́ıcil. O sistema proposto neste trabalho, baseado em técnicas de processamento digital de imagens e redes neurais artificiais, tem o objetivo de identificar a mancha analisada e discernir entre óleo e os demais fenômenos geradores de mancha. O algoritmo que trata da classificação (Rede de função de Base Radial) é apresentado e comentado. O desempenho final do sistema medido através da curva ROC e do produto SP. As taxas de acertos são consideradas condizentes com o que a literatura de detecção de manchas de óleo na superf́ıcie oceânica através de imagens de SAR apresenta. Palavras-chave— Derramamento de Óleo, Mancha de Óleo, Classificador Neural, Sistemas Inteligentes, SAR.

Oil Recovery By Electromagnetic Heating Method In Fractured Oil Wells

The success achieved by recovery thermal methods in heavy oil reservoirs motivated emerging studies on using electromagnetic heating process for improved oil recovery. There are three different types of electromagnetic heating according to the frequency range used. They are: the resistive, the inductive and the dielectric heating. The choice of the heating type depends, among others, on factors such as reservoir depth, geological heterogeneities, electrical characteristics of reservoir constituents, type of electromagnetic heating and operating frequency. In order to increase the heat distribution in the reservoir, it can be fractured using electromagnetically sensitive particles. This study was based on computer simulations in oil reservoirs with characteristics similar to those found in the sedimentary basins of the Brazilian Northeast. Regardless to electromagnetic heating type to be used, this will generate a temperature distribution according to the geometry of the fracture developed filled with electrically sensitive particles. The purpose of this work is the use of electromagnetic heating as a recovery method of heavy oil, to analyze the influence of these fractures geometries in the reservoir model proposed. All cases studied were carried out using the commercial simulator STARS from CMG (Computer Modelling Group, version 2012.10).

Operational Conditions in Oil Recovery with Blanket Heating in Shallow Reservoirs

Abstract The most innovative proposals in the field of petroleum research refer to the oil recovery previously considered economically unviable in the market. Included in this premise is low °API oil, also known as heavy oil. Statistics show that, currently, the world reserves could be greatly improved by heavy oils contained in formations with depths between 50 m and 300 m, which are classified as shallow or ultra-shallow reservoirs. Thermal methods have been the most effective alternative for heavy oil recovery, and among them, there is the steam flood, the technique most often applied to reduce oil viscosity. A recently developed method, called Blanket Heating, combines some of the fundamental characteristics of thermal methods, adapting them to the particularities of the shallow reservoirs. This process works introducing steam in horizontal metal conduits, meaning that the heated fluid does not come into direct contact with the formation, working as a classical heat exchanger. The heating occurs indirectly, avoiding problems such as the recovery of large amounts of water and the insertion of excessive volume of steam, especially in cases where the depth is minimal and the overlying pressure is insufficient to contain the fluid. The primary focus of the article is to examine the influence of parameters involved in the operation of blanket heating, in order to find an optimal operational configuration. The choice of the horizontal direction for conduits reflects the need to maintain the greatest possible contact area between conduits and oil reserves. The results show that the blanket heating may be a viable process for heavy oil recovery in extremely shallow formations. They also show that oil recovery can be maximized in proportion to the increase of temperature in the conduits and the number of conduits. The cumulative oil production is reduced when the distance between the conduits and producer wells or between the own conduits is greater. In addition, the results were better when the completion interval of producer wells and the position of the conduits in relation to the vertical are arranged between the center and base of the reservoir. The inner diameter of the conduits was the only parameter that had minimal influence, showing no significant alterations in the production of oil. The study also showed that the blanket heating does not produce significant emissions of steam to the surface, confirming the reduction in the amount of water produced. In the face of the growing importance of heavy oil on the world market, together with the successful exploration of this resource, and knowing the current applicability of the steam flood as the main alternative to the economic recovery of this type of oil, justify the need to a study that will expand the options to use this method in reservoirs that retain great amount of viscous oil at lower depths.

Optimization of Steam and Solvent Injection as an Improved Oil Recovery Method for Heavy Oil Reservoirs

Abstract Currently a resource more and more used by the petroleum industry to increase the efficiency of steam flood mechanism is the addition of solvents. The process can be understood as a combination of a thermal method (steam injection) with a miscible method (solvent injection), promoting, thus, reduction of oil viscosity and interfacial tensions between injected fluid and oil. Solvents are hydrocarbons well known for reducing these tensions and facilitating the production of heavy oil. The use of solvent alone tends to be limited because of its high cost. When co-injected with steam, the vaporized solvent condenses in the cooler regions of the reservoir and mixes with the oil, creating a zone of low viscosity between steam and heavy oil. Mobility of the displaced fluid is then improved, resulting in an increase of oil recovery. To better understand this improved oil recovery method, a numerical study of the process was done contemplating the effects of some operational parameters (distance between wells, steam injection rate, solvent type and injected solvent volume) on cumulative oil production and oil rates. A semi synthetic model was used. Some reservoir data were obtained similar to those found in Brazilian Potiguar Basin and others ones were obtained from literature. Simulations were performed in STARS (CMG, 2007.11). It was found that injected solvent volumes increased oil recovery and oil rates. Further, the majority of the injected solvent was produced and can be recycled. High initial productions achieved by models that use solvent have normally a significant impact on the operation economics, because earlier productions suggest that fluids injection (steam and solvent) can be interrupted earlier. On environmental point of view, it would have a reduction of energy and water consumptions for steam generation, having diminished Green House Gases (GHG) emissions. Also it is important to emphasize that the high oil rates presented by these models can generate an earlier financial return, and this would be decisive for the economic viability of the project.