964 resultados para Well planning


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Domains where knowledge representation is too complex to be described analytically and in a deterministic way is very common in the petroleum industry, particularly in the field of exploration and production. In these domains, applications of artificial intelligence techniques are very suitable, especially in cases where the preservation of corporate and technical knowledge is important. The Laboratory for Research on Artificial Intelligence Applied to Petroleum Engineering (LIAP) at Unicamp, has, during the last 10 years, dedicated research efforts to build intelligent systems in well drilling and petroleum production fields. In the following sections, recent advances in intelligent systems, under development in the research laboratory, are described. (C) 2001 Published by Elsevier B.V. B.V.

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The development of oil wells drilling requires additional cares mainly if the drilling is in offshore ultra deep water with low overburden pressure gradients which cause low fracture gradients and, consequently, difficult the well drilling by the reduction of the operational window. To minimize, in the well planning phases, the difficulties faced by the drilling in those sceneries, indirect models are used to estimate fracture gradient that foresees approximate values for leakoff tests. These models generate curves of geopressures that allow detailed analysis of the pressure behavior for the whole well. Most of these models are based on the Terzaghi equation, just differentiating in the determination of the values of rock tension coefficient. This work proposes an alternative method for prediction of fracture pressure gradient based on a geometric correlation that relates the pressure gradients proportionally for a given depth and extrapolates it for the whole well depth, meaning that theses parameters vary in a fixed proportion. The model is based on the application of analytical proportion segments corresponding to the differential pressure related to the rock tension. The study shows that the proposed analytical proportion segments reaches values of fracture gradient with good agreement with those available for leakoff tests in the field area. The obtained results were compared with twelve different indirect models for fracture pressure gradient prediction based on the compacting effect. For this, a software was developed using Matlab language. The comparison was also made varying the water depth from zero (onshore wellbores) to 1500 meters. The leakoff tests are also used to compare the different methods including the one proposed in this work. The presented work gives good results for error analysis compared to other methods and, due to its simplicity, justify its possible application

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A viticultura é uma atividade relevante para os produtores rurais do Estado de São Paulo, sobretudo aqueles detentores de pequenas áreas. O presente trabalho teve como objetivo caracterizar os principais aspectos sociais e tecnológicos utilizados na produção de uvas para mesa na região de Jales (SP). Os dados foram levantados nos anos de 2009 e 2010, a partir da aplicação de questionários a 19 produtores de uva e do acompanhamento do ciclo de produção de 10 propriedades. Os produtores cultivam pelo menos três cultivares diferentes de uva, sendo as principais: 'Niagara Rosada', 'Itália' e 'Benitaka'. A área média das propriedades é de, aproximadamente, 21 ha, e a área média com parreiras de uva é de 2,4 ha. A maioria dos produtores não conta com assistência técnica regular, não segue recomendações de adubação e não emprega critérios técnicos para o manejo da irrigação. O controle de doenças é realizado de forma preventiva e intensa, chegando a superar 100 aplicações por ciclo, no caso das uvas finas para mesa. Os resultados devem subsidiar a realização de outras pesquisas, assim como programas de planejamento e transferência de tecnologia, proporcionando ao produtor um manejo mais adequado da cultura, bem como o desenvolvimento sustentável rural regional.

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Bit performance prediction has been a challenging problem for the petroleum industry. It is essential in cost reduction associated with well planning and drilling performance prediction, especially when rigs leasing rates tend to follow the projects-demand and barrel-price rises. A methodology to model and predict one of the drilling bit performance evaluator, the Rate of Penetration (ROP), is presented herein. As the parameters affecting the ROP are complex and their relationship not easily modeled, the application of a Neural Network is suggested. In the present work, a dynamic neural network, based on the Auto-Regressive with Extra Input Signals model, or ARX model, is used to approach the ROP modeling problem. The network was applied to a real oil offshore field data set, consisted of information from seven wells drilled with an equal-diameter bit.

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The development of oil wells drilling requires additional cares mainly if the drilling is in offshore ultra deep water with low overburden pressure gradients which cause low fracture gradients and, consequently, difficult the well drilling by the reduction of the operational window. To minimize, in the well planning phases, the difficulties faced by the drilling in those sceneries, indirect models are used to estimate fracture gradient that foresees approximate values for leakoff tests. These models generate curves of geopressures that allow detailed analysis of the pressure behavior for the whole well. Most of these models are based on the Terzaghi equation, just differentiating in the determination of the values of rock tension coefficient. This work proposes an alternative method for prediction of fracture pressure gradient based on a geometric correlation that relates the pressure gradients proportionally for a given depth and extrapolates it for the whole well depth, meaning that theses parameters vary in a fixed proportion. The model is based on the application of analytical proportion segments corresponding to the differential pressure related to the rock tension. The study shows that the proposed analytical proportion segments reaches values of fracture gradient with good agreement with those available for leakoff tests in the field area. The obtained results were compared with twelve different indirect models for fracture pressure gradient prediction based on the compacting effect. For this, a software was developed using Matlab language. The comparison was also made varying the water depth from zero (onshore wellbores) to 1500 meters. The leakoff tests are also used to compare the different methods including the one proposed in this work. The presented work gives good results for error analysis compared to other methods and, due to its simplicity, justify its possible application

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There has been an increasing interest in the impact of individual well-being on the attitudes and actions of people receiving services designed to offer support. If well-being factors are important in the uptake and success of service programmes it is important that the nature of the relationships involved is understood by service designers and implementers. As a contribution to understanding, this paper examines the impact of well-being on the uptake of intervention programmes for homeless people. From the literature on well-being a number of factors are identified that contribute towards overall well-being, which include personal efficacy and identity, but also more directly well-being can be viewed as personal or group/collective esteem. The impact of these factors on service use is assessed by means of two studies of homelessness service users, comparing the implementation of two research tools: a shortened and a fuller one. The conclusions are that the factors identified are related to service use. The higher the collective esteem – esteem drawn from identification with services and their users and providers – and the less that they feel isolated, the more benefits that homeless people will perceive with service use, and in turn the more likely they are to be motivated to use services. However, the most important factors in explaining service use are a real sense that it is appropriate to accept social support from others, a rejection of the social identity as homeless but a cultivation of being valued as part of a non-homeless community, and a positive perception of the impact of the service.

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PURPOSE: To report an uncommon case of osteochondroma affecting the mandibular condyle of a young patient and to illustrate the important contributions of different imaging resources to the diagnosis and treatment planning of this lesion. CASE DESCRIPTION: A 24-year-old female patient with the chief complaint of an increasing facial asymmetry and pain in the left pre-auricular region, revealing a reduced mouth opening, mandibular deviation and posterior cross-bite over a period of 18 months. Panoramic radiography revealed an enlargement of the left condyle, whereas computed tomography (CT) sections and three-dimensional CT showed a well-defined bone growth arising from condylar neck. The scintigraphy exam showed an abnormal osteogenic activity in the left temporomandibular joint. The condyle was surgically removed and after 18 months follow-up the panoramic radiography and CT scans showed no signs of recurrence. CONCLUSION: Although osteochondroma is a benign bone tumor that rarely arises in cranial and maxillofacial region, it should be considered in the differential diagnosis of slow-growing masses of the temporomandibular area and the use of different imaging exams significantly contribute to the correct diagnosis and treatment planning of this pathological condition.

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Recent advances in energy technology generation and new directions in electricity regulation have made distributed generation (DG) more widespread, with consequent significant impacts on the operational characteristics of distribution networks. For this reason, new methods for identifying such impacts are needed, together with research and development of new tools and resources to maintain and facilitate continued expansion towards DG. This paper presents a study aimed at determining appropriate DG sites for distribution systems. The main considerations which determine DG sites are also presented, together with an account of the advantages gained from correct DG placement. The paper intends to define some quantitative and qualitative parameters evaluated by Digsilent (R), GARP3 (R) and DSA-GD software. A multi-objective approach based on the Bellman-Zadeh algorithm and fuzzy logic is used to determine appropriate DG sites. The study also aims to find acceptable DG locations both for distribution system feeders, as well as for nodes inside a given feeder. (C) 2010 Elsevier Ltd. All rights reserved.

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Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.

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The reconstruction of power industries has brought fundamental changes to both power system operation and planning. This paper presents a new planning method using multi-objective optimization (MOOP) technique, as well as human knowledge, to expand the transmission network in open access schemes. The method starts with a candidate pool of feasible expansion plans. Consequent selection of the best candidates is carried out through a MOOP approach, of which multiple objectives are tackled simultaneously, aiming at integrating the market operation and planning as one unified process in context of deregulated system. Human knowledge has been applied in both stages to ensure the selection with practical engineering and management concerns. The expansion plan from MOOP is assessed by reliability criteria before it is finalized. The proposed method has been tested with the IEEE 14-bus system and relevant analyses and discussions have been presented.

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Tese de Doutoramento, Ciências do Mar (Biologia Marinha)

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This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances, including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.

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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

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Arquivos de Medicina 1998; 12(4): 246-248