941 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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The aim of this paper is to provide a review of the theoretical and research literature on the ways in which financial planning can enhance well-being. In reviewing the literature, the paper develops a conceptual framework for thinking about the extended value of financial planning, beyond financial outcomes, by examining the process of planning in the financial domain and its relationship to life satisfaction, living an intentional life, attainment of life goals, and the development of a sense of mastery. An essential element of psychological well-being is engagement in life tasks and roles. Planning can be considered a life management strategy that enables individuals to control and structure their lives. Having meaningful goals and the plans to achieve those goals enable individuals to experience higher levels of life engagement and well-being (MacLeod et al., 2008). Recent research on well-being suggests that domain-specific behaviours contribute to domain-specific satisfactions, which in turn contribute to an individual’s overall satisfaction with life (Easterlin, 2003; 2006). Thus changes in domain satisfaction, such as financial satisfaction, are likely to effect changes in life satisfaction.

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There is evidence that contact with the natural environment and green space promotes good health. It is also well known that participation in regular physical activity generates physical and psychological health benefits. The authors have hypothesised that ‘green exercise’ will improve health and psychological well-being, yet few studies have quantified these effects. This study measured the effects of 10 green exercise case studies (including walking, cycling, horse-riding, fishing, canal-boating and conservation activities) in four regions of the UK on 263 participants. Even though these participants were generally an active and healthy group, it was found that green exercise led to a significant improvement in self-esteem and total mood disturbance (with anger-hostility, confusion-bewilderment, depression-dejection and tension-anxiety all improving post-activity). Self-esteem and mood were found not to be affected by the type, intensity or duration of the green exercise, as the results were similar for all 10 case studies. Thus all these activities generated mental health benefits, indicating the potential for a wider health and well-being dividend from green exercise. Green exercise thus has important implications for public and environmental health, and for a wide range of policy sectors.

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As the financial planning industry undergoes a series of reforms aimed at increased professionalism and improved quality of advice, financial planner training in Australia and elsewhere has begun to acknowledge the importance of interdisciplinary knowledge bases in informing both curriculum design and professoinal practice (e.g. FPA2009). This paper underscores the importance of the process of financial planning by providing a conceptual analysis of the six step financial planning process using key mechanisms derived from theory and research in cognate disciplines such as psychology and well-being. The paper identifies how these mechanisms may operate to impact client well-being in the financial planning context. The conceptual mapping of th emechanisms to process elements of financial planning is a unique contribution to the financial planning literature and offers a further framework in the armamentarium of researchers interested in pursuing questions around the value of financial planning. The conceptual framework derived from the analysis also adds to the growing body of literature aimed at developing an integrated model of financial planning.

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While anecdotal evidence indicates financial advice affects consumers’ financial well-being, this research project is motivated by the absence of empirically-grounded research relating to the extent to which, and, importantly, how, financial planning advice contributes to broader client well-being. Accordingly, the aim of this project is to establish how the quality of financial planning advice can be optimised to add value, not only to clients’ financial situation, but also to broader aspects of their well-being. This broader construct of well-being captures a range of process and outcome factors that map to concepts of security, control, choice, mastery, and life satisfaction (Irving, 2012; Gallery, Gallery, Irving & Newton, 2011; Irving, Gallery, and Gallery, 2009). Financial planning is commonly purported to confer not only tangible benefits, but also intangible benefits, such as increased security and peace of mind that are considered as important, if not more important, than material outcomes. Such claims are intuitively appealing; however, little empirical evidence exists for the notion that engaging with a financial planner or adviser promotes peace of mind, feelings of security, and expands choices and possibilities. Nor is there evidence signalling what mechanisms might underpin such client benefits. In addressing this issue, we examine the financial planning advice (including financial product advice) provided to retail clients, and consider the short- and longer-term impacts on clients’ financial satisfaction and broader well-being. To this end, we examine both process (e.g., how financial planning advice is given) and outcome (e.g., financial situation) effects.

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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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Two distinct maintenance-data-models are studied: a government Enterprise Resource Planning (ERP) maintenance-data-model, and the Software Engineering Industries (SEI) maintenance-data-model. The objective is to: (i) determine whether the SEI maintenance-data-model is sufficient in the context of ERP (by comparing with an ERP case), (ii) identify whether the ERP maintenance-data-model in this study has adequately captured the essential and common maintenance attributes (by comparing with the SEI), and (iii) proposed a new ERP maintenance-data-model as necessary. Our findings suggest that: (i) there are variations to the SEI model in an ERP-context, and (ii) there are rooms for improvements in our ERP case’s maintenance-data-model. Thus, a new ERP maintenance-data-model capturing the fundamental ERP maintenance attributes is proposed. This model is imperative for: (i) enhancing the reporting and visibility of maintenance activities, (ii) monitoring of the maintenance problems, resolutions and performance, and (iii) helping maintenance manager to better manage maintenance activities and make well-informed maintenance decisions.

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Information and communication technologies (ICTs) had occupied their position on knowledge management and are now evolving towards the era of self-intelligence (Klosterman, 2001). In the 21st century ICTs for urban development and planning are imperative to improve the quality of life and place. This includes the management of traffic, waste, electricity, sewerage and water quality, monitoring fire and crime, conserving renewable resources, and coordinating urban policies and programs for urban planners, civil engineers, and government officers and administrators. The handling of tasks in the field of urban management often requires complex, interdisciplinary knowledge as well as profound technical information. Most of the information has been compiled during the last few years in the form of manuals, reports, databases, and programs. However frequently, the existence of these information and services are either not known or they are not readily available to the people who need them. To provide urban administrators and the public with comprehensive information and services, various ICTs are being developed. In early 1990s Mark Weiser (1993) proposed Ubiquitous Computing project at the Xerox Palo Alto Research Centre in the US. He provides a vision of a built environment which digital networks link individual residents not only to other people but also to goods and services whenever and wherever they need (Mitchell, 1999). Since then the Republic of Korea (ROK) has been continuously developed national strategies for knowledge based urban development (KBUD) through the agenda of Cyber Korea, E-Korea and U-Korea. Among abovementioned agendas particularly the U-Korea agenda aims the convergence of ICTs and urban space for a prosperous urban and economic development. U-Korea strategies create a series of U-cities based on ubiquitous computing and ICTs by a means of providing ubiquitous city (U-city) infrastructure and services in urban space. The goals of U-city development is not only boosting the national economy but also creating value in knowledge based communities. It provides opportunity for both the central and local governments collaborate to U-city project, optimize information utilization, and minimize regional disparities. This chapter introduces the Korean-led U-city concept, planning, design schemes and management policies and discusses the implications of U-city concept in planning for KBUD.

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Rapidly changing economic, social, and environmental conditions have created a need for urban and regional planning practitioners who are resilient, innovative, and able to cope with the increasingly complex and cosmopolitan nature of major metropolitan areas. This need should be reflected in planning education that allows students to experience a diverse range of approaches to problems and challenges, and that exposes students to the diverse array of perspectives on planning issues. This paper investigates the outcomes of a collaborative regional planning exercise organised jointly by planning academics from both Queensland University of Technology and the International Islamic University of Malaysia, and involving planning students from both universities. The regional planning exercise consisted of a regional appraisal and report topics of the area under investigation, Klang Valley – Kuala Lumpur, Malaysia. It culminated with the presentation of regional development strategies for the area, with a field trip to Malaysia being the cornerstone of the project. The collaborative exercise involved a series of workshops and seminars organised locally, in which both Australian and Malaysian planning students participated, as well as meetings with local and federal planning officials, and also a forum for Young Planners of Australian and Malaysian Planning Institutes. The experience attempted to bridge the teaching of theoretical concepts of regional planning and development and the regional, more professional knowledge of planning practice, as it relates to specific political, institutional and cultural contexts. A survey of participating students, from both Queensland University of Technology and the International Islamic University of Malaysia, highlights the benefits of such project in terms of leaning experience and exposure to different cultural contexts.

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Mobile robots are widely used in many industrial fields. Research on path planning for mobile robots is one of the most important aspects in mobile robots research. Path planning for a mobile robot is to find a collision-free route, through the robot’s environment with obstacles, from a specified start location to a desired goal destination while satisfying certain optimization criteria. Most of the existing path planning methods, such as the visibility graph, the cell decomposition, and the potential field are designed with the focus on static environments, in which there are only stationary obstacles. However, in practical systems such as Marine Science Research, Robots in Mining Industry, and RoboCup games, robots usually face dynamic environments, in which both moving and stationary obstacles exist. Because of the complexity of the dynamic environments, research on path planning in the environments with dynamic obstacles is limited. Limited numbers of papers have been published in this area in comparison with hundreds of reports on path planning in stationary environments in the open literature. Recently, a genetic algorithm based approach has been introduced to plan the optimal path for a mobile robot in a dynamic environment with moving obstacles. However, with the increase of the number of the obstacles in the environment, and the changes of the moving speed and direction of the robot and obstacles, the size of the problem to be solved increases sharply. Consequently, the performance of the genetic algorithm based approach deteriorates significantly. This motivates the research of this work. This research develops and implements a simulated annealing algorithm based approach to find the optimal path for a mobile robot in a dynamic environment with moving obstacles. The simulated annealing algorithm is an optimization algorithm similar to the genetic algorithm in principle. However, our investigation and simulations have indicated that the simulated annealing algorithm based approach is simpler and easier to implement. Its performance is also shown to be superior to that of the genetic algorithm based approach in both online and offline processing times as well as in obtaining the optimal solution for path planning of the robot in the dynamic environment. The first step of many path planning methods is to search an initial feasible path for the robot. A commonly used method for searching the initial path is to randomly pick up some vertices of the obstacles in the search space. This is time consuming in both static and dynamic path planning, and has an important impact on the efficiency of the dynamic path planning. This research proposes a heuristic method to search the feasible initial path efficiently. Then, the heuristic method is incorporated into the proposed simulated annealing algorithm based approach for dynamic robot path planning. Simulation experiments have shown that with the incorporation of the heuristic method, the developed simulated annealing algorithm based approach requires much shorter processing time to get the optimal solutions in the dynamic path planning problem. Furthermore, the quality of the solution, as characterized by the length of the planned path, is also improved with the incorporated heuristic method in the simulated annealing based approach for both online and offline path planning.