4 resultados para operation mode
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
In the last decades, the oil, gas and petrochemical industries have registered a series of huge accidents. Influenced by this context, companies have felt the necessity of engaging themselves in processes to protect the external environment, which can be understood as an ecological concern. In the particular case of the nuclear industry, sustainable education and training, which depend too much on the quality and applicability of the knowledge base, have been considered key points on the safely application of this energy source. As a consequence, this research was motivated by the use of the ontology concept as a tool to improve the knowledge management in a refinery, through the representation of a fuel gas sweetening plant, mixing many pieces of information associated with its normal operation mode. In terms of methodology, this research can be classified as an applied and descriptive research, where many pieces of information were analysed, classified and interpreted to create the ontology of a real plant. The DEA plant modeling was performed according to its process flow diagram, piping and instrumentation diagrams, descriptive documents of its normal operation mode, and the list of all the alarms associated to the instruments, which were complemented by a non-structured interview with a specialist in that plant operation. The ontology was verified by comparing its descriptive diagrams with the original plant documents and discussing with other members of the researchers group. All the concepts applied in this research can be expanded to represent other plants in the same refinery or even in other kind of industry. An ontology can be considered a knowledge base that, because of its formal representation nature, can be applied as one of the elements to develop tools to navigate through the plant, simulate its behavior, diagnose faults, among other possibilities
Resumo:
The precision and the fast identification of abnormalities of bottom hole are essential to prevent damage and increase production in the oil industry. This work presents a study about a new automatic approach to the detection and the classification of operation mode in the Sucker-rod Pumping through dynamometric cards of bottom hole. The main idea is the recognition of the well production status through the image processing of the bottom s hole dynamometric card (Boundary Descriptors) and statistics and similarity mathematics tools, like Fourier Descriptor, Principal Components Analysis (PCA) and Euclidean Distance. In order to validate the proposal, the Sucker-Rod Pumping system real data are used
Resumo:
Despite the emergence of other forms of artificial lift, sucker rod pumping systems remains hegemonic because of its flexibility of operation and lower investment cost compared to other lifting techniques developed. A successful rod pumping sizing necessarily passes through the supply of estimated flow and the controlled wear of pumping equipment used in the mounted configuration. However, the mediation of these elements is particularly challenging, especially for most designers dealing with this work, which still lack the experience needed to get good projects pumping in time. Even with the existence of various computer applications on the market in order to facilitate this task, they must face a grueling process of trial and error until you get the most appropriate combination of equipment for installation in the well. This thesis proposes the creation of an expert system in the design of sucker rod pumping systems. Its mission is to guide a petroleum engineer in the task of selecting a range of equipment appropriate to the context provided by the characteristics of the oil that will be raised to the surface. Features such as the level of gas separation, presence of corrosive elements, possibility of production of sand and waxing are taken into account in selecting the pumping unit, sucker-rod strings and subsurface pump and their operation mode. It is able to approximate the inferente process in the way of human reasoning, which leads to results closer to those obtained by a specialist. For this, their production rules were based on the theory of fuzzy sets, able to model vague concepts typically present in human reasoning. The calculations of operating parameters of the pumping system are made by the API RP 11L method. Based on information input, the system is able to return to the user a set of pumping configurations that meet a given design flow, but without subjecting the selected equipment to an effort beyond that which can bear
Resumo:
In the last decades, the oil, gas and petrochemical industries have registered a series of huge accidents. Influenced by this context, companies have felt the necessity of engaging themselves in processes to protect the external environment, which can be understood as an ecological concern. In the particular case of the nuclear industry, sustainable education and training, which depend too much on the quality and applicability of the knowledge base, have been considered key points on the safely application of this energy source. As a consequence, this research was motivated by the use of the ontology concept as a tool to improve the knowledge management in a refinery, through the representation of a fuel gas sweetening plant, mixing many pieces of information associated with its normal operation mode. In terms of methodology, this research can be classified as an applied and descriptive research, where many pieces of information were analysed, classified and interpreted to create the ontology of a real plant. The DEA plant modeling was performed according to its process flow diagram, piping and instrumentation diagrams, descriptive documents of its normal operation mode, and the list of all the alarms associated to the instruments, which were complemented by a non-structured interview with a specialist in that plant operation. The ontology was verified by comparing its descriptive diagrams with the original plant documents and discussing with other members of the researchers group. All the concepts applied in this research can be expanded to represent other plants in the same refinery or even in other kind of industry. An ontology can be considered a knowledge base that, because of its formal representation nature, can be applied as one of the elements to develop tools to navigate through the plant, simulate its behavior, diagnose faults, among other possibilities