Experiments with a steel catenary riser model in a towing tank

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)A model test with a steel catenary riser (SCR) was concluded in a towing tank. The main purpose of the experiment was to gain further understanding of the global SCR dynamic behavior with vortex-induced vibration (VIV). To this end, a large model scale factor (250) was considered. The mass and stillness of the riser model are very low, and the Reynolds number in the experiment ranged from 900 to 600. The experimental results demonstrated the influence of traveling waves on the cross-flow response of the riser model, which was verified by several analytical methods. This study provided important indications that the sources of the traveling waves (power-in regions) seem to change position along the riser length over time. Finally, the experimental design, data processing procedure, experimental set-up, and results are described in detail. (C) 2013 Elsevier Ltd. All rights reserved.43244255Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Finep (CTPetro)PetrobrasCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)PRH/ANP - The Brazilian National Petroleum AgencyConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES

Case-based reasoning in offshore well design

Petroleum well drilling is an expensive and risky operation. In this context, well design presents itself as a fundamental key to decrease costs and risks involved. Experience acquired by engineers is notably an important factor in good drilling design elaborations. Therefore, the loss of this knowledge may entail additional problems and costs. In this way, this work represents an initiative to model a petroleum well design case-based architecture. Tests with a prototype showed that the system built with this architecture may help in a well design and enable corporate knowledge preservation. (C) 2003 Elsevier Science B.V. All rights reserved.4041671476

Development of intelligent systems for well drilling and petroleum production

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 Science B.V.3241731SI19119

Leak detection in petroleum pipelines using a fuzzy system

A methodology for pipeline leakage detection using a combination of clustering and classification tools for fault detection is presented here. A fuzzy system is used to classify the running mode and identify the operational and process transients. The relationship between these transients and the mass balance deviation are discussed. This strategy allows for better identification of the leakage because the thresholds are adjusted by the fuzzy system as a function of the running mode and the classified transient level. The fuzzy system is initially off-line trained with a modified data set including simulated leakages. The methodology is applied to a small-scale LPG pipeline monitoring case where portability, robustness and reliability are amongst the most important criteria for the detection system. The results are very encouraging with relatively low levels of false alarms, obtaining increased leakage detection with low computational costs. (c) 2005 Elsevier B.V. All rights reserved.494173222323