FPSO fuel consumption and hydrocarbon liquids recovery optimization over the lifetime of a deep-water oil field

• Autor(a) principal: Allahyarzadeh-Bidgoli, Ali
• Data de Publicação: 2019
• Outros Autores: Dezan, Daniel Jonas, Salviano, Leandro Oliveira [UNESP], Oliveira Junior, Silvio de, Yanagihara, Jurandir Itizo
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1016/j.energy.2019.05.146; http://hdl.handle.net/11449/185942
• topic: Thermodynamic analysis; Fuel consumption and stabilization of hydrocarbon liquids optimization; FPSO; Deep-water oil field; Hybrid optimization method

A Floating, Production Storage and Offloading (FPSO) plant is a high-energy consumer (from a few to several hundreds of megawatts). Since a number of parameters have effects on the FPSO plant performance, screening analysis procedure could be used to select the most important parameters affecting a given output and an optimization procedure being applied to maximize/minimize an objective function. Thus, optimization procedures focused on fuel consumption and hydrocarbon liquids recovery can improve the energy efficiency, product recovery, and sustainability of the plant. In the present work, optimization procedures are used for an FPSO plant operating at three different conditions of the Brazilian deep-water oil field in pre-salt areas to investigate: (1) Maximum oil/gas content (Mode 1); (2) 50% BS&W oil content (Mode 2) and; (3) High water/CO2 content in oil (Mode 3). In order to reduce the computational efforts, we investigate the contribution of eight thermodynamic input parameters to the fuel consumption of the FPSO plant and hydrocarbon liquids recovery by using the Smoothing Spline ANOVA (SS-ANOVA) method. From SS-ANOVA, the input parameters that presented the major contributions (main and interaction effects) to the fuel consumption and hydrocarbon liquids recovery were selected for the optimization procedure. The optimization procedure consists of a Hybrid method, which is a combination of Non-dominated Sorting Genetic Algorithm (NSGA-II) and AfilterSQP methods. The results from the optimized case indicate that the minimization of fuel consumption is 4.46% for Mode 1, 834% for Mode 2 and 2.43% for Mode 3, when compared to the baseline case. Furthermore, the optimum operating conditions found by the optimization procedure of hydrocarbon liquids recovery presented an (C) 2019 Elsevier Ltd. All rights reserved.