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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/CO 2 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, 8.34% 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 increase of 4.36% for Mode 1, 3.79% for Mode 2 and 1.75% for Mode 3 in total exportation oil. • For the first time, a lifetime FPSO optimization is performed considering three operation modes. • The fuel consumption of the FPSO plant is reduced by 8.34%. • The hydrocarbon liquids recovery is increased by up to 4.36%. • Real data of an FPSO operating in the Brazilian pre-salt basin has been used. [ABSTRACT FROM AUTHOR]

Abstract The present work aims to perform a parametric study of heat transfer enhancement and the associated pressure loss applied to louvered fins with rectangular winglet vortex generators (RWL). The contributions of a set of design variables on heat transfer and pressure drop are evaluated for two geometry types, L1 and L2. The procedure to investigate the relative importance of the geometrical design variables on thermal-hydraulic performance is enabled by a Design of Simulations (DOS) method called Latin Hypercube Sampling (LHS) in association with a modern non-parametric statistical method (Smoothing Spline ANOVA method) and Computational Fluid Dynamics. Outcomes from the screening analyses turned out that the louver angle is the unique contributor to friction factor for both geometry types and this behaviour is independent of Reynolds number. With respect to heat transfer, the contributions of the input variables are different for both geometry types and Reynolds numbers. For Re D h = 120 , no important two-factor interaction effects were observed for both L1 and L2, in the same way as occurred in terms of friction factor. Conversely, for Re D h = 240 one relevant interaction effect was observed. [ABSTRACT FROM AUTHOR]

The demand for LNG (liquefied natural gas) increases each year, and relevant studies have been developed in order to reduce both power consumption and greenhouse gas emissions of LNG plants. Multistream plate-fin heat exchangers (MPFHE) are widely used in these plants due to their large heat transfer surface area per unit volume for multi-phase flows. The thermal-hydraulic performance of heat exchangers also impacts on compressor shaft work of liquefaction plants. In this study, an automated optimization procedure is performed for commonly used MPFHE in a three-stage propane pre-cooling cycle to maximize the coefficient of performance (COP) of liquefaction plants. Four geometric input parameters (fin type, fin height, fin thickness, and fin frequency) have been selected for the optimization. The optimal heat exchangers and operating conditions of the entire refrigeration cycle and their feasibility are taken into account. The optimal fin designs of the heat exchangers affect the cycle operating conditions, which results in COP improvements of 18.9%, 2.5%, and 9.4%, and ranging from 7% to 32% of mitigation in CO 2 emission when compared to the literature cases. Compared with the baseline case, the COP is improved by 9.4%, compressor shaft power is reduced by 7.1% (about 11.2 MW), heat transfer is augmented by 1.5% (3.8 MW), and CO 2 emission is reduced by 6.3 t/h, which result in more efficient and sustainable LNG production. • The pre-cooling cycle operational conditions and the MPFHE fin parameters were simultaneously optimized. • The operational feasibility of the optimal heat exchangers is guaranteed during the optimization procedure. • The optimal solution leads to a reduction in CO 2 emission of up to 38.3 t/h. • The optimal solution results in COP improvement of up to 18.9%. [ABSTRACT FROM AUTHOR]

Abstract FPSO (Floating, Production, Storage and Offloading) units are used for primary petroleum processing. The FPSO units have a technical advantage for short-lived well exploration and for remote marginal fields, where building a pipeline is cost-prohibitive. Considering the relevance of the FPSOs for the Brazilian petroleum market, the main goal of this paper is to present an optimization procedure to find the best operating conditions of a primary petroleum platform processing crude oil with high gas-oil ratio (GOR) and moderate CO 2 content. Seven input parameters related to operating pressures of plant are selected for the optimization procedure aiming to minimize the total fuel consumption (FUE) of the FPSO. For the optimization procedure, the processing plant of the FPSO is modeled and simulated by using Aspen HYSYS®, and the Genetic Algorithm is used for minimizing the objective function. The optimum operating condition found by the optimization procedure presented a reduction in fuel consumption by 4.6% when compared to a conventional operating condition. Moreover, because of the fuel consumption optimization, a significant reduction by 6.3% in the power consumption of the plant and an improvement in the recovery of the volatile components were verified, in comparison with the baseline case. Highlights • A FPSO processing crude oil with high GOR and moderate CO2 content was modeled and optimized. • Real performance data of an offshore gas turbine was considered. • The integration of Aspen HYSYS with an external optimizer based on Genetic Algorithm was conducted. • Significant reductions of fuel consumption and CO 2 emission were achieved by optimization. • Real data of a FPSO operating in the Brazilian pre-salt basin was used. [ABSTRACT FROM AUTHOR]