Fábio S. Liporace

Real Time Fouling Diagnosis and Heat Exchanger Performance

The issue of fouling in preheat trains of crude oil distillation units in Petrobrass refineries is a major concern—especially now, as heavier Brazilian crudes with higher asphaltene content are being refined. As the efficiency of the preheat train plays an important role in the energy consumption of a distillation unit, its performance must be tracked as precisely as possible in order to identify operational problems. This work describes an online heat exchanger performance evaluation system based on rigorous simulation of the equipment in order to predict both the operational and clean overall heat transfer coefficient. A real-time comparison between these two values indicates the actual performance of the heat exchanger and of the preheat train. The use of a rigorous process simulator (Petrox from Petrobras) together with a rigorous calculation of the global heat transfer coefficient (using the program Xist from HTRI) allows one to consider aspects that are not usually taken into account in this kind of evaluation. These aspects include crude vaporization after the desalters and variations of crude and products composition with the distillation unit run. The system is being implemented at the biggest Petrobras refinery (360,000 bpd) in a 25 heat exchanger preheat train.

Parameter Estimation of Fouling Models in Crude Preheat Trains

Several fouling mitigation techniques depend on the capacity of predicting fouling rates. Therefore, the identification of accurate fouling rate models is an important task. Crude fouling rates are usually evaluated through empirical or semiempirical models. In both alternatives, there are parameters that must be determined through laboratory or process data. In this context, the article presents an analysis of the parameter estimation problem involving fouling rate models. A proposed procedure for addressing this problem is described through the development of a computational routine called HEATMODEL. An important aspect of this study is focused on the obstacles associated to the search for the optimal set of parameters of the Ebert and Panchal models and its variants. This optimization problem may present some particularities that complicate the utilization of traditional algorithms. In the article, the performance of a conventional optimization algorithm (Simplex) is compared with a more modern numerical technique (a hybrid genetic algorithm) using real data from a Brazilian refinery. The results indicated that, due to the complexity of the parameter estimation problem, the Simplex method may be trapped in poor local optima, thus indicating the importance of the utilization of global optimization techniques for this problem.

Challenges and problems with advanced control and optimization technologies

Abstract Abstract Oil & Gas companies continuously try to create and increase business value of their installations (platforms, refineries, etc). Particularly the increasing energy consumption on a worldwide basis and, as a result, the substantial increase in prices volatility is a major drive for better advanced control and optimization technologies. Advanced control and optimization system can play an important role to improve the profitability and stability of industrial plants. This paper discusses the problems and challenges of advanced control and optimization in petroleum industries nowadays. It emphasizes the importance of control performance assessment technology to maintain a good regulatory control and the difficulties in using these technologies. It also shows the importance of malfunction detection and diagnosis advisory system for critical equipment in order to increase the operational reliability. Model predictive control (MPC) has become a standard multivariable control solution in the continuous process industries, but there are still many open issues related to accelerate a new implementation and maintain the controller with a good performance along the years. Real time optimization tools also impose new challenges for Oil & Gas industries application, which are discussed in this paper.

PETROBRAS Experience Implementing Real Time Optimization

Abstract PETROBRAS has defined Real Time Optimization (RTO) as a “High Sustainability” technology for downstream operations, due to its high economic return. Since 2001, RTO tools are being tested within the Company, either using in-house process simulators or, sometimes, using available commercial ones. This paper presents an overview of the PETROBRAS experiences on RTO, showing applications on Distillation and Fluidized Catalytic Cracking (FCC) units. Alternatives based on Sequential-modular simulators, along with reduced models (Kriging models and neural nets), as well as Equation-oriented based simulators / optimizers have been explored. The project scopes vary from covering only the Reactor / Regenerator section of a FCC unit up to a whole Crude distillation unit, including the preheat train, all distillation towers and the heat and material integration. Some of these RTO applications have been running close loop for almost 6 months, with proved expressive economical benefits. Based on the knowledge acquired during all these years, some of the future development needs for the improvement of RTO technology will be presented and discussed, as a guide for future research projects.

A Sliding Mixed-Integer Linear Programming Approach for the Optimization of the Cleaning Schedule of Crude Preheat Trains

The fuel consumption in the fired heaters of atmospheric distillation columns for petroleum refining increases during the refinery operation. This effect is a consequence of fouling in the heat exchangers of the crude preheat train. The application of a cleaning schedule to the crude preheat train can reduce fouling costs. However, the management of the cleanings for the entire set of interconnected heat exchangers is a complex problem. Aiming to contribute to the solution of this problem, this paper presents an optimization approach based on the resolution of a sequence of mixed-integer linear programming problems. Each problem indicates the set of heat exchangers that must be cleaned in a certain time instant. The structure of the crude preheat train is described using an incidence matrix, encompassing supply and demand nodes, heat exchangers, mixers, splitters, and desalters. The sequence of problems is associated to a sliding horizon, where the concatenation of the solutions composes the complete heat exchanger cleaning schedule. Although the present approach cannot guarantee the global optimality of the solution, the linear structure avoids nonconvergence problems. The performance of the proposed approach is illustrated through its application in an example of a crude preheat train from a Brazilian refinery.

Decomposition Techniques for the Real-time Optimization of a Propylene Production Unit

Abstract In this work an application of decomposition techniques on a propylene production unit from REPLAN refinery by Petrobras S.A. is presented. It is shown that the classic Lagrangian Relaxation (LR) technique and the alternative technique called “Pricing Interprocess Streams Using Slack Auctions” (PISUSA) do not converge for the case study presented. The issues involved in each decomposition approach are identified and discussed; then a modification of the Lagrangean Relaxation algorithm is proposed using a new constraint-updating rule. This modified algorithm is able to overcome the issues and solve the decomposed problem properly.

Design and Implementation of a Real Time Optimization Prototype for a Propylene Distillation Unit

Abstract The design of a steady state RTO system prototype to be tested in an industrial unit is presented. A software architecture (SA) approach is carried out proposing an objectoriented software framework. SA patterns are used in the architecture design. The framework aims to allow the implementation of different RTO approaches. A RTO system prototype is being developed using the framework integrating EMSO (Soares and Secchi, 2003) as the modeling and optimization engine. The framework opens opportunities for academic uses and deeper researches on the field.

Practical Implementation of a RTO in an Industrial-Scale Vapor Recompression Distillation Process

Abstract In this work a practical implementation of a real time optimization (RTO) in an industrial scale propylene-propane distillation process (Refinaria de Paulinia, SP, Brazil) owned by Petrobras S.A. is carried out. The main steps of a classical RTO cycle are considered: steady-state identification, parameter estimation, data reconciliation and economical optimization. The non-identifiability problems, observed in the parameter estimation module, are mitigated by using the Rotational Discrimination (RD) method (Graciano et al., 2014). The outcomes of this study suggest that the model parameters are successfully estimated by the RD method and the RTO is able to improve the economical gains between 3-26%, depending on the initial condition, which represents saves up to 19 million dollars per year.

Fouling Management in Crude Oil Preheat Trains Through Stream Split Optimization

Abstract In general, the first main step of petroleum refining consists in the distillation of the crude oil stream. In order to provide adequate fractionation, the crude stream must be fed in the atmospheric distillation column at about 380°C. Aiming to reduce energy consumption, heat from hot streams of side products and pumparounds is transferred to the crude stream in a heat integration scheme, called crude preheat train. The final heating of the crude stream is executed in a furnace. However, during the operation of the preheat train; the thermal effectiveness of the heat exchangers diminishes due to fouling and, as a consequence, fuel costs increases. The large volumes of crude oil processed and the scenario of crescent energy prices justify the importance of this problem for the oil companies. Seeking to provide a solution to reduce the impact of this problem, this paper presents the exploration of stream splitting in crude preheat trains composed by several parallel branches. In this case, each branch may present different fouling levels, which allows the exploration of different distributions of the stream flow rates along the system, through a proper optimization algorithm. This optimization algorithm searches the set of stream splitters related to the maximization of the final temperature of the crude preheat train. A mathematical model of the preheat train works coupled to the optimization method. An important focus of this paper is to explore the introduction of constraints in order to guarantee feasible operating solutions, i.e., the optimum solution must attend different operational aspects related to bounds on fluid flow velocities and heat exchanger capacities. The performance of the proposed approach is illustrated through a typical example of a petroleum refinery.