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Oil production employing gas lift techniques enable the production of no natural flow wells and supply the energy lost in the reservoir caused by the field depletion, keeping the production in brown fields feasible. The multiphase flow conditions and the long pipes used to transport the fluids from the reservoir to the surface facilities, especially in deep and ultra-deepwater cases, may create unstable flow situations. Several publications in process control have discussed this problem since the 1980s, but the potential multivariable actions on the choke valve and gas lift flow have not been explored so far. In this paper the operating oil production system is treated through a nonlinear predictive control strategy. The strategy evaluation in a rigorous model (OLGA) shows the association between predictive capability and the integrated actuation in the manipulated variables results in an oil production increase and a partial or entire suppression of the instabilities in the multiphase flow. Furthermore, the rate of acting required on the valves is lower in the multivariable approach, allowing the use of slow choke valves as a final control element.

The search for improvements in the production efficiency is one of the main challenges for the production engineers responsible for an asset, mainly at moments of low prices and very strict regulations for safety, environment and quality of products. Another point is that offshore plants are becoming more complex, so advanced control systems can support the operators and play an important role to improve stability and profitability. This paper will present an advanced control algorithm for gas-lift optimization of offshore wells that aims to increase oil production. It will also show and discuss some results of the implementations of this real time advanced control system in two offshore platforms, emphasizing the economic gains and critical points to maintain this controller running with a good performance.

The application of advanced control techniques in offshore oil production plants is a challenge. There are many changes in operational points in time, for example, the process is affected by the natural oil well's behavior dynamics. Besides that, limited instrumentation available has to be considered when thinking in oil optimization and control. In order to improve the scenario, taylor-made advanced control modules have been developed for those units. The present article will present development, implementation and results of anti-slug control for three platforms located at Campos and Santos basins. The controllers were designed to achieve improvement in operational stability and safety, decreasing in unscheduled compressor shutdown events, as well as increasing in operational efficiency.

The application of advanced control techniques in offshore oil production plants is a challenge. There are many changes in operational points in time, for example, the process is affected by the natural oil well's behavior dynamics. Besides that, limited instrumentation available has to be considered when thinking in oil optimization and control. In order to improve the scenario, taylor-made advanced control modules have been developed for those units. The present article will present development, implementation and results of anti-slug control for four platforms located at Campos and Santos basins. Severe slugging flow regimes are one of the major disturbances for the operation of offshore production platforms. Slugs can occur, for example, in pipeline-riser systems that transport oil and gas mixture from the seabed to the surface and they are characterized by severe flow and pressure oscillations, with moments of high instantaneous liquid or gas flow, which is then followed by moments of almost no flow. This cyclical phenomenon can cause many problems like reduction in process efficiency, and production losses due to many unplanned shutdowns. One of the ways to minimize issues associated with slugs is to use advanced control techniques in wells. These techniques utilize the available measurements, as downhole pressure (PDG) and top side pressures, to define a choke valve position that minimize or even eliminate slug instability. The objective is to have a stable flow together with the maximum possible production rate. One great challenge for this anti-slug control is how to deal with plant nonlinearity, because the process gain of the system changes drastically at different operating conditions. So, we will discuss in this paper different control algorithms to deal with this problem. This paper will present an anti-slug advanced control, which has three subsystems: one responsible to diagnose and identify slugs, considering some pressures patterns; other to control or minimize slugs; and finally one to protect the process plant in case of severe disturbances. Finally, this paper will show and discuss some economic and safety results of the implementations of these anti-slugs advanced control systems in offshore platforms, emphasizing the benefits obtained, which are related with stability, energy efficiency, and profitability due to a important decreasing in unscheduled compressor shutdown events, as well as increasing in operational efficiency. It will be shown that operators have well accepted this system and are maintaining this controller in automatic mode in more than 80% of the operating time.

In this paper, a thermodynamic optimization procedure for FCC riser units has been developed. The formulation uses a 2D fluid flow and kinetic model to provide the necessary information for the optimization process. The thermodynamic analysis is based on the unit entropy generation minimization, i.e., the minimization of the destroyed exergy in the system. This kind of analysis has been widely used in power generation plants, with large benefits. It was verified that for any given catalyst mass flow rate, there exists an optimum value for the catalyst to oil mass flow rate ratio, COR, for maximum mass flow rate production of gasoline, or any other desired product. Next, the objective function (net exergy production rate) was maximized through the minimization of the destroyed exergy inside the FCC unit. The optimization was conducted with respect to the catalyst to oil ratio (COR). It is important to stress that all optima are sharp, i.e., for example with H/D = 50, the variation ofeE net is greater than 50%, calculated from ðeE net; max eE net; minÞ=eE net; max for 5 < COR < 25. Based on the lack of second law analysis related works for FCC plants in the technical literature and in view of the potential gains suggested by the results, the authors believe that thermodynamic optimization could bring new insight in the quest for better FCC plants. Therefore, a low computational time tool is made available for simulation, control, design and optimization of FCC units.

BACKGROUND: A simple model is required to produce a fast computational code that is sufficiently precise to be used for the design, simulation, control and optimization of fluid catalytic cracking (FCC) risers. This work experimentally validates and adjusts a simplified FCC riser model using available experimental data, and proposes utilization of the inverse problem of the parameter estimation method to fit any existing kinetic model to a specific feedstock/catalyst set for general application. RESULTS: The model adjustment procedure was repeated for nine different experimental sets and the best fitting parameters were obtained statistically. The fitting parameters were utilized to predict the riser output conditions for the other 18 data sets. The numerical results are in good quantitative and qualitative agreement with the experimental data. The model was then utilized to simulate an industrial FCC riser, predicting concentrations and temperature profiles from the bottom to the top of the riser. CONCLUSIONS: The results suggest that the simplified model, combined with the proposed inverse methodology could produce accurate results for any feedstock/catalyst set, once the kinetic model is known for a particular feedstock/catalyst set. Therefore, a low computational time and accurate tool is made available for simulation, control, design and optimization of FCC risers. Copyright © 2008 Society of Chemical Industry

A simplified two-dimensional (2-D) formulation for FCC risers has been developed. The model approximates the mixture of gasoil, steam, and solid catalyst that flows inside the riser reactor by an equivalent fluid with average properties. The cracking reactions are modeled by a 6-lump kinetic model combined with two energy equations (gas and solid). Due to the adopted simplifications, a fast and simple-to-solve computational code was written; nevertheless, it still is sufficiently precise to be used for the design of new units and for system control and optimization of operating conditions of FCC risers. The validation of the proposed model was performed by direct comparison of the obtained results with available experimental data for a multi-purpose pilot FCC riser unit. The model was then utilized to simulate an actual size industrial FCC riser. The obtained numerical results in this article demonstrate that the model can be used as a powerful and simple tool for design, control, and optimization of FCC units, combining accuracy with low computational time to obtain solutions when simulating actual FCC riser operation. © 2006 American Institute of Chemical Engineers AIChE J, 2006

In Brazil, as in many other countries, the fuel quality control is made according to standard assays, which depend on some of the fuel properties, such as specific gravity, Reid vapor pressure and distillation curve. These properties are intimately related to the fuel composition and their prediction relies on the knowledge of its components characteristics. In Brazil, 25% (v/v) of anhydrous ethanol is added to the mixture of hydrocarbons that is usually called gasoline, according to the local regulations. In this work, the composition of the gasoline was obtained by gas chromatography as a small series of pseudo-components. Given the gasoline composition, its volatility properties and specific gravity were calculated using the Peng–Robinson equation of state with the Fisher–Gmehling mixing rule. The model provided excellent predictions for specific gravity, Reid vapor pressure and most of the distillation curve. However, important deviations are observed at the end of the distillation curve (90+%). These deviations are due to chemical alterations of the fuel caused by the high temperatures occurring at the end of the distillation curve. The model, as proposed, is efficient to forecast the fuel properties; as a consequence, it can be applied as a tool in the study of gasoline formulations and as an alternative tool in quality control.

Artificial neural networks (ANNs) were used to find correlations between the chemical composition of Brazilian gasoline and some its properties including specific gravity, distillation curve and Reid vapor pressure (RVP). The neural networks were trained with supervised learning by the use of a backpropagation algorithm. After preliminary studies and experimental planning, 35 samples of Brazilian gasoline from a universe of 1284 samples were chosen and submitted to standardized laboratory assays. The chemical composition of the samples was obtained by chromatographic analysis, which included software for detailed hydrocarbon analysis (DHA). These chemical compositions were the inputs and the standard laboratory assays were the outputs for the neural networks. The networks obtained are able to predict the gasoline properties within an average error of 1%.

Mathematical models are important tools for optimizing the design and operation of solid-state fermentation (SSF) bioreactors. Such models must describe the kinetics of microbial growth, how this is affected by the environmental conditions and how this growth affects the environmental conditions. This is done at two levels of sophistication. In many bioreactor models the kinetics are described by simple empirical equations. However, other models that address the interaction of growth with intraparticle diffusion of enzymes, hydrolysis products and O2 with the use of mechanistic equations have also been proposed, and give insights into how these microscale processes can potentially limit the overall performance of a bioreactor. The current article reviews the advances that have been made in both the empirical- and mechanistic-type kinetic models and discusses the insights that have been achieved through the modeling work and the improvements to models that will be necessary in the future.

Deodorizer distillate, produced during the last processing step of edible oil refinement, is a mixture of tocopherols, sterols, fatty acids, glycerides, hydrocarbons, water and other materials. The amount of tocopherols in deodorizer distillate is large enough to be considered as raw material for vitamin E preparation. In this work, separation of tocopherols from sterols has been achieved using liquefied petroleum gas (LPG) extraction. LPG was chosen as extraction solvent in order to improve extract recovery and prevent tocopherol degradation.

Mathematical models are important tools for optimizing the design and operation of solid-state fermentation (SSF) bioreactors. Such models must describe the transport phenomena within the substrate bed and mass and energy exchanges between the bed and the other subsystems of the bioreactor, such as the bioreactor wall and headspace gases. The sophistication with which this has been done for SSF has improved markedly over the last decade or so. The current article reviews these advances, showing how the various transport phenomena have been modeled. It also discusses the insights that have been achieved through the modeling work and the improvements to models that will be necessary in order to make them even more powerful tools in the optimization of bioreactor performance.

Abstract The discovery of new reserves of oil and gas located at great distances from the coast, with increasingly stringent regulations for safety, energy efficiency, environment and quality of products, poses new technological challenges for automation and control. Advanced control systems can play an important role to improve stability and profitability. The main objectives of advanced control systems are:Maximize the production;Ensure the specification of products;Minimize energy consumption;Minimize the process variability which increases safety and minimizes the flare (loss of products);Minimize operational costs, operating the equipment in a stable environment thus reducing the number of unscheduled stops resulting in lower maintenance and logistics costs. Although advanced control system is a reality in many industrial areas (refineries, petrochemicals and gas plants), it is not widely used for offshore production units. There are many causes that justify why advanced control is not widely utilized in offshore platforms, like:A platform has many transients (shutdown, different well alignments, etc.), many disturbances (slugs), uncertainties and noise.Oil and gas production is never in a steady state because it is a time-varying process (gas-oil-rate, water cut, sand production, gas coning, water coning, etc.).Few instruments available, for example there aren't many pressures and temperatures instruments inside subsea pipelines and wells, etc.There are no advanced control specialists onboard to install and keep these tools working properly. This paper will present some solutions to promote the use of advanced control on a platform, for example:New control strategies to minimize the effects of transients (adaptive algorithms to find out optimum PID tuning) and disturbances (anti-slug control) and also new algorithms to optimize the process.A methodology in order to help the implementation of these tools that change the way the operators interacts with the production process. This paper will show and discuss some results of the implementations of these advanced control systems in offshore platforms, emphasizing the gains of stability and profitability. The offshore plants are becoming more complex and require these advanced tools to support the operators. Introduction The regulatory and advanced control, as well as real time optimization systems can provide many advantages for the industrial units, as improved stability and safety, respect to constraints and higher profitability. Figure 1 shows a schematic automation pyramid containing the regulatory and advanced control layers.

Abstract Asset management tools related with instruments, control loops, equipment and processes, are important to reduce production costs of offshore platforms. These technologies can help to identify potential problems in advance regarding equipment and process in order to intervene and correct them. These problems can be related with operating conditions or due to the wear and tear of the equipment itself. In these scenarios, solutions could be obtained either changing the way of operating this equipment or planning new maintenances. Therefore, asset management tools can contribute to increase the reliability of the platform. This paper will describe a set of tools for asset management and discuss the challenges of its use in offshore production platforms. On a first level, there are tools that help to evaluate the quality of information related with equipment's sensors. The instruments may fail or generate a drift in its measurement over time. This deviation may compromise the operation of the associated equipment and should be detected in order to plan maintenance. On a second level, there are tools to assess the performance of PID controllers. For instance, a bad PID tuning can increase the variability of the process, putting the equipment into regions of low efficiency, which will contribute to premature wear and failure thereof. On a third level, there are tools for monitoring equipment performance, such as pumps and compressors. At this level, we try to monitor both the vibrations and the equipment performance, in order to identify deviations from the desired or normal operation. These deviations will generate alerts to be checked by experts. And finally, there are tools for process monitoring, which through KPI (key performance indicators), are able to identify early deviations from the optimal operating regions. This paper will also present some results of the application of these asset management tools. Introduction Asset management is an important activity to ensure reliability and optimize operating cost of offshore platforms. Through constantly monitoring operational variables and their alarms it is possible to identify problems and abnormal situations before they evolve to more serious faults (Venkatasubramanian et al., 2003). These problems or faults can be related with operating conditions or due to the wear of the equipment itself. In these scenarios, solutions could be obtained either changing the way of operating this equipment or planning a new maintenance intervention. Therefore, asset management comprises activities related with condition monitoring as well as supervision of the way equipment and processes are operated, helping to increase the overall availability and safety of the platform.

Zymotis bioreactors for solid-state fermentation (SSF) are packed-bed bioreactors with internal cooling plates. This design has potential to overcome the problem of heat removal, which is one of the main challenges in SSF. In ordinary packed-bed bioreactors, which lack internal plates, large axial temperature gradients arise, leading to poor microbial growth in the end of the bed near the air outlet. The Zymotis design is suitable for SSF processes in which the substrate bed must be maintained static, but little is known about how to design and operate Zymotis bioreactors. We use a two-dimensional heat transfer model, describing the growth of Aspergillus niger on a starchy substrate, to provide guidelines for the optimum design and operation of Zymotis bioreactors. As for ordinary packed-beds, the superficial velocity of the process air is a key variable. However, the Zymotis design introduces other important variables, namely, the spacing between the internal cooling plates and the temperature of the cooling water. High productivities can be achieved at large scale, but only if small spacings between the cooling plates are used, and if the cooling water temperature is varied during the fermentation in response to bed temperatures.

Inverse gas chromatography (IGC) was used to measure diffusion and thermodynamic parameters of volatile compounds in polymers. A comprehensive model for IGC is proposed, and a numerical solution for it is developed. Four capillary columns were prepared using PDMS and EPDM as the stationary phase. Toluene, ethanol, water, and some chlorinated compounds were the probes for the chromatographic experiments. Limitations of the IGC technique, although not reported in the literature, are explained. Nevertheless, the results for the systems chosen were satisfactory and agreed with the literature. The effect of adsorption on the column wall is important when water is used as a solute. The adsorption effect was incorporated into the model. The parameters obtained for water using the modified model became more reliable. The parameters obtained with IGC were used to get further understanding of the pervaporation process.

The ultrafiltration data for selective membranes, reported in the literature, show a decrease in solute rejection as the applied pressure difference through the membrane increases. This behavior is maintained until the limiting flux is reached. After this point, the solute rejection seems to remain constant in spite of the increase of the applied pressure. In the present work, a set of ultrafiltration experiments were carried out using flat and hollow fiber polysulphone membranes and aqueous dextran solutions. The conditions, at which the experiments were carried out, enabled the neglecting of adsorption and fouling phenomena. Furthermore, at these conditions, gel formation does not occur for the solute-solvent system chosen. Therefore, the limiting flux is due to concentration polarization only. In the limiting flux region, as the applied pressure difference increases, an increase in the rejection coefficient was observed for all operating conditions. In order to describe this phenomenon, a mathematical model was developed taking into account the influence of the solute concentration on the mass transfer coefficient in the polarized layer near the membrane. The results obtained with the model fit the experimental data well. An analysis of the model shows that the exponential variation of the solution viscosity with the solute concentration plays the main role in the observed rejection behavior.

Solid-state cultivation involves the growth of microorganisms in beds of moist solid particles that have a minimum of free water between the particles. The chapter describes environmentally-related solid-state cultivation processes. For example, some processes use substrates that are residues of agriculture, forestry, or food-processing, thereby reducing the environmental impact of the residue. Other processes do not use residues, but produce products that have environmental applications. Still other processes use environmental-friendly biotransformations that have the potential to replace current industrial processes. Finally, some solid-state cultivation processes can be used to remove pollutants from soil or waste streams. Typically, environmental applications of solid-state cultivation involve large-scale processing of organic solids. The current chapter addresses the design and operation of bioreactors for these processes. It shows how the various bioreactor types can be classified according to the aeration strategy, namely whether the bed of solids is forcefully aerated or not, and according to the agitation strategy, namely the frequency of mixing of the bed of solids. It discusses the current state-of-the-art in optimizing the design and operation of the various bioreactor types, showing how mathematical models that combine microbial growth kinetics and heat and mass transfer phenomena are the most powerful tools that we have available for this task. The chapter concludes by highlighting the necessity to convert current mathematical models into user-friendly computer programs that can guide design and operation decisions for large-scale solid-state cultivation bioreactors.

Macroscale heat and mass transfer phenomena play important roles in determining the performance of SSF bioreactors. Therefore, in order for a mathematical model to describe bioreactor performance reasonably, it must describe these phenomena. The current chapter gives a qualitative overview of the various macroscale heat and mass transfer processes that occur within SSF bioreactors. These processes will be treated quantitatively in Chap. 18, where the various mathematical expressions that are used to describe them within bioreactor models will be presented. Note that, in a particular SSF bioreactor, some of the heat and mass transfer mechanisms presented in this chapter may not be present, and the relative importance of the various mechanisms that are present may differ from bioreactor to bioreactor. Details specific to each bioreactor type will be covered in Chaps. 6 to 11 and 21 to 24. The current chapter focuses on the period of high heat generation, when it is necessary to remove energy from the bed, although early in the fermentation it might be necessary to transfer energy to the bed to maintain the temperature high enough to initiate growth.

True packed-bed operation can only be used in those cases where the bed does not dry out to levels that cause water limitations on growth, because water can only be uniformly distributed within a bed of solids while the solids are being agitated. If the organism tolerates some mixing, then the intermittently-mixed mode of operation can be used, in which the bioreactor operates as a packed-bed during the majority of the fermentation period and undergoes infrequent mixing events, during which water can be added to the bed (Chap. 10). In fact, once the intermittentlymixed mode of operation is selected, the use of dry air to promote evaporative cooling is potentially available as an operating strategy. The current chapter presents a model that can be used to investigate the operation of such bioreactors.