Advanced Anti-slug Control for Offshore Production Plants

Campos, Mário Cesar Mello Massa de; Takahashi, Tatsuhito; Ashikawa, F.; Simoes, S.; Stender, A.; Meien, Oscar F. von

doi:10.1016/j.ifacol.2015.08.014

Cited by 11 publications

(2 citation statements)

References 7 publications

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“…Havre, Stornes and Stray (2000) showed a feedback control solution that is able to tame the slug flow and which greatly improves the stability of the multiphase flow. Furthermore, Campos et al (2015) implemented an advanced anti-slug control algorithm on three separate platforms leading to a massive decrease in compressor trips and gas flaring and hence increased operational stability and safety. This also led to an increase in income estimated at several million USD per year.…”

Section: Control Of Pipeline-riser System Subject To Slug Flowmentioning

confidence: 99%

A Comparison of Hazards and Efficiencies of Conventional and Adaptive Control Algorithms Using Systems-Theoretic Process Analysis

et al. 2019

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Control systems are an important and increasingly complex part of most industrial and non-industrial systems. As such, identifying and handling associated risks is increasingly important. Systems- Theoretic Process Analysis (STPA) is a relatively new hazard identification method developed to analyze modern, complex control systems. While traditional hazard analysis methods mainly focus on the failures of a system, STPA focuses on interactions among control commands and environmental conditions, so that potential non-failure problems, mainly caused by unsafe control actions, can be identified. Proportional-Integral-Derivative (PID) controllers are the most common conventional controllers (CCs) and are widely used in industry due to their simplicity. PID controllers are tuned for operation and based on the system behaviour, in a certain limited operating region. If the behavior and/or operating region of a system changes over time, the PID controller requires retuning to perform as desired and prevent loss of production, or accidents, due to inadequate control. Adaptive controllers (ACs) are able to self-adjust and adapt to changes in the system parameters and operating region, such that the overall control task is performed without the need for continuous re-tuning by an operator. The tuning of an AC is done once, at the time of implementation. This can be very helpful for both the efficiency and the safety of the control system. The interactions between the operator and the control system are reduced when the controller is able to self-adjust, potentially reducing the number of hazards. On the other hand, the complexity of ACs may introduce new kinds of hazards that do not exist when using CCs. In this paper, we compare CCs and ACs from both a control and a safety perspective using STPA. As a test case, we compare the efficiencies and hazards of a CC, and an AC applied to a pipeline-riser system subject to slug flow, a hazardous phenomenon occurring in mixed oil and gas pipes. This phenomenon is difficult to control since the behaviour changes drastically with different flow conditions.

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Section: Control Of Pipeline-riser System Subject To Slug Flowmentioning

confidence: 99%

A Comparison of Hazards and Efficiencies of Conventional and Adaptive Control Algorithms Using Systems-Theoretic Process Analysis

et al. 2019

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“…Furthermore, model reference adaptive control is applied to a pipe separator. Adaptive control schemes have seen applications in process control [12] and offshore oil and gas production [13][14][15], but the authors have not been able to locate any prior published work on adaptive control of pipe separators.…”

Section: Introductionmentioning

confidence: 99%

Controller Design and Control Structure Analysis for a Novel Oil–Water Multi-Pipe Separator

et al. 2019

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To enable more efficient production of hydrocarbons on the seabed in waters where traditional separator equipment is infeasible, the offshore oil and gas industry is leaning towards more compact separation equipment. A novel multi-pipe separator concept, designed to meet the challenges of subsea separation, has been developed at the Department of Geoscience and Petroleum at the Norwegian University of Science and Technology. In this initial study, a control structure analysis for the novel separator concept, based on step-response experiments, is presented. Proportional-integral controllers and model reference adaptive controllers are designed for the different control loops. The proportional-integral controllers are tuned based on the well-established simple internal model control tuning rules. Both control methods are implemented and tested on a prototype of the separator concept. Different measurements are controlled, and results show that the performance of the separator under varying inlet conditions can be improved with proper selection of control inputs and measurements.

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