A System of Systems Engineering Approach for Intelligent Control and Supervision of Subsea Production Systems Edmary Altamiranda, IEEE Member
Eliezer Colina, IEEE Member
Subsea Control Systems Engineering Department GE Oil & Gas Stavanger, Norway
[email protected]
Engineering Faculty, Systems Engineering Department Universidad de Los Andes Mérida, Venezuela
[email protected]
Abstract—A fundamental aspect in the design of a complex system is the use of systems concepts, principles and laws in terms of a holistic view of the problem under study. The increasing complexity of subsea production systems demand the development of condition monitoring, supervision, integrated diagnosis and control technologies to achieve the synergy among all different subsystems and therefore increase performance, reliability, safety and optimize the overall operation for the subsea facility. This paper explores the use of a system of systems engineering approach to develop a framework to support intelligent control, supervision and integrated diagnosis applicable for subsea production and processing systems. Keywords—Systems of Systems; Intelligent Control; Supervision; Subsea Production; Underwater Technology.
I.
INTRODUCTION
The need to operate industrial plants in a smooth and sound manner to ensure compliance with technical specifications and safeguard product quality is heightened in today’s increasingly competitive globalised economy [1]. Competitive advantage can be gained by reducing raw material and energy consumption and energy consumption costs, maximizing plant throughput and by meeting rigorous environmental regulations [2-5]. One of the important challenges facing control system engineers is how to design and implement intelligent systems that may assist supervision and decision making such as abnormal situation management (ASM), start up and shut down, controller performance assessment [2,6]. The growing interest of system of systems (SoS) as new generation of complex systems has opened many challenges for systems engineers. Performance, optimization, robustness, and reliability among an emerging group of heterogeneous systems, in order to realize a common goal, have become the focus of various applications; including military, security, aerospace, manufacturing, service industry, environmental systems etc. [7]. There is an increasing interest in achieving
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synergy among independent systems to obtain higher capabilities and performance. The use of artificial intelligence approaches such as Neural Networks, Genetic Algorithms and Fuzzy Logic have been increasing in the last few years. These paradigms have potential for developing reasoning strategies for applications such as fault detection, diagnosis, supervision and decision making among others [2-3, 8-11]. They have been successfully applied in oil industry related businesses such as Refinery and Petrochemical where the processes and control systems involved have a very high complexity [2]. Over the last decade, there has been a huge increase in the application of subsea production systems for the production of oil and gas from subsea wells [6]. There is also a growing interest on evolving from traditional subsea production systems to subsea production and processing systems to increase oil recovery reduce capital expenditures (CAPEX) and operational expenditures (OPEX), provide operational flexibility and health, safety and environment (HSE) benefits among others [12-15]. The increasing complexity of subsea production and processing functions demands the development of condition monitoring, supervision, integrated diagnosis and control technologies to achieve the synergy among all different subsystems and therefore increase performance, reliability, safety and optimize the overall operation for the subsea facility. Intelligent control, supervision and integrated diagnosis for subsea systems are still in development stages. In [1] was presented an artificial intelligence based framework for integrated fault detection and diagnosis to support supervision and decision making applicable to subsea control systems. It includes instrumentation, electrical, electronic, hydraulic and communication subsystems. This approach is oriented to minimize well shut-down, disruption to the operations and production losses due to unexpected failures on any subsea control system component or subsystem. It may also
contribute to achieve early fault detection and appropriate fault identification to support and improve troubleshooting, decision making and maintenance tasks (preventive maintenance). In [6] was presented a prototype for condition monitoring on subsea electronic modules. The proposed prototype is a model based tool that includes residual analysis for fault detection. This paper explores the use of system of systems concepts to develop a framework to support intelligent control, supervision and integrated diagnosis applicable for subsea production and processing systems. Systems engineering is a very fundamental field within subsea technology. System of systems engineering (SoSE) concepts may support the challenging development of subsea production and processing systems; enhancing functionality, integration, robustness and increasing reliability of the overall complex SoS system. The paper is structured as follows: section II and III present an overview of subsea production systems and subsea processing systems. Section IV and V present the SoS concepts and SoSE approach and sections VI and VII describe local supervision of SoS elements and integrated control of SoS. II.
SUBSEA PRODUCTION SYSTEMS
Over the last decade, there has been a huge increase in the application of subsea production systems for the production of oil and gas from subsea wells. A conventional subsea production system comprises control system, wellhead and xmas tree equipment, pipelines, manifold structures and riser systems among others. In many cases a number of wellheads have to be controlled from a single location [16]. A. Subsea Production Control System A subsea control system is part of a subsea production system. The control system provides operation of valves and chokes on subsea completions, templates, manifolds and pipelines. In addition, for satisfactory operational characteristics, the design of a control system must also provide a means for safe shutdown on failure of equipment or loss of electrical/hydraulic control from the topside (a platform or floating facility) and other safety features that automatically prevent dangerous events. A conventional subsea production control system comprises: 1) Topside equipment: Includes hydraulic power unit, electrical power unit, chemical injection unit and a master control station. 2) Umbilicals: An umbilical is a conduit between the topside host facility and the subsea control system and is used for chemical and/or hydraulic fluids, electric power and electric control signals. 3) Subsea equipment: Comprises the power, communication and distribution equipment and the subsea
control modules which provide monitoring and control of all functions of the subsea production system [6]. B. X- mas trees A production x-mas tree produces well flow of oil and gas from a wellhead. It is an arrangement of remote operated valves, such as choke for flow control, master and wing valves for safety and several auxiliary valves for well intervention and chemical treatment of the well flow. A x-mas tree is also equipped with sensors for monitoring well performance. C. Manifold A production manifold gathers production flow from several wells and distributes the well flow through flow lines to a topside installation. D. Flow Lines The flow lines may be a combination of pipelines and flexible lines (risers) to a platform or pipelines to onshore installation. III.
SUBSEA PROCESSING SYSTEMS
The interest on evolving from traditional subsea production systems to subsea production and processing systems is growing as fields become more remote and in deeper waters. This emerging technology allows increasing oil recovery, reduce capital expenditures (CAPEX) and operational expenditures (OPEX); provide operational flexibility and health, safety and environment (HSE) benefits among others [12-15, 17]. Subsea processing systems are also attractive for mature or marginal fields. In order to maintain the production rates and optimize the recovery, water and gas are re-injected with subsea injection pumps. Subsea boosters and pumps are introduced to ease the transport of the hydrocarbons from the field to an onshore installation or a platform. Separation of sand, oil, water and gas is being performed on the sea bed [12]. Subsea separation optimizes the amount of production transferred from the seabed to the surface, debottlenecking the processing capacity of the topside facility. Gas treatment and compression technologies are also being deployed at the seabed [13-14, 17]. In order to increase or maintain gas production rates on mature or marginal fields, compression power is needed to boost gas pressure. The long step out conditions and the power requirements for these technologies demand the need of subsea high voltage transmission lines and distribution equipment. It is not economically viable to supply power to individual loads from topside [15]. This has opened the opportunity to develop electrical equipment and control systems to suit the
challenging demands of the subsea environment for these applications. Subsea processing technology is foreseen to continue developing in the future. This technology contributes to flow management and assurance, enhances the efficiency of flow lines and risers, increases field recovery, and reduces capital and operational expenditures among other benefits. The increasing system complexity and demanding requirements will continue leading to challenging developments in the subsea systems field. IV.
SYSTEMS OF SYSTEMS CONCEPTS
The growing interest of system of systems (SoS) as new generation of complex systems has opened many challenges for systems engineers. Performance, optimization, robustness, and reliability among an emerging group of heterogeneous systems, in order to realize a common goal, have become the focus of various applications; including military, security, aerospace, manufacturing, service industry, environmental systems etc. [7]. System of systems concepts are still in development stages [18, 19]. There are numerous SoS definitions in literature [7, 18-27]. This section will refer to some of the potential definitions that can be considered applicable to the topic under study in this paper. A system of systems (SoS) is a collection of task-oriented or dedicated systems that pool their resources and capabilities together to create a new, more complex system which offers more functionality and performance than simply the sum of the constituent systems [20]. According to [18, 23], systems of systems are large-scale integrated systems which are heterogeneous and independently operable on their own, but are networked together for a common goal. The goal may be cost, performance, robustness, etc. [7] A SoS can exhibit complex systems characteristics, but not all complex systems might fall into the realm of SoS. In fact, SoS goes beyond than the merely integration of large scale systems. According to [28] a system of systems exists when there is a presence of a majority of the following characteristics on the constituent systems: operational independence, managerial independence, geographic distribution, emergent behavior and evolutionary development. Definition presented in [29] describes the characteristics of SoS constituent components as dynamic properties including autonomy, belonging, connectivity, diversity and emergence. The methodology for defining, abstracting, modeling, and analyzing system of systems problems together with the
processes, tools and methods to design, deploy and operate solutions to SoS problems are typically referred as systems of systems engineering (SoSE) [7, 18, 23-24, 30-34]. Systems of systems engineering is an emerging engineering field oriented to support development, operation and optimization of various interacting legacy and new systems brought together to satisfy multiple objectives. V.
SYSTEMS OF SYSTEMS ENGINEERING APPROACH
A crucial step towards a system of systems engineering approach to conceive a complex production process should be the use of systems principles, laws and concepts [35] together with a good understanding of the problems associated with the constituent system elements and the knowledge of the entire complex process objectives as a whole entity. Such an approach must include phases such as planning, analysis, organization and integration of existing and new systems in a bigger system that has greater capabilities than the sum of the capabilities of their individual components. Two highlights in the description of the SoS for the production and processing case of study presented in sections II and III are: 1) The need for access and proper management of information concerning the status of constituent systems, allowing autonomous operation or implementation of control and supervision tasks. 2) A physical/communicational interconnection among functionally independent constituent systems operations leading to the satisfaction of common goals in terms of reliability, performance, lower operational costs, etc. Additionally, the production and processing systems should be adaptable to operate against technical, financial or organizational changes. The foregoing leads to propose an approach based on three main mega phases: a) Specification of the problems: It is necessary to structure and frame the boundaries of the problems to be treated within the SoS considered, using a team with the resources and expertise necessary to develop a “strategy plan” that allows specifications deployment using fenomenological information as well as qualitative and quantitative data about the problems. b) Analysis of the problems: This phase is centred in exploring and analysing the SoS objectives and executing the “strategy plan” that leads to characterize the SoS purposes. c) Design and results: The principal task in this phase is to define implementation goals required to support the SoS objectives. Undoubtedly, each of the previous phases involves the use of a large number of auxiliary tools, working simultaneously on a number of different tasks, with a multidisplinary team of actors.
VI.
HYBRID SYSTEMS TO SUPPORT CONTROL AND SUPERVISION OF SOS ELEMENTS
Interaction of components in a SoS can be achieved by efficient communication among the relevant systems or through a central coordination in a given SoS [7]. Interactions among subsystems are generally asynchronous in nature. Such systems interactions can be effectively represented as discrete event models [23]. For subsea production and process applications the different subsystems will operate in a continuous time frame and they will have a high degree of interoperability. However, in order to promote individual subsystems to SoS components, the subsystems should have independent condition monitoring, integrated diagnosis, intelligent control and supervision to be able to support and contribute to the large production systems goals. These requirements imply a hybrid nature for the subsea production and process SoS components. In the process control area, the continuous time process of a hybrid system corresponds to the physical process itself, which must be controlled. A discrete event system, on the other hand, represents a supervisor (automaton), which reacts in presence of generated events from the continuous time process in order to fulfil system specifications. The dynamic systems whose behaviours depend on the interaction between continuous time processes and discrete supervisors are called hybrid systems [2]. A framework for intelligent supervision and integrated fault detection and diagnosis applicable to subsea production control systems was presented in [1]. This philosophy based on hybrid systems [2] can be utilized and adapted to enhance the capabilities of individual subsea production and processing systems to be promoted to SoS elements within the large subsea production system.
The proposed supervision scheme, for individual subsea systems, based on philosophy presented in [1] is illustrated in figure 1. The continuous process level represents the individual subsea production or processing system interacting with the condition monitoring, fault detection and diagnostic system to monitor the equipment and support the faults identification when they are produced. Continuous level layout is illustrated in figure 2. Appropriate instrumentation to support equipment monitoring, diagnostic models and algorithms to support fault detection and diagnosis must be in place [1, 5-6, 10-11]. Process condition monitoring and process control performance monitoring can be also incorporated to the continuous level supported by process models and appropriate algorithms [2, 4, 37-41]. Data pre-processing and residual analysis to support fault detection and diagnosis is proposed to be performed within the condition monitoring modules. This information is then processed by an intelligent event detector according to the philosophy presented in [2, 36] which allows mapping the identified conditions and faults in discrete events. The discrete events are used in the supervisory system in order to generate the appropriate discrete control patterns for supporting system optimization, troubleshooting, decision making and maintenance tasks. These patterns have to be sequenced for multivariable processes with several subsystems. The translator block will translate the discrete control patterns in specific control set points, decisions and messages for subsea operation and maintenance tasks. The local supervisory system must interact with management levels to be able to update the operational regions in accordance with management priorities. S u p e r v is o r y L e v e l D is c r e te E v e n t s D o m a in
M an agem ent Level
D is c r e t e C o n tro l P a tte rn s
S u p e r v is o r In (A u to m a to n )
Ev e n ts
C o n t r o lI nP a t t e r n s Se q u en cer
In t e llig e n t E v e n t In D e te c to r
T r a n IsTl ra nt o r
S e t P o in t s O p e ra t io n a l D e c is io n s M e s s a g e s fo r m a in t e n a n c e ta sk s
In t e g ra t e d C o n d it io n M o n it o r in g F a u lt D e t e c t io n & D ia g n o s is S u b s e a P r o c e s Ss s ua unb ds C o n t r o l S y s t e m
.
Fig.1 Intelligent Supervisory Scheme based on Hybrid Systems
P r o c e s s V a r ia b le s D ia g n o s is O u t p u t s
C o n t in u o u s P ro ce ss L e v e l
Integrated Condition Monitoring Fault Detection and Diagnosis
Fault Detection and Diagnosis Equipment Residuals
Equipment Condition Monitoring Equipment measurements and Housekeepings
Process Residuals
Process and Control Performace Condition Monitoring
Equipment Residuals
Control Deviations
Process Variables
Control System Control outputs
Control Variables
.
Subsea Process
Fig. 2 Hybrid System Continuous Level Layout
VII.
INTEGRATED CONTROL OF SYSTEMS OF SYSTEMS
The main challenge in the design of SoS control strategies is the complexity of developing comprehensive SoS models. This complexity is dependent on the specific application problem. Therefore SoS control is still an open field of research [7].
Figure 4 illustrates a hierarchical control diagram of a SoS and is based on the assumption that the SoS can be characterized by a finite set of elements that can be separately monitored, controlled and optimized using the hybrid system approach presented in section VI. . Coupled Model
SoS elements interaction in an integrated SoS is driven by interoperability and overall integration of elements [7]. As mentioned on section VI such system interactions can be effectively represented as discrete events models [23]. Discrete event system specification [42] is a formalism that provides a means of specifying component of a system in a discrete event simulation. The basic models are called atomic models and the larger models obtained by connecting these atomic blocks are called coupled models [7]. Figure 3 illustrate discrete system specification model representing systems and subsystems [23, 43, 44]. Each of these atomic models has input ports to receive external events, output ports to send events, set of state variables, internal transition, external transition and time advance function [7]. Another difficulty from control perspective is that each system control strategy cannot solely depend on its on-board sensors information. To achieve efficient integrated control schemes, communication links among neighbouring systems or between sensors, controllers and actuators need to be considered [7].
Coupled Model
Atomic Model Atomic Model Atomic Model
Fig. 3 Discrete Event System Specification Model
Solid lines represent the interaction between each local supervisor and the global SoS supervisor. Dashed lines represent data transmission among SoS elements.
SoS
Supervisor System 2
Supervisor System 1
......
Supervisor System n-1
Supervisor System n
Fig.4 Hierarchical Approach for SoS Integrated Control
VIII.
CONCLUSION
Systems of systems engineering is an emerging engineering field oriented to support development, operation and optimization of various interacting systems to satisfy multiple objectives.
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This paper has explored the use of systems of systems concepts to develop a framework to support intelligent control and supervision schemes applicable to subsea production and processing systems. A particular element of the proposed scheme is the construction of a hybrid systems based intelligent supervision and integrated fault detection and diagnosis to enhance individual systems capabilities of the SoS elements. Furthermore the coordination of the interactions among SoS elements is conceived in terms of a discrete event system specification model which operates on a hierarchical topology of the integrated control structure of the considered SoS case of study. The system of system engineering approach is applicable to new systems and also to the integration of existing systems with new designed systems components, in order to improve information management required for appropriate decision making tasks, such as fault detection, diagnosis, control and supervision. Appropriate specification and analysis of SoS objectives is important to define the implementation goals and address the required SoS elements capabilities to support the objectives for the large integrated system of systems.
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