The transition towards drilling automation in the oil and gas industry has increased the need for digital infrastructures for development and testing of new technology. This includes infrastructures to facilitate changes in work processes and technical competences. This paper describes the design and use of OpenLab Drilling, a digital infrastructure with applications in education, technology development and testing. OpenLab Drilling offers access to a high fidelity drilling process simulator capable of simulating transient hydraulics, temperature, torque and drag, and cuttings transport. Since 2018, the infrastructure has been publicly available for students, researchers and engineers who need realistic drilling data for technology development, demonstration and education. The simulated drilling data can be accessed by several means. First, through a user-friendly web application used as a tool for teaching the physics involved in drilling operations. Secondly, drilling data can be accessed programmatically through a web API or via programming language APIs written in MATLAB, Python and .NET. Thirdly, OpenLab offers a fast communication interface that can be used for applications that are closer to hardware, and which require a realistic Hardware in The Loop (HIL) infrastructure. This paper describes the objectives of OpenLab as a project, its system architecture, its simulation capabilities, the design of its web application, and its various communication interfaces. The paper also presents projects that uses OpenLab in education, research on machine learning, semantical representation of drilling data, and other industrial relevant activities. The paper is naturally divided in two parts: The design of the infrastructure, and its applications.
The application of Discrete Event Systems to model a drilling control system is investigated in this paper. Issues in the drilling process include enhancing the drilling performance, and reducing the risk of accidents. The drilling control systems that are in use today were designed to meet earlier requirements which unfortunately do not hold today. Control System engineers meet great difficulties to satisfy new requirements. We argue that those requirements are simply subsets of more general requirements namely, safety, functional scalability and task planning enablement. In this paper we show how a drilling control system can be categorized as a Discrete Event System. We formalize the problem by mapping the drilling control system to the so-called basic transition system. Finally we illustrate through a use case from drilling, how a Petri net model of the transition system satisfies our predefined requirements.
In this paper, we address the problem of high greenhouse gas emissions from oil and gas platforms in Norway. We look at the potential of integrating an energy system composed of wind turbines and battery systems to unload the electrical power generated by gas turbines being the main source of emissions today. We propose a simulation model of the energy system, the power demand, the available wind speed, and different control strategies. By putting the models together, we evaluate the performance of various compositions of the system and determine their impact on emissions and battery lifetime. The numerical results show that changing today’s practices has great potential to reduce greenhouse gases, with amounts varying between 30% and 80% compared with today’s level.
Real-time signals exchanged during a drilling operation are in constant evolution and provided by multiple stakeholders that have distinct perspectives on the drilling process. To achieve an improved drilling management and control, it is desirable that real-time drilling data can be exchanged seamlessly without necessitating any human intervention to configure software applications. By utilizing a shared drilling semantic model, drilling data-producers can expose the meaning of their real-time signals in a computer readable format. On the other hand, data-consumer applications can discover programmatically which data streams are the most appropriate for their functioning, therefore achieving seamless interoperability. This paper presents a drilling semantic framework that allows software solutions to achieve automatic and versatile self-configuration. Yet, the data exchange performances are compatible with the requirements of high-end applications involved in the management and control of drilling operations. The semantic framework relies on few but important concepts for the drilling domain. It allows to qualify the physical quantity associated with the signal, to define its dimensionality and to specify necessary references. Another important notion is the differentiation between measurements, set-points, commands, estimated values, parameters, etc. Derived measurements are explicitly described as a function of direct ones. The semantic definition encompasses how signals are related to each other in a semantical network. Relationships between signals and their logical position, in a topological description of the drilling system, are also important. Finally, the conditional validity of signals may be semantically described. A semantical model for drilling is presented together with its implementation in the OPC-UA real-time data exchange standard and will be made available to the drilling community for free usage.
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