Examination arrangement

Course content

The course covers the theory and application of automation and digital technologies for control, optimization and performance analytics for well construction and production processes. The following topics are covered in the course with the focus on digital and automation technologies in the oil and gas industry applications:

• Automation and digitalization in oil and gas industry
• Components of digital and automation technologies. Hierarchy of automation systems
• Modelling of dynamic processes in well construction and hydrocarbons production
• Design and tuning of automatic control systems
• Advanced process control
• Signal processing, estimation and detection systems
• Introduction to data analytics/decision support systems
• Systems engineering aspects of digital and automation technologies
• Risk evaluation and mitigation for digital and automation technologies
• Business case evaluation for digital and automation technologies

The students will get a hands-on experience in design and implementation of digital and automation technologies for petroleum applications in a simulated environment.

Learning outcome

Ingress: In this course the students should acquire basic knowledge and skills for development and application of automation and digital technologies for control, optimization and decision support for well construction and hydrocarbons production processes.

Knowledge: The students should know/understand the following items in their application to well construction and hydrocarbons production:

• Principles of digital and automation technologies
• Modelling principles for dynamical processes and various types of models (static / dynamic; linear / nonlinear; continuous-time / discrete-time; advanced models for simulations and fit-for-purpose models for control systems development)
• Components of automation technologies (controlled process, instrumentation, data acquisition system and automation infrastructure, human-machine interface, automation algorithms, actuators, safety systems)
• Methods for development of automation systems: logics-based systems, linear automatic control systems (e.g. PID controller), simple model-based control systems
• Principles of optimal control systems: model-based (e.g. Model Predictive Control) and data-driven (e.g. extremum seeking)
• Basic notions and tools of signal processing, state and parameter estimation (soft sensors, least-squares method, observers, Kalman filter)
• Systems engineering aspects for digital and automation technologies in oil and gas industry
• Risks related to introduction of automation and digital solutions in production and well construction and their mitigation
• Elements for business case evaluation for applications of automation and digital technologies for production and well construction processes

Skills: The students will acquire basic skills to develop and tune automatic control and optimization systems for applications in well construction and hydrocarbons production; to develop basic signal processing tools; to make a technology development and implementation plan for digital and automation technologies.

General competence: The students should acquire general competence on:

• Digital and automation technologies and the scope for their potential applications within hydrocarbons production and well construction
• Links between digital and automation technologies and other disciplines, e.g. field development, drilling & well, production technology, operations and maintenance, etc.
• Development, implementation and use of such technologies in industry

Learning methods and activities

The course will be given through lectures, self-study and exercises/projects. Depending on the course participants and their needs, the lecture and work plan will be defined in more detail between the professor and the student(s) at the beginning of the semester. The course will not be given if less than 3 students apply to take the course. The course will be held in English.

Compulsory assignments

• Exercises

Further on evaluation

To pass the course a score of at least 70 percent is required.

Specific conditions

Required previous knowledge

MSc degree in Petroleum Engineering or approval by lecturer.

Course materials

Lecture notes, selected papers and publications.