Modeling and Control for Automation Processes (PET575)

Automated drilling and modeling course provides a detailed knowledge of mathematical drilling models, drilling data, drilling control systems and automated drilling methods.

Course description for study year 2023-2024. Please note that changes may occur.


Course code




Credits (ECTS)


Semester tution start


Number of semesters


Exam semester


Language of instruction



The course provides detailed knowledge of developing static and dynamic models and related simulation software; strengthens programming skills; introduces data analysis techniques and data quality improvement methods; introduces control techniques, automation tools and automated systems; demonstrates laboratory for automated systems and realtime automation operations.

Adjustments to the plan may occur.

Learning outcome

Students who successfully complete the course should achieve:

  • understand modeling procedures
  • know about data and data processing methods
  • know about control theories and observer design methods
  • know about automation tools and automated process
  • be able to perform basic programming in Matlab or Python
  • be able to process and analyze data
  • be able to implement control strategies for automated systems
  • be able to perform realtime operations through simulators
  • have a general understanding about high-level automated drilling techniques which also can be relevant to other areas
  • have insight into how automated laboratorial systems and software tools can be used for increased understanding and research
  • general programming competence which can be useful in different disciplines

Required prerequisite knowledge


Recommended prerequisites

Physics, mathematics, cybernetic engineering, mechanical engineering, drilling subjects and basic programming in e.g. Matlab or Python


Form of assessment Weight Duration Marks Aid
Written schoolexam 1/1 4 Hours Letter grades Standard calculator

Coursework requirements

Mandatory homework

Course teacher(s)

Course teacher:

Jan Einar Gravdal

Course coordinator:

Dan Sui

Head of Department:

Øystein Arild

Method of work

Classroom teaching, individual assignments/group work, exercises, presentations, homework, projects, visits to laboratory

Overlapping courses

Course Reduction (SP)
Advanced Drilling Technology and Engineering (PET525_1) 5

Open for

Admission to Single Courses at the Faculty of Science and Technology Computational Engineering - Master of Science Degree Programme Petroleum Engineering - Master of Science Degree Programme Exchange programme at Faculty of Science and Technology

Course assessment

There must be an early dialogue between the course coordinator, the student representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital course evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.


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