Virtual prototyping: a case study of positioning systems for drilling operations in the Barents Sea

ABSTRACT

This study proposes a framework for comparative study on three different positioning solutions for mobile offshore drilling units (MODUs) using high modulus polyethylene (HMPE) ropes, including active mooring with an HMPE rope, conventional dynamic positioning (DP) and active hybrid position-keeping (AHP-K). The goal of the positioning systems is to keep the MODU above the wellhead with acceptable riser-angle loading, minimal energy consumption, reduced underwater noise generation, and harmful emissions. This is the first time a holistic study has been performed on positioning that factors in the financial and environmental costs. The time domain simulation, which includes sea-state, wind, and current profiles, is performed with a well-developed software architecture and control algorithms for MODU position-keeping. The case study addresses a MODU drilling in the Barents Sea. Simulation results show that AHP-K is more efficient compared to the other two positioning solutions for drilling operations in the studied environment.

KEYWORDS:

• Barents Sea
• environmental cost Estimation
• framework for simulation integration
• hybrid mooring position keeping
• time domain simulation
• virtual prototyping

Notes on contributors

Pierre Major received his M.Sc degree in Information Technology and Electrotechnique from the Swiss Federal Institute of Technology of Zürich (ETHZ) in 2005. After various positions in the software industry, became head of research at Offshore Simulator Centre in 2019. He is currently working as an industrial Ph.D. candidate at the Norwegian University of Science and Technology (NTNU), Ålesund. His domains of interests are virtual prototyping, real time simulation and machine learning.

Robert Skulstad received his M.Sc. degree in Engineering Cybernetics from the Norwegian University of Science and Technology (NTNU), Trondheim, Norway, in 2014. He is currently working at NTNU, Aalesund, Norway, as part of the Mechatronics Laboratory within the Department of Ocean Operations and Civil Engineering, as a Ph.D. candidate. His research interests include ship motion prediction, machine learning and ship motion control.

Guoyuan Li received a Ph.D. degree from the Institute of Technical Aspects of Multimodal Systems (TAMS), Department of Informatics, University of Hamburg, Hamburg, Germany, in 2013. In 2014, he joined the Mechatronics Laboratory, Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Norway. In 2018, Dr. Li became an associate professor in ship intelligence. He has extensive research interests including eye tracking analysis, modeling and simulation of ship motion, artificial intelligence, optimization algorithms and locomotion control of bio-inspired robots. In these areas, he has published over 40 journal and conference papers.

Professor Houxiang Zhang, D.Sc., received his Ph.D. degree in mechanical and electronic engineering from Beijing University of Aeronautics and Astronautics, China, in 2003. From 2004 to 2011, he worked as a postdoctoral fellow at the Institute of Technical Aspects of Multimodal Systems, Department of Informatics, Faculty of Mathematics, Informatics and Natural Sciences, University of Hamburg, Germany. Dr. Zhang joined the Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology in Aalesund, Norway, since April 2011, where he is a full professor on robotics and cybernetics. Currently, he also has a gift professorship on product and system design from the industry. Dr. Zhang’s research focuses on maritime operation and mobile robotics. In these areas, he has published over 150 journal and conference papers and book chapters as author or co-author. He received the best paper award at the IEEE/AEME AIM2008 conference, and three finalist awards for best conference paper at IEEE Robotics and Automation conferences.

ORCID

Pierre Major http://orcid.org/0000-0001-6527-7615

Robert Skulstad http://orcid.org/0000-0003-2575-1508

Guoyuan Li http://orcid.org/0000-0001-7553-0899

Houxiang Zhang http://orcid.org/0000-0003-0122-0964

Additional information

Funding

The Norwegian Research Council supported this work under [grant number 255959]; RRFMidt Norge supported it under [grant number 274104 and 285949]; Deep Tek AS, DSM, and Offshore Simulator Centre.