The DSATS technical section believes that this challenge benefits students in several ways. Petroleum, mechanical, electrical or control engineers, gain hands-on experience in each person’s area of expertise that forms a solid foundation for post-graduate careers. They also develop experience working in multi-disciplinary teams, which is so important in today’s technology driven industries. Winning teams must possess a variety of skills. The mechanical and electrical engineers need to build a stable, reliable and functional drilling rig. Control engineers need to architect a system for real-time control, including selection of sensors, data handling and fast-acting control algorithms. The petroleum engineers need an understanding drilling dysfunctions and mitigation techniques. Everyone must work collectively to establish system functional requirements understood by each team member, properly model the drilling issues, and then to create a complete package working seamlessly together.
The oil and gas industry today seeks lower costs through efficiency and innovation. Many of the student competitors may discover innovative tools and control processes that will assist drillers to speed the time to drill and complete a well. This includes more than faster ROP, such as problem avoidance for dysfunctions like excessive vibrations, stuck pipe, and wellbore stabilty issues. Student teams built new downhole tools using 3D printing techniques of designs that would be difficult, if not impossible to machine. They used creative hoisting and lowering systems. Teams modeled drilling performance in particular formations and adjusted the drilling parameters accordingly for changing downhole conditions. While they have a lot to learn yet about our business, we have a lot to learn about their fresh approach to today’s problems.
Successful teams must be able to…
In the 2019-2020 competition, there is a new category for those who cannot build a physical rig. Teams may create a virtual rig and must use it to drill a virtual directional well. Teams model the rig and its actions and responses. Next they create automation and control algorithms similar to their physical counterparts. Then they must model the bit/bha interactions with the wellbore while monitoring the performance of the drillstring and the rig. Finally they bring all of this together to model the effects of drilling a directional well in this virtual setting.
