Cooperative Control of Drilling Equipment

One fully funded 4-year industrially sponsored PhD is available in Edinburgh starting September 2017. Sponsorship will be provided by Schlumberger (www.slb.com). Schlumberger is the leading supplier of technology, project management, and information solutions, trusted to deliver superior results and improved E&P performance for oil and gas companies around the world. Through their well site operations and in their research and engineering facilities, they are working to develop products, services and solutions that optimize customer performance in a safe and environmentally sound manner.

As automation of drilling processes is developed, operation will be split between completely automated tasks and tasks that are carried out by humans. The project will look at how teams comprising human and robotic actors will collaborate to achieve complex and uncertain tasks in drilling operations.

Particular areas of interest:

- Delivery and execution monitoring of collaborative plans.

- Developing and maintaining trust between the human and automated parts of the system.

- Multi-modal interfaces for communication and coordination (using wearable computing, etc.).

- Dynamically changing activities in response to unexpected events/changes in priorities.

- Reliable state/event detection and communication mechanisms that prioritise significant events and support effective human decision-making.



Applicants should have, or expect to obtain one of the following qualifications:

BEng/MEng/MSc in Mechanical Engineering (or equivalent) 1st class/70% average or above
BEng/MEng/MSc in Mechanical Engineering (or equivalent) 1st class/70% average or above
BSc/MSc Computer Science (or equivalent) 1st class/70% average or above.
Other engineering, science or mathematical backgrounds studied to a suitably qualified level may also be considered. A background in dynamics and control of autonomous/robotic mechanical systems is desirable.