Modern drilling operations are supported by broadband data links, real-time computer simulations and increased levels of automation. The integration of different computer systems is gradually improving, but consideration of human-machine interface is lagging behind causing information overload, mistakes and collaboration problems. New mathematical models for anomaly detection in drilling operations have been developed in the IO Centre. Recommendations and guidelines are established on how to implement and use the mathematical methods for better experience transfer and anomaly detection during drilling operations.
Ongoing activities include mathematical methods for better integration of computer models and work processes during drilling, early detection of drilling problems and improved experience transfer. The project consider both the impact of new technologies such as wired drill pipe or networked drill string and the interplay between the technical and organizational side of drilling. The issue of bad data quality, which is a big problem for drilling automation, is a typical example of a problem which cannot be studied only as a technical problem, but require a cross-discipline approach.