Abstract
SPE's Drilling Systems Automation Technical Section (DSATS) sponsors the Drillbotics® autonomous drilling contest to promote advanced learning at participating universities. Two groups working independently employed similar engineering, software, and control technology to detect and mitigate drilling dysfunctions. Both teams demonstrated understanding of engineering requirements coupled with hands-on experience to successfully deploy their designs.
One team created a control model that connected with an industry research entity's well model that included a variety of formations and downhole pressures based on data from previously drilled wells in the North Sea. The well control simulation was new to the competition, and the team successfully created a workable system. The team drilled ahead at optimal ROP, stopping for connections. They then had to recognize an influx and determine whether this should be handled with the MPD system or stop drilling and close in on the kick. The model monitored surface flow in and flow out and pit level and compared readings with a trend analysis based on one-second data. The kick detection module included a technique to minimize false positives using a higher kick threshold, first giving a warning, and then switching from conventional drilling to MPD, and finally closing in the well if necessary. The simulated kick occurred during a connection and was a small kick at a low influx rate. It was detected when drilling, but later than desired. A retest with a lower kick threshold was more successful.
A second team designed and built a remotely operated autonomous small scale experimental rig that included a working version of an RSS tool to steer the BHA along a predefined trajectory within a block of sandstone. The control architecture enabled the distribution of various drilling tasks to independent specialized operating algorithms. Despite the limitations of a 1.5-inch wellbore, the physical rig team constructed and implemented an RSS with three pads actuated mechanically from the surface. Accompanied by an enhanced bit design and a length reduction of the BHA by over 50% compared to the previous model, a build rate of 8 degrees was achieved in less than two feet measured depth. This effort resulted in the team's first successful application of the newly developed scaled RSS to autonomously drill a directional trajectory provided only minutes earlier. An externally applied electromagnetic field was used to measure the azimuth, while an accelerometer was used to measure the inclination to close the feedback loop for the steering algorithm.
Both teams had to solve common engineering problems, which may lead to the use of a physical rig to improve the fidelity of virtual models. Importantly, there is an increasing industry need to provide improved data interoperability, which is being met by this program. The achievements of both teams are important to the future of drilling automation, as they are first steps towards using these research tools to improve the creation of digital twins of full-scale rigs and to verify and validate interoperability of third-party apps prior to field release on land and offshore rigs.
