Lab-Scale Drilling Rig Autonomously Mitigates Downhole Dysfunctions and Geohazards Through Bit Design, Control System and Machine Learning
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AbstractOilfield economic conditions today continue to emphasize the need to recognize and respond to drilling dysfunctions quickly to maximize performance and minimize well costs. It is important for drilling engineers planning wells to fully comprehend each dysfunction in order to develop a means to mitigate their impact. As progress is made in this effort, it has become increasingly clear that many issues facing the drilling industry cannot be solved or solutions implemented with traditional drilling technology and platforms. The automation of drilling data collection and control systems response is increasingly becoming a key aspect of advancing many aspects of drilling performance.SPE's Drilling Systems Automation Technical Section (DSATS) now enters its third year of an international competition for universities to design and build a small drilling rig that can operate hands-free in an unknown formation. Much like engineers in the field, students from each team must develop technical skills to understand the drilling dysfunctions that affect their rig's performance and calculate their impact on drilling performance. For the first time, in the 2017 competition, students must design and build a downhole sensor integrated into their control scheme. They have applied several different sensor types and unique telemetry techniques in custom-machined bottom-hole assemblies (BHA) that follow a 1.125 in (28.5mm) bit. The collected data is being used for vibration mitigation in real-time without human intervention.The teams realize that the measurement and control aspects of drilling are as important as the equipment design, so they must model the drilling-states to determine appropriate response algorithms. Issues must be identified, and drilling parameters adjusted before dysfunctions severely limit performance. Teams often conduct a series of structured tests in various rock types to pre-tune their drilling algorithms. With improved state-detection algorithms and new optimization techniques, the drilling parameters that maximize performance are immediately calculated and implemented. DSATS intentionally challenges each team by choosing a thin-walled pipe which limits the ability to apply weight on the bit (WOB), ultimately generating an environment that promotes bit whirl. DSATS also provides an unknown rock sample of varying material, formation dips and other "surprises."This paper presents the results of on-site testing of the winning team, Texas A&M University, who drilled a high-quality wellbore in the shortest amount of time. It also details the decision-process for the rig's design, based on background lab tests and engineering calculations.
