During the last decade, there has been a growing interest in developing automatic drilling process control solutions to increase drilling efficiency and consistency. But any drilling automation solution must be able to cope with drilling incidents as unexpected situations occur very frequently during the drilling process. Testing and verifying how drilling process control functions respond to drilling incidents on full scale rigs is both costly and risky, therefore it is tempting to perform such tests at a smaller scale where expenses and hazards are easier to manage.

At the laboratory-scale, it is possible to reproduce many of the classical drilling problems, like torsional vibrations, forward and backward whirls, pack-offs, drill-pipe washouts, overpulls, buckling. However, the very small scale of the rig highlights specific technical challenges that are not usually relevant for full-scale drilling operations, while other demanding conditions associated with drilling wells over several kilometers, are absent at such a small scale. For that reason, the small scale of the autonomous drilling rig influences greatly the mechanical setup and its instrumentation, as the requirements for autonomy forces to cope, in a timely fashion, with extremely short reaction times.

This paper describes the limits by which a small-scale rig should work and analyzes whether these restrictions are relevant for a standard drilling setup. The first part of the analysis focuses on how such small-scale rig experiments can be used to support the investigation of new real-time fault detection and model-based control algorithms and their associated instrumentation requirements, when the final objective is to improve full scale drilling automation. But thereafter, the study investigates how an autonomous small-scale rig can be used as a pedagogical tool for drilling engineering students.

The comparison between the specific requirements of the small-scale laboratory setup with those of a standard drilling operations exacerbates the importance of scale when analyzing drilling automation solutions, as technical solutions that may look satisfactory for wells of normal dimensions may be inadequate for more extreme drilling conditions.

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