Drill bit dysfunction identification based on compact torsional behavior encoding

Abstract

Based on measurements of forces and rotational velocity experienced by a drill bit during drilling, drilling behavior is detected and identified. Measurements of forces on a drill bit including torque on bit (TOB), weight on bit (WOB), etc. and measurements of rotational velocity (rotations per minute or RPM) are acquired in real time at the drill bit. Various measurements are correlated to produce related combinations of measurements, such as WOB-RPM, TOB-RPM, and RPM-time. Based on fitting between the combinations of measurements and curves corresponding to predetermined torsional behavior trends, torsional, axial, and rotational behaviors are classified as functional or dysfunctional. A dysfunction identifier then identifies drill bit dysfunctions, such as high-frequency torsional noise, cutting-induced stick-slip, friction-inducted stick-slip, pipe-induced stick-slip, three-dimensional (3D) coupled vibrations (including subsets high-frequency torsional oscillations and low-frequency torsional oscillations), low-frequency torsional vibration, high-frequency torsional vibration, etc.) based on the functionality of the torsional, axial, and rotational behaviors. Based on drill bit dysfunction identification, dysfunctional drilling behavior can be mitigated.