Detection of downhole incidents for complex geological drilling processes using amplitude change detection and dynamic time warping

Abstract Geological drilling process is operating under complex geological conditions, which may lead to a high risk of downhole incidents and thus compromise the drilling efficiency. To achieve prompt detection of downhole incidents and prevent them from developing to serious drilling accidents, this paper proposes a new data-driven detection method for downhole incidents based on the amplitude change detection and dynamic time warping. Two major phases are involved: the change monitoring phase detects whether there is any significant change in the drilling signals and extracts variational trend features by linear fitting and amplitude change detection; the incident detection phase determines if the cause of a change is a normal switching or a downhole incident by similarity analysis based on the dynamic time warping and the density-based spatial clustering. Industrial case studies show that the proposed method achieves good performance in downhole incidents detection for geological drilling processes.