Machine vision for drill string slip status detection

Abstract

Slip status of drill string is system generated binary value computed by comparison of sensor generated real time hook load value with a minimum threshold value of hook load stored in measurement system. This research article describes a novel method of slip status detection by machine vision technology which helps overcome the constraints of slip status detection with legacy measurement method. It also helps improve the real time drilling data quality and optimize and automate drilling operations. A method to detect drill string slip status with high-resolution digital camera installed on mast near rig floor is described along with backend vision processing and communication modules, which generate binary values of slip status. The binary values are transferred in real time to drilling measurement system of rig to compute other drilling parameters like bit depth, hole depth and stand counters. This method includes deploying active optical sensors at the rig floor, obtaining 1-D, 2-D, or 3D image data, and processing it to obtain the status of drill string. Reliable measurement of slip status by machine vision helps reduce non-productive time (NPT) by reliable real time surveillance of drilling operations.