In addition to formation evaluation, logging-while-drilling (LWD) measurements can also be used as a real-time solution to issues that arise during drilling. For example, LWD measurements can be interpreted to help determine if increasing mud weight is useful or if the rate of penetration (ROP) must be slowed. What if measurements made with LWD tools can help predict whether or not a drill string will become stuck while drilling? This paper describes a model that was created to predict situations with high risk of the tool becoming stuck so they can be addressed during the planning and execution phases. The model learns, or builds on each job experience, to improve future decisions. Most experienced individuals involved in the drilling process understand the various ways that a drill string can become stuck and factors that contribute to it becoming stuck. Many variables are attributed to a bottom hole assembly (BHA) becoming stuck during drilling operations. This paper explains the variables that were used in the model and why they were used. Some measurable variables are wellbore characteristics, BHA characteristics, downhole pressure and temperature, drilling practices and mud properties. These variables were gathered from 42 wells drilled on the Gulf of Mexico (GOM) shelf. More specifically, the information was gathered from end-of-run reports, annular pressure (AP) logs, LWD databases and surveys. After the model was created, the model was tested against seven additional GOM shelf wells. The model predicted correctly that in three of the seven wells, the drill string would be permanently stuck. In another three of the seven, the drill string was temporarily stuck while the model claimed it would be permanently stuck. In the final well, the model predicted that the drill string should be stuck, while it was not; however, the client made decisions while drilling the section which indicated that they were fearful of getting stuck. If it can be shown that there is a risk of the drill string becoming stuck in a well, preventative as well as after-the-fact measures can be used to adjust the mud system and other drilling parameters. Additionally, fishing services can be prepared early or even moved to location earlier to cut down on non-productive time (NPT). A model such as this provides an indication of the need to try preventive measures to mitigate the situation before the problem occurs, or at a minimum provides additional information so that the best course of action can be taken.

This Health Hazard Evaluation (HHE) report and any recommendations made herein are for the specific facility evaluated and may not be universally applicable. Any recommendations made are not to be considered as final statements of NIOSH policy or of any agency or individual involved.