Stuck Pipe Prediction and Avoidance: A Convolutional Neural Network Approach

Refining advanced technologies for successful completion of wells is paramount in high-risk, high-cost environments such as ultra-deep water. Challenges are still very much associated with extreme depths, high temperatures, and with the small differences between formation pore pressure and pressures that will unintentionally frac a formation. Drilling mud pressures outside this narrow range can readily lead to additional problems such as stuck pipe and wellbore instability. Comparatively little research has been done to predict stuck pipe, and there are few references for quantifying estimates of force needed to free stuck pipe. Traditionally, stuck pipe problems are solved by using available standard methods and by post-sticking, ad hoc techniques. However, the real key to savings and success is in avoiding the risks leading to stuck pipe occurrences. If these risks are identified in advance, procedures can be set up to reduce the possibility of stuck pipe and, therefore, to reduce the costs associated with freeing stuck pipe. This paper presents an application of neural network methods for understanding the causes of differentially stuck pipe. The method is proposed as a more effective prognostic tool than are currently available procedures. The methodology enables drilling industry personnel to estimate the risk of occurrence of stuck pipe not only during well planning procedure but also during drilling. A three layer feed-forward network with full connection topology between layers is used. Sigmoid type non-linear activation functions and an error, back propagation learning rule are used. The convolutional analysis of the model is based on the constraints of different drilling variables. The trained neural net is shown to be able to automatically detect variables of concern. Extensive simulations have been carried out. The paper also includes three case studies of stuck pipe incidents from Gulf of Mexico where the neural network methodology successfully predicted pipe sticking and also suggested the procedure and forces necessary to free the pipe.