Drilling Stuck Pipe Prediction in Iranian Oil Fields: An Artificial Neural Network Approach

Stuck pipe is one of the most serious drilling problems, estimated to cost the petroleumindustry hundreds of millions of dollars annually. One way to avoid stuck pipe risks isto predict the stuck pipe with the available drilling parameters which can be employedto modify drilling variables. In this work, Artificial Neural Network (ANN) was used forstuck pipe prediction according to the fact that this method is applicable whenrelationships of parameters are too complicated. Based on the drilling fluid conditionfrom one of the Iranian oil fields, stuck pipe instances were divided into static anddynamic types. The results of this study show more than 90% accuracy for stuck pipeprediction in the investigated oilfield. The methodology presented in this paper enablesthe Iranian drilling industry to estimate the risk of stuck pipe occurrenc during the wellplanning procedure.