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A New Approach for Estimating Free Point in Fishing of Stuck Pipe using Artificial Neural Network
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 82 - Number 6 |
| Year of Publication: 2013 |
| Authors: Aboutaleb Sasan Nejad, Khalil Shahbazi |
10.5120/14124-2248
|
Aboutaleb Sasan Nejad, Khalil Shahbazi . A New Approach for Estimating Free Point in Fishing of Stuck Pipe using Artificial Neural Network. International Journal of Computer Applications. 82, 6 ( November 2013), 53-57. DOI=10.5120/14124-2248
Abstract
Stuck pipe is a common problem in drilling industry. It accounts for the major rig time losses each year in the petroleum industry. In cases where common solutions such as pulling up and pushing down, rotating, jarring, and changing flow rate don't work, then backing off is the last resort. To have a successful back off operation, estimating location of the free point is vital. In this study, an attempt is made to estimate the free point in stuck pipe cases using the drilling data and artificial neural network approach. For this purpose, drilling data such as mud properties, pipe rotation, rate of penetration, and some other parameters are required. In this study, artificial neural networks (ANNs) model using field data from more than 40 wells was employed, and results were compared to field results. ANN model was constructed with a supervised learning algorithm and feed forward back propagation learning rule is used for training the network. The statistical error analysis results obtained by the models and acceptable values for correlation coefficient indicate that ANN model is successful in free point prediction.
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