Affiliation:
1. Young Researchers and Elites Club, Science and Research Branch, Islamic Azad University, P.O. Box 14515-775, Tehran 1477893855, Iran e-mail:
Abstract
Prediction of differential pipe sticking (DPS) prior to occurrence, and taking preventive measures, is one of the best approaches to minimize the risk of DPS. In this paper, probabilistic artificial neural network (ANN) has been introduced. Moreover, conventional ANNs through multilayer perceptron (MLP) and radial basis function (RBF) have been used to compare with probabilistic ANN. Furthermore, to determine the most important parameters, forward selection sensitivity analysis has been applied. By predicting DPS and performing sensitivity analysis, it is possible to improve well planning process. The results from the analyses have shown the better potentiality of the probabilistic ANN in this area.
Subject
Geochemistry and Petrology,Mechanical Engineering,Energy Engineering and Power Technology,Fuel Technology,Renewable Energy, Sustainability and the Environment
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