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A Genetic Neuro-Model Reference Adaptive Controller for Petroleum Wells Drilling Operations
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Classification of Petroleum Well Drilling Operations Using Support Vector Machine (SVM)
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An Intelligent System for Petroleum Well Drilling Cutting Analysis
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Petroleum well drilling monitoring has become an important tool for detecting and preventing problems during the well drilling process. In this paper, we propose to assist the drilling process by analyzing the cutting images at the vibrating shake shaker, in which different concentrations of cuttings can indicate possible problems, such as the collapse of the well borehole walls. In such a way, we present here an innovative computer vision system composed by a real time cutting volume estimator addressed by support vector regression. As far we know, we are the first to propose the petroleum well drilling monitoring by cutting image analysis. We also applied a collection of supervised classifiers for cutting volume classification.