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One of the major challenges in the drilling industry is the quick detection of problems that can occur during drilling a deep well due to high cost implications. These problems can occur for various reasons and can exhibit varying symptoms, which make them difficult to identify or prevent automatically. Visual Analytics has emerged as an alternative approach for data analysis. It combines both the computational power of computers and the experience of domain experts to analyze and gain insights into large data. This paper describes a procedure for analyzing and identifying drilling problem using Visual Analytics techniques. It provides results of an elaborated analysis of sensor measurement datasets that contain “Stuck Pipes” situations - one of the most common drilling problems. Statistical features are calculated from the dataset using the sliding window method. We show how visual analysis by means of linked scatter plots enable relating the problem patterns to the computed features and can hence help in identifying “Stuck Pipes” problems.