Abstract: A method for predicting a failure of oilfield equipment based on univariate time series includes providing training data by a sensor. A training data stream comprising the training data is received by a preprocessor. The method further includes extracting training data segments and identifying each training data segment of the training data segments as corresponding to a normal operational state of the first oilfield equipment or a failed state of the first oilfield equipment. The method also includes generating a shapelet-based decision tree and receiving a test data stream from a sensor of second oilfield equipment. The method further includes determining, based on the shapelet-based decision tree, whether one or more test data segments extracted from the test data stream predict a failure of the second oilfield equipment.