Abstract: The subject disclosure relates to employing grouping and selection components to facilitate a grouping of failure data associated with oil and gas exploration equipment into one or more equipment failure type groups. In an example, a method comprises grouping, by a system operatively coupled to a processor, training data of a set of equipment failure data into one or more failure type groups based on one or more determined failure criteria, wherein the one or more failure type groups represent equipment failure classifications associated with energy exploration processes; and selecting, by the system, first ungrouped data from the set of equipment failure data based on a level of similarity between the first ungrouped data and the training data.

Abstract: The subject disclosure relates to employing grouping and selection components to facilitate a grouping of failure data associated with oil and gas exploration equipment into one or more equipment failure type groups. In an example, a method comprises grouping, by a system operatively coupled to a processor, training data of a set of equipment failure data into one or more failure type groups based on one or more determined failure criteria, wherein the one or more failure type groups represent equipment failure classifications associated with energy exploration processes; and selecting, by the system, first ungrouped data from the set of equipment failure data based on a level of similarity between the first ungrouped data and the training data.

Abstract: A system and method are provided. The system includes a feature calculator calculates features of a Pressure Volume diagram. The system further includes a pumpjack condition separator separates normal pumpjack conditions from abnormal pumpjack conditions using a hierarchical decision tree, the conditions being determined using the features. The system also includes a compound indicator generator generates a compound indicator when a predetermined number of at least one of features and conditions exceed respective thresholds. The system additionally includes an abnormal PV diagram indicator provides a user-perceptible indication that the PV diagram is abnormal when the compound indicator exceeds a compound indicator threshold.

Abstract: The subject disclosure relates to employing grouping and selection components to facilitate a grouping of failure data associated with oil and gas exploration equipment into one or more equipment failure type groups. In an example, a method comprises grouping, by a system operatively coupled to a processor, training data of a set of equipment failure data into one or more failure type groups based on one or more determined failure criteria, wherein the one or more failure type groups represent equipment failure classifications associated with energy exploration processes; and selecting, by the system, first ungrouped data from the set of equipment failure data based on a level of similarity between the first ungrouped data and the training data.

Abstract: The subject disclosure relates to employing grouping and selection components to facilitate a grouping of failure data associated with oil and gas exploration equipment into one or more equipment failure type groups. In an example, a method comprises grouping, by a system operatively coupled to a processor, training data of a set of equipment failure data into one or more failure type groups based on one or more determined failure criteria, wherein the one or more failure type groups represent equipment failure classifications associated with energy exploration processes; and selecting, by the system, first ungrouped data from the set of equipment failure data based on a level of similarity between the first ungrouped data and the training data.

Abstract: A system and method are provided. The system includes a feature calculator calculates features of a Pressure Volume diagram. The system further includes a pumpjack condition separator separates normal pumpjack conditions from abnormal pumpjack conditions using a hierarchical decision tree, the conditions being determined using the features. The system also includes a compound indicator generator generates a compound indicator when a predetermined number of at least one of features and conditions exceed respective thresholds. The system additionally includes an abnormal PV diagram indicator provides a user-perceptible indication that the PV diagram is abnormal when the compound indicator exceeds a compound indicator threshold.