Identifying operation anomalies of subterranean drilling equipment

Abstract

The present disclosure relates to systems, methods, and non-transitory computer-readable media for dynamically utilizing, in potentially real time, anomaly pattern detection to optimize operational processes relating to well construction or subterranean drilling. For example, the disclosed systems use time-series data combined with rig states to automatically detect and split similar operations. Subsequently, the disclosed systems identify operation anomalies from a field-data collection utilizing an automated anomaly detection workflow. The automated anomaly detection workflow can identify operation anomalies at a more granular level by determining which process behavior contributes to the operation anomaly (e.g., according to corresponding process probabilities for a given operation). In addition, the disclosed systems can present graphical representations of operation anomalies, process behaviors (procedural curves), and/or corresponding process probabilities in an intuitive, user-friendly manner.