ALSTMResNet: Active-Learning-Enhanced LSTMResNet as an Efficiency-Oriented Training Framework for Well Anomaly Monitoring Under Partial Labels
Oil-well anomaly monitoring supports safe and efficient oil-and-gas production, but delayed recognition of abnormal operating states can reduce lifting efficiency, trigger costly interventions, and increase operational risk. Existing data-driven detectors are also vulnerable to optimistic estimates when segmentation, n...