AI-enabled shale shaker system aims to boost wellbore stability management capabilities

Drilling engineers rely on hydraulic models and drill cuttings transport models to measure hole-cleaning performance. However, these models can become more inaccurate as well depth increases, which can lead to costly nonproductive time (NPT) or stuck pipe incidents. CleanSight, an automated shale shaker monitoring system from DrillDocs, uses industrial cameras embedded with edge computing servers and AI-enabled computer vision algoritms to extract images of the cuttings as they exit the shale shaker. The system analyzes the size and shape of the cuttings, then reports anomalous objects that might indicate a part of the bottomhole assembly is failing.

Speaking to DC at the IADC/SPE International Drilling Conference in Galveston, Texas, on 17 March, Calvin Holt, Co-Founder and CEO of DrillDocs, talked about the CleanSight system and the impact it can have on real-time decision making.