Term 252

RigLab-AI: Smart Return Line Monitoring System with AI Camera & Sensors

Project Type: Self-Initiated

Project Description

In this project, we are designing RigLab-AI, a rig-ready return-line monitoring system that combines an AI camera with controlled LED lighting and a sensor suite to continuously analyze drilling fluid behavior as it exits the well. The purpose is to improve early detection of drilling hazards (kick/loss), increase the reliability and repeatability of monitoring under real rig conditions (splash, vibration, and low light), and reduce the time required for testing and reporting. The proposed design uses a clamp-mounted hardware package installed on the mud return line. A 1080p camera (≥30 fps) with LED illumination will capture critical visual features, specifically the mud returns line gate opening degree and mud level changes, while sensors will measure key parameters such as pressure, density, flow rate, and a viscosity-related signal. These measurements will be time synchronized through a data acquisition and processing unit. The system features a dedicated web-based Decision Support System (DSS). This software architecture processes the raw camera data, converting visual gate opening metrics into digital values, and integrates them with sensor readings on a real-time dashboard. The DSS includes a logic-based alert engine that compares these synchronized inputs against safety thresholds to flag potential kick/loss events, and an automated reporting module that generates daily logs and critical event summaries for Petroleum and Control Engineers. The project will deliver a complete conceptual design including system architecture, component selection, performance targets, and verification planning. Prototype testing will be conducted by comparing RigLab-AI measurements and alerts against baseline conditions and reference tools to quantify detection responsiveness and repeatability. The expected outcome is a low-disruption, cost - effective monitoring solution that provides reliable real-time warning capability and improved digital documentation of return-line behavior.