Lease Automatic Custody Transfer

The accurate measurement of crude oil during custody transfer is a critical determinant of revenue assurance and operational efficiency in the oil and gas industry. In the Niger Delta, where fiscal losses from measurement inaccuracies and operational inefficiencies are acute, optimizing Lease Automatic Custody Transfer (LACT) systems becomes a strategic imperative. This study aims to optimize LACT system performance by enhancing measurement accuracy and operational efficiency, with specific focus on the Nigerian context. Employing a novel dual-methodology approach, the research first conducts a meter drift simulation to model the financial impact of calibration decay on a turbine meter, evaluating four proving strategies: annual, quarterly, monthly, and predictive. Second, it utilizes machine learning techniques, specifically Random Forest regression, on a dataset from a Port Harcourt LACT unit to model the relationship between operational parameters (pressure, temperature, API gravity) and flow rate, identifying optimal conditions for throughput maximization. The findings reveal profound financial implications. The current industry practice of annual proving results in an estimated annual loss of $10.48 million per LACT unit. A shift to predictive proving could reduce this loss by 99.5%, saving approximately $10.43 million annually. The machine learning model (R² = 0.716) identified operating pressure as the most significant parameter influencing flow rate and pinpointed an optimal operational window (Pressure: 75.3 psi, Temperature: 92.2°F) that can improve flow rates by over 10.5% compared to sub-optimal conditions. The study concludes that significant optimization potential exists through data-driven strategies. It provides a clear, actionable roadmap for operators and regulators, recommending an immediate transition to quarterly proving and the adoption of setpoint optimization, with a long-term view towards predictive maintenance and digital integration. This research demonstrates that leveraging operational data and modern analytical techniques is key to safeguarding national revenue, enhancing transparency, and achieving operational excellence in Nigeria's oil and gas sector.