Automated Trend Identification and Alert System for Wells Monitoring in Mature Asset: Advantages and Challenges

Abstract Manual monitoring procedures, while necessary, are sometimes inaccurate and inefficient. This study provides a proof of concept for an advanced automated trend identification and alert system intended to improve well monitoring in mature assets by detecting trends and anomalies in real-time and historical data such as production, injection, temperature, pressure, and gas-oil ratio (GOR). Meaningful insights were obtained through statistical analysis and used to inform the system's trend detection capabilities. The created system established its efficiency as an early warning mechanism for oil rim health by using unique data analytics to identify changes in water cut and correlate them with well flow line temperature. Despite issues with data quality and missing inputs, the system seamlessly integrates workflow, data management, analytics, and alarm creation, providing important qualitative insights into contact movement variances. This integration is especially important for enhancing reservoir management practices under constrained data settings, demonstrating the ability of innovative data processing approaches to overcome the limits of standard monitoring methods.