Digital Transformation Evolution: From Zero to AI/ML Smart Production Surveillance

Abstract Mature oilfields in the Ecuadorian Amazon Basin face persistent operational challenges derived from decades of continuous production, aging infrastructure, fragmented data, and a high reliance on manual processes. This paper presents a comprehensive case study of a structured, long-term digital transformation implemented in a brownfield with more than 50 years of production history, with most wells being artificially lifted with Electric Submersible Pumps (ESPs) and where a high proportion of wells in the field manage high water cuts. Beginning in 2012, the asset experienced limitations in automation, delayed response times, and suboptimal decision-making, which motivated the definition and execution of a digital transformation strategy aligned with business objectives and measured through clearly defined Key Performance Indicators (KPIs). The roadmap was executed in four distinct stages, each with the aim of integrating assets, increasing instrumentation and generating workflows. The first stage focused on establishing the foundation for data transmission and governance by implementing satellite communication, structured data storage for producer wells and creating the Integrated Monitoring Asset (MIA) center. Subsequent stages expanded fiber optic networks, field instrumentation and established a Supervisory Control and Data Acquisition (SCADA) system to enable real time acquisition and control of high frequency data from wells and surface facilities. A Production Data Management System (PDMS) was also implemented to govern low frequency and historical data enabling further analysis for the whole asset. Once a robust infrastructure was implemented, the fourth and final stage had the aim of bringing data analytics, cloud-based platforms and Artificial Intelligence/Machine Learning (AI/ML) solutions and workflows. Key applications include real time ESP well surveillance and prioritization events, virtual flow estimation for the water injection, disposal and producer wells, annular gas monitoring and flare detection, vibration-based monitoring and surveillance for Horizontal Pump Systems (HPS) along with automated and self-calibrating well and network models. These solutions transformed operations enabling early detection of abnormal events, rapid corrective actions and continuous optimization of production and injection networks. The tangible results of this transformation strategy can be seen through more than 200,000 barrels of oil that in 2023 were saved through early events detection and debottlenecking. Among other benefits, including personnel efficiency increases by 93%, ESP system reliability enhancements and a significant reduction in operational risks and carbon dioxide (CO2) emissions. This case study confirms that digital transformation in brownfields is not merely a technology deployment exercise, but a systemic re-engineering of people, processes, and operations.