Decision-Support System Optimizes Produced-Water Management

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 35993, “Transforming Produced-Water Management With a Decision-Support System,” by Ashish K. Loomba, SPE, Norwegian University of Science and Technology, and Gaute S. Aaboen and Prashant K. Soni, Aker BP, et al. The paper has not been peer reviewed. Copyright 2025 Offshore Technology Conference. _ This study introduces a novel decision-support system (DSS) to optimize produced-water (PW) management in the offshore oil and gas industry. The DSS integrates field data, system specifications, and simulation tools to quantify system performance, forecast operational challenges, optimize operations, and evaluate the effect of system modifications. This research highlights the DSS’s potential to advance PW management practices by improving system efficiency and equipment and environmental performance, leading to more economically viable operations. DSS Description A DSS provides a structured framework that integrates data, analytical models, and expert knowledge. By offering actionable insights, predicting outcomes, and optimizing decisions, a DSS optimizes operational performance and productivity. For PW management, the DSS combines historical, real-time, and forecast data with system awareness and simulation tools to deliver a comprehensive understanding of treatment processes. Traditional PW management methods often rely on manual monitoring and reactive decision- making, which are time-intensive and prone to error. In contrast, a DSS leverages real-time data processing and simulation models to provide up-to-date system-performance insights and predict potential issues before they escalate. Additionally, by integrating diverse data sources and analytical tools, a DSS delivers a holistic view of the system, empowering engineers to make informed, precise decisions. A comprehensive DSS typically consists of the following components: - Field data—A thorough analysis of field data is essential for effective decision-making. This includes historical data collected from sensors and monitoring equipment installed throughout the production system. Examples of field data include flow rates, pressure, temperature, and oil-in-water (OiW) measurements, which provide critical insights into system performance. - Forecast data—While not mandatory, forecast data enhances decision-making by offering insights into future conditions and trends. This data allows for proactive planning and the anticipation of potential challenges. - System information—In addition to field data, a comprehensive knowledge of production and treatment facilities is crucial. This includes equipment specifications, operational parameters, and platform constraints, which collectively define the system’s current state and capabilities. - Simulation tools—As the core of the DSS, simulation tools replicate the behavior of the PW management system under various scenarios. These tools use physics-based models or, when applicable, data-driven approaches to analyze historical performance, predict future outcomes, and evaluate the effect of different operational adjustments. - Dashboards—The processed data and simulation results are presented through interactive and user-friendly dashboards. These dashboards offer visual representations of key metrics and performance indicators, enabling operators to monitor the system effectively and make informed decisions.