Data Reliability and Information Verification Engine (DRIVE): Unlocking the Driving Power of Digital Insights

Abstract This paper presents the development of a real-time Data Reliability and Information Verification Engine designed for production engineers to support informed and timely decision-making. Reliable data is essential for accurate analysis, operational optimization and effective intervention in production systems. The developed engine continuously evaluates the reliability of incoming data from intelligent field equipment, ensuring that any anomalies are promptly detected and addressed before they affect operational performance. The developed in-house engine provides a unified view of real-time data from the PI server and actionable insights in a single, streamlined environment, serving as a unified data hub. The developed engine continuously captures and transforms real-time field data measurements into insights in minutes, driving faster and more informed decisions. It applies four sequential verification logics: detecting null values, negative readings, out-of-range measurements and stuck readings. If a parameter trigger any of these checks for 80% or more of the time, it is flagged as unreliable. The architecture is built around four specialized modules: (1) Overall Field Data Reliability – providing a high-level view of data health across the entire field, (2) Equipment Reliability – identifying the number of healthy parameters for each equipment (3) Site Reliability Visualization – displaying a data reliability percentage-based tree map and (4) Data Reliability Explorer – enabling detailed trend analysis for individual parameters. The engine has an engine that has the capability to transform 20M+ field data measurements into insights in minutes, driving faster, more informed decisions. The engine architecture is fully customizable, built around four specialized modules, enabling customizable analytics within the fields of interest and allowing data-driven decisions without external dependencies. Additionally, it is a scalable, fast and robust data retrieval tool, with fast data handling and retrieval capabilities that streamline surveillance workflows. The visualization features, such as the Site Reliability Visualization and Data Reliability Explorer, also imply easy tagging and filtering capabilities. Overall, the automated reliability assessment and data handling capabilities reduce the data loss or corruption during load, providing a reliable and efficient solution for data management. Furthermore, it delivers immediate insights into the quality of real-time data, pinpoints the most affected equipment and helps prioritize the resolution of data reliability issues based on their operational impact—particularly valuable for offshore areas where logistics costs and access limitations are significant. The engine bridges the gap between sensor big data from all intelligence field sensors and actionable intelligence by combining multi-tier automated reliability assessment with intuitive visualization tools, allowing users to uncover actionable insights in a single, streamlined environment. This approach not only improves production surveillance efficiency but also sets a new benchmark for proactive, automated data quality assurance in the oil and gas industry.