Abstract

The oil and gas industry continues to face challenges. We have witnessed volatility in commodity prices (oil supply outstripping demand, leading to overall market slowdown), the COVID-19 pandemic affecting production and supply chains around the world, labor shortages, facilities-security issues, and the need to prepare for the energy transition, just to name a few. Operators, now more than ever, need to make the most of their assets, not only maintaining production but also understanding what is happening around the clock to be able to prevent potential threats or situations that may escalate and affect operations. New sensors and innovative uses of existing technology are allowing access to a variety of data that can be incorporated into integrated work flows and modeling tools for better understanding of the production system. There are initial signs of operations moving toward the use of real-time models supporting decision making, enabling fast response to external changes, and improved forecasting, resulting in overall improved asset performance. New technology and innovation in production monitoring is focusing more and more on data integration and the use of integrated work flows. Significant attention is being paid to leveraging digital technology (e.g., remote operations, advanced data analysis tools) and improving the accuracy of measured data for better surveillance planning aiming at efficiency gains. Some examples of advances in the past year include the following: - Successful integration of data from permanent reservoir monitoring systems into reservoir models, allowing a better understanding of reservoir changes in waterflooding applications, showing the value of 4D data - Demonstration of the value of using fiber optics (e.g., for distributed acoustic and distributed temperature sensing) for a variety of use cases including well-flow profiling, calibration of fracture propagation models, and understanding well interference - New sensors to monitor pressure and temperature beyond well-integrity barriers in zones with reduced clearance, just ready for field testing - Use of traditional acquired data (e.g., pressure) to infer inter- and intrazone well interference, affordable integration of tracers with sleeve technology for completion and reservoir diagnostic in horizontal wells - Digital methods such as machine learning and artificial intelligence for data interpretation and forecasting and even to serve as surrogate measurements to provide multiphase flow data (i.e., virtual flowmeters). Recommended additional reading at OnePetro: www.onepetro.org. SPE 210270 Innovative Applications of Oil-Soluble Tracers in Unstimulated and Stimulated Multistage Horizontal Wells for Long-Term Flow Assurance and Production Monitoring by Venky Ramanathan, Torxen Energy, et al. URTeC 3723767 Virtual Flow Metering for Continuous Real-Time Production Monitoring of Unconventional Wells by Torgeir Vanvik, Turbulent Flux, et al. SPE 204662 Artificial Intelligence and Data Analytics for Virtual Flow Metering by Anton Gryzlov, Aramco Innovations, et al.

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