With current economic realities, now is the time to produce "more with less". Exception Based Surveillance (EBS) helps eliminate waste in an engineer's day, by removing unnecessary analysis and allowing the engineer to focus on the highest value tasks. For the surveillance of oil wells, an efficient and effective way to achieve this is to use an automated Exception Based Surveillance System, often augmented by data-driven well rate estimates. Specifically, this paper provides examples from Shell operations in Gabon, Malaysia, and the Netherlands on how EBS systems have been set up to address day to day production challenges. The multiple EBS Systems to be described here have been achieved via the tight integration of real-time data in Well, Reservoir and Facilities management (WRFM) workflows and the automation of complex calculations and rule sets. This paper also describes the WRFM "Next Generation surveillance tool" (NGT) currently being rolled out in several Shell assets (Clinton 2016). The work described here regarding enhanced Exception Based Surveillance Systems and integrated Portals go beyond just deploying tools. To be sustainable and value adding over existing practices, the introduction of these systems requires the transformation of roles, processes and tools to fully and efficiently leverage and gain value from now mature

On the tenth anniversary of the first Intelligent Energy Conference held in 2006, it is appropriate to look back at some of the technologies introduced at the time, and report out on how these have been progressed. This paper discusses one of the technologies: the use of data driven models for well rate estimation, to support and enable real-time surveillance and optimization. In the early 2000s real-time data from oil and gas fields became available in abundance on engineering central office desktops via process data historians and wide area / global communications networks. A key challenge to production management, then, as now, was: "What are the wells producing?" The April 2006 SPE Paper 99963 introduced data driven modelling for continuous well production surveillance leveraging on the suddenly abundant and often very revealing PI data. Today, ten years later, a stream of success stories on the use real time well rate estimates based on data driven models continue to be reported, and these tools are seen as best practice in many different operational scenarios. This paper reviews the key concepts introduced in 2006, and extensions and applications of the technology to various aspects of production surveillance and optimization. As with all innovations, the most challenging elements in the journey have been related to people and processes. The paper discusses these issues in relation to the important role played by technology integration themes such as Smart Fields.