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Many sensors and devices in the field are now available to the reservoir manager for on-line surveillance and monitoring of his assets. Recently, systems typically termed "Intelligent/Smart Fields", "e-Fields" or "Fields of the Future" have begun to communicate this field data and information directly to his desk. However, the industry still finds itself faced with the challenge of transforming all this raw streaming data into useful information. A multitude of potential applications for real-time field data has become apparent. At short periods, it is already widely used to identify anomalies and provide alarms in the classical Field Automation sense. At medium-long term, however, data ought to be used to identify well and reservoir pressure and flow signatures that help in Formation Evaluation, and for reservoir management and planning through the use of flow simulation and automated history matching. However, rarely is data exploited effectively even at the short timeframes, and hardly ever at the medium and long term. This is largely because the analysis involved - which includes highly technical disciplines - simply cannot be automated by computer. This paper examines how our next big challenge in the Field of the Future will be the ability to streamline these engineering activities and to be able to deliver the associated analysis as a turnkey service to the Field Operator. In particular, it may be that the delivery of this key reservoir knowledge, given the current staff structure of the industry, will only be practical using a third-party service provider approach. Introduction Measurement, automation and control in general, and within the upstream oil industry in particular, has seen an explosion in activity over the last two decades. In virtually every field of engineering, there has been a concerted effort to exploit new technology to maximize the efficiency of a wide variety of processes. Within the oil and gas industry, this process of improved measurement and automation was led by the downstream sector, following the trend in Process Engineering in general. Shortly thereafter, the midstream gathering and transportation pipeline sector followed the same direction, adapting systems utilized in other energy-related transportation industries, notably electric power. For at least a decade now, initiatives in the upstream exploration and production sector typically termed "Intelligent" or "Smart" Fields, "e-Fields" or "Fields of the Future" have also begun to communicate field information directly to the reservoir manager's desk. This topic, also widely referred to as "Digital Energy", is widely discussed in the literature, but a good applications-oriented review is given by Chorneyko (2006). The Field of the Future concept really covers two broad issues:Classical measurement, automation and control similar to any Process Industry. Wells, downhole equipment, meters and sensors, separators, pipelines and other facilities are all essentially components of a standard production process chain. As such, they are best managed using modern automated systems.Advanced Reservoir Management. Since the reservoir itself is a highly important but unconventional component of the production chain, it requires special attention. Most of the measurements taken are indirect (downhole pressure sensors, surface flow rates, water and gas cut, etc.) and the controls are also indirect (choke settings, pump rates, water and gas injection rates). These two issues are also best understood in terms of time-frame and granularity. Saputelli et al. (2003) describe this well in Figure 1. At short periods, data is already widely used to identify anomalies and provide alarms in the classical Field Automation sense. At millisecond-to-second resolution, most measurement and control is done directly by electronics, within automated controllers and DCS systems. The applications are typically regulatory control and emergency management. At the minutes-to-hours level, more centralized and supervisory control is possible with some human intervention.

This paper describes one application of Right-Time analysis of continual field measurements as used in a high-rate HPHT field in the North Sea. Many sensors and devices in the field are available for constant monitoring at the reservoir manager's desk, yet, we are still faced with the challenge of transforming all this raw streaming data into useful information. Data is regularly used to identify anomalies in the classical Field Automation sense. At medium-long term, however, it ought to be used to identify well and reservoir signatures that help in Formation Evaluation, and for reservoir management and planning. This rarely happens because the analysis involved -which includes highly technical disciplines -simply cannot be automated by computer. This makes it vital to be able to streamline these activities and to deliver the associated analysis as a turnkey service to the Field Operator.

IUPAC is very interested in data, big or small. Its web site opens with the statement, “The International Union of Pure and Applied Chemistry (IUPAC) is the world authority on … many other critically-evaluated data.” While the ‘…’ covers compelling and widely popular topics, such as naming new elements, the mission of IUPAC to give its imprimatur for chemical data is of great importance to health, security, and trade in the world. In this article, after a review of present activities, we will contemplate how a comprehensive approach might be structured under IUPAC project rules and then look to the future in a world of ‘big data’ and ‘smart instruments’.