The dependency on well-head and field real time data has significantly increased in the past few years in the oil and gas industry. The data is used to maximize oil and gas recovery, increase revenue and improve health and safety. This new mode of operation mandates the availability of reliable real time information sent by the different well and field digital equipment for optimum right-time decision making. The challenge is in the fact that intelligent field components include many different layers and nodes that increase the complexity of such assurance. Therefore, the health and the data transmitted from these components, such as digital gauges (e.g., multi-phase flow meters and permanent downhole monitoring systems) and the communication network must be continuously monitored and well maintained. This paper will highlight a newly developed comprehensive and interactive monitoring and key performance indices reporting solution to quantify, assess and visualize the health of the different intelligent field components. The new system is using advance technologies, such as GIS maps to locate fields, equipment, real-time data historian servers, and networks to highlight their availability and reliability status. This solution provides real time alerting and alarming in case of transmission failure, well data integrity situation or inaccurate data detected using an automated diagnostic engine, thereby maximizing safety and increasing accuracy and data reliability.
IntroductionIntelligent (or digital) field is basically a remote acquisition and utilization of real-time surface and subsurface equipment data to monitor and control field processes in a collaboration environment to reduce production cost, real-time optimization and maximize field live value . Intelligent field concept is being a mandatory in the dynamic oil and gas handling operations. In order to achieve that goal, the right data need to be delivered in the right time using the right optimization tools. The realtime data is the foundation layer for any optimization process. With the current dynamic operation mode, a huge amount of data is received in a real-time basis which is required to be validated and verified.