In recent years, volatile energy prices and exploration for hydrocarbons on new frontiers have started to focus attention on the transformative role of information technology in the search for new oil. Big data, 3D and 4D seismic and new mapping analytics have made it easier to pinpoint oil deep in the ground, even “seeing through” geological structures that were previously impenetrable. Sophisticated multiphase flow assurance simulation has significantly cut the cost of new facilities design by allowing better value engineering to actual conditions. Cloud-based services enable seamless sharing of production data in real-time to support collaboration among joint venture partners and their key technology suppliers to get the best minds solving problems without barriers of time or space. When oil was trading above $100 per barrel, investment in powerful computing technology was justified by the continued quest for more valuable barrels. Now, with oil prices hovering at around $65-$70 per barrel advanced technology is a tool for reducing capital and operating costs, and increasing responsiveness and flexibility.
Until recently, these big IT initiatives were oriented primarily to upstream applications where the costs and profits were large enough to justify investments in new technology. However, as computer and control technology advances, information innovations are starting to move into the downstream space.
Let’s look at the Industrial Internet of Things (IIoT) for example. Cloud-based technologies can facilitate the development of IIoT in the downstream market. New instrumentation comes ready-built with communications protocols that enable sensors and controllers to carry on a real-time dialogue amongst themselves through edge-of-network processors managing plant-level control functions, while propagating data up to a central cloud-based hub to drive and exploit coordinated higher-level analytics. In the refining / petrochemical space, more sensors monitoring temperature, pressure, vibration and flow means a closer handle on optimizing operating conditions. Integration with on-line analyzers monitoring density, chemical composition and other physical properties will spot plants moving off-spec, catalyst performance deterioration and conditions like line plugging, compressor vibration or heat exchanger fouling.
All of these things are possible today in isolation, but data points are costly, monitoring is not end-to-end and is usually reactive in response to suspected operating problems. Engineering manpower is expensive, scarce and can be inconsistent. Humans do not focus well on routine, repetitive tasks, and don’t have the capacity to handle the breadth of optimizing tasks required.
But IIoT will change that. Instrumentation will become cheaper and more ubiquitous; there will be a separation of mission critical (expensive, reliable) instruments from non-mission critical (cheap, disposable) devices; centralized analytics will lead to reliability and margin benefits that will justify the costs of this additional data gathering. Cloud-based solutions will facilitate continuous proactive monitoring of process operations by ‘intelligent’ systems that make more efficient and directed use of operations and maintenance manpower.
By joining up all the pieces of refinery operations – data gathering, aggregating and optimizing – and adding in emergent machine analytics, your plant operations will become more automated, more reliable and more profitable. The role of the plant operator will not disappear, but his position will be upskilled so that he is focused on higher value tasks while the technology looks after the optimal operation of the process units. Big data, IIoT and advanced monitoring technology are already being developed and deployed in the downstream space. Their benefits are only just beginning to be articulated, but it is clear that the direction of travel is toward advanced technology. As these new systems evolve to incorporate the inputs of data scientists, commercial, technical service, operations and maintenance expertise, we expect the combination of more data and intelligent analytics to emerge as a key performance differentiator for top quartile refiners.