Shell’s Next Generation Operations Center

Shell Oil has created a next generation control room (CR) to monitor their deep water offshore production activities in the Americas. Shell Oil has created a control room whose scope of analysis is larger than the typical control room, and one that is also delivering an ROI much greater than is typical. The Shell CR is also an Internet of Things (IIoT) Big Data analytics solution.  From a supply chain perspective, this is a critical cog in their supply chain continuity capabilities. From an operations perspective, this solution delivers ROI in the form of better throughput.

Tom Moroney, Shell Oil’s VP of Wells and Facilities Technologies, spoke at ARC’s 2016 Industry Forum in Orlando in February. This article is based upon his remarks.

A control room (CR), or operations center, is a room serving as a central space where a large production facility or physically dispersed production environment can be monitored and controlled by operational personnel. Control rooms are very common in the heavy process industries. The CR’s goals are to insure the safe operation of a facility and production control. The data is real-time and near real-time, and typically actions that are taken based on the information are presented to operators is almost instantaneous in the event of safety issues, or can be executed in a few hours surrounding less critical production equipment issues.

shell operation center

Shell’s CR, located in New Orleans, is staffed by both operational personnel and engineers, with both short term decision making by operations personnel and engineering decisions and analysis that occurs over days and weeks. The savings from this next generation control room have been on the order of 5 to 10 times larger then what they invested. These savings have occurred based on a higher degree of production optimization, based on more tightly integrating engineering analysis into CR activities, than what is seen in traditional control room environments.

Shell’s control room is used to monitor Shell’s deep water offshore production activities in the Americas. The assets being monitored by the CR include 7 floating and 2 fixed offshore oil and gas platforms in the Gulf of Mexico and 2 floating platforms off the coast of Rio de Janeiro Brazil. These superstructures are connected to seven drilling rigs and 300 to 350 production wells. These facilities produce roughly 600,000 barrels of oil equivalent per day.

On a given day, 2000 people are working offshore and these people and the drilling activities are supported by 35 support vessels and 10 helicopters. This is a clearly a big operation.

16,000 to 17,000 pieces of equipment are being monitored in terms of their speed, thrust, pressure, temperature or other critical variables on a daily basis. The integrated production environment being monitored includes reservoir detection sensors, subsurface equipment, connections to the well, and above ground processing equipment. This generates 870 million data points per day. There are 430,000 analyses conducted daily with each analysis consisting of 30 to 150 calculations. This is truly an Industrial Internet of Things Big Data analytics platform.

Production and safety process control is well understood. Centralized control rooms came into operation in the 1920s and many large process industry companies, including Shell, have built multiple generations of control rooms. But Shell wanted to shift the design to include advanced engineering analyses and improve the ROI of this set of incredibly capital intensive offshore investments. The ROI was to come from making sure that every piece of equipment was being utilized at maximum efficiency so that production could be optimized. Events like equipment wearing down, wells sanding up, or insuring water injection into the reservoir maintains sufficient pressure should be detected and dealt with before production is adversely affected.

Understanding when parameters are trending outside a targeted operating envelope is important for understanding how equipment is operating. But to optimize production, models, by the stage of life of a reservoir, need to be applied to parameter data in order to generate actionable information. “If this well is at this stage of its life and the reservoir pressure is X, we know it should be operating at this level” is the example that Mr. Moroney gave.

The information needed by operators and engineers was different, as were the actions that needed to be taken. Therefore, Shell needed to develop clarity around roles and responsibilities. A consistent terminology around alerting was developed:

 

  • An Alarm is a notification for operators that requires immediate and urgent attention. Many alarms are focused on the safe operation of equipment.
  • An Alert is a notification for engineers that indicates a parameter is trending outside of a desired range. This is a developing condition that requires interpretation. This is not a safety issue. But it is a financial issue. The company could lose throughput and other efficiencies if the matter is not dealt with in a timely manner.
  • An Event is a single or combination of alerts that indicate a defined production anomaly. For example, the combination of alerts may indicate that there is insufficient water injection at the reservoir and that this event will ultimately impact recovery efficiencies and production volumes.
  • A Service is the defined set of steps to “treat” an event. A service has little room for interpretation. These are the standard operating procedures (SOPs) necessary to fix the problem. Services include traceability to make sure the desired actions were taken in a timely manner. A service is closed out in a final financial scorecard step that shows the value captured or the losses prevented by this set of activities. As an example of a cost prevented would be an analyses that suggests a field has entered a stage of production where less chemicals need to be put “down hole.”

From a data perspective, the end to end data gathering and processing needed to be thought out including how the data was collected, interrogated, stored and managed. “Data interrogation” refers to how often a piece of equipment needs to be providing data. Leak detection data needs to be continuously collected on a sub-second basis, for example, but a machine that is off line may only need to be interrogated on a daily basis. Interrogation was tightly defined to provide actionable information in the desired time periods. The data collected, and the frequency with which equipment is interrogated, was based on a safety and ROI analyses.

Automation of analytic calculations was also an important goal. According to Mr. Moroney, we “thought about what engineers do on a daily basis, we thought about all the activities, and calculations and models they run” and worked to automate these activities. The goal was to have highly specialized engineering talent, like reservoir production experts, focus on where they add the most value and not have analysis delayed as engineers turned on their computers, downloaded data, put it into the latest models, and waited while calculations were run. When Mr. Maroney was asked about the benefits of this project, he said “It is sensitive to even discuss this. We believe visibility is a differentiator.” But when pushed on the benefits he did admit that they spend tens of millions of dollars to develop this solution and the benefits were 5-10 times as great as the investment. Shell tracks metrics such as deferred production volumes, equipment uptime, and other metrics that impact production volumes and a field’s recovery efficiencies. And as previously noted, a service is closed out with a step that determines the dollars saved or costs prevented, so Shell has a very good handle on exactly the kind of ROI this CR is producing.

According to Mr. Maroney, “This is the cheapest product we have, the CapEx has already been spent, getting returns on these preexisting investments is just good business.”

Finally, Mr. Moroney discussed the importance of forming solid partnerships. Internally, they needed to closely collaborate with the IT function. Externally, Honeywell was their key partner.

Finally, Mr. Moroney stressed that this was a “change journey” that will never end. Engineers will continue to create new types of events based on their modeling, and new services will need to continue to be defined. In particular, Shell has more work to do in incorporating oil field service companies into their services standard operating procedures.

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