Embrace control room technology innovation
Tips on how to do more with what you’ve got, look to the future.
It was for safety’s sake that control-room management (CRM) regulations were introduced into the oil & gas pipeline industry. Yet, over time, to achieve a comprehensive view of operations, more and more alarm states were introduced. By replacing simple high-level and low-level alarms with alerts for practically anything and everything, an environment was created that too often overwhelms.
CRM regulations were created with good intentions, to fix controller overload and provide for industry uniformity. However, it’s time to stop playing catch-up based on outdated regulations and innovate based on today’s technology.
For pipeline management, the Internet of Things (IoT) means more data is available than was ever thought possible. While this granular pipeline information can lead to a better understanding of an operation’s health, much of it isn’t used and thereby lacks value.
An opportunity exists to better use existing data to create safer, more profitable operations. Value can be found in data already captured, while looking ahead to how the technology is evolving. Revisiting existing technology to increase its profitability is a useful exercise, even with tools already in hand.
Doing Big Data small
IIoT brings intelligent sensing and control to the process and empowers connectivity. But because data is generated or transmitted in aggregate, the overall data burden is lessened, introducing new opportunities. The application of analytics to these simple data sets can lead to improved productivity. Consider the following examples.
Pump-station sensors provide readings at high-frequency intervals. Aggregation and analysis of these readings can yield information useful in optimizing operation and reliability of pump-station turbines.
Most door locks on remote terminal-unit shelters are monitored already. The advantages of applying analytics may not be apparent. Yet by making these locks into online devices a very small dataset can be monitored to answer two important questions: "Did I remember to lock the door as I left the shelter?" and the follow-up, "If I forgot, can I lock it remotely?"
Recently, an industry supplier wanted to monitor, in "near real time," its client’s remotely installed tank that was located outside of cellular coverage. However, the potential return-on-investment did not justify significant data transfer over satellite. Instead, it was decided to sample the tank levels only once per day. Few data sets are smaller than a single analog value once-per-day. Nonetheless, the present arrangement provides grist for relevant, knowledge-based decision making.
Tank level example
Tank-level measurement is another area where simple but meaningful improvements are possible. Gauging tank levels is among the simplest of measurements. Yet from that single measurement, simple calculation is then used to determine tank fluid volumes and space remaining, otherwise known as "ullage." Daily consumption rates are easily calculated and then setpoints determined to generate alarms for rates above or below target. Rates above target could signal a possible leak and lost product. Rates below target could indicate a possible pump malfunction, resulting in lost revenue and upset customers.
In one case study, monthly volume and revenue versus expected-volume were calculated, as well as the number of days until tanks were expected to empty, to alert users to fill the tanks. After that, users devised a function that calculated the optimal amount to add to the tank to achieve a target inventory that minimized total costs of refilling the tanks with carrying inventory.
The potential remains to do more. What about calculating the total volume added for the month? What about the total volume carried for the month in relation to inventory costs?
Stepping back from this simple example, what if the same level of analysis was applied to every data point in a real-time system? Use possibilities extend far beyond what is typical today. We should not only be storing more live values, but doing more with the live data we already collect.
Today’s real-time systems should automatically collect and perform additional analysis of larger volumes of historical data. The analysis should include basic statistical measures as well as simple calculus. This would mean that that flow rate is a derivative and inventory carried is an integral. It should also measure what other values exist, such as, "Is the derivative of the flow rate useful for the business?" While mathematical functions provide value, it often takes human reasoning to understand their significance.
The demand for real-time data inside and out of the control room is greater than ever before. Too much of a pipeline controller’s time is spent communicating SCADA data to field workers. Calling the control room for SCADA data seems like an outdated practice given the current state of technology.
Technology is the intermediary in this situation, with mobile access to that data. Steps taken in this direction ease controller overload and distraction, allowing focus on pipeline-operations safety and efficiency.
HTML and SCADA
Using HTML for SCADA data is another way to increase efficiency through mobile data accessibility. By incorporating web-browser accessibility, enterprise visibility of pipeline information is brought into modern times. With the ability to reach more desktops and devices, HTML has major potential in the pipeline oil & gas sector—both in the office and out in the field.
Display technology has changed over time. Fancy, complex colors and graphics were once considered a great selling point for SCADA system displays. However, just as with adding alarms, these extravagant, complex displays proved a distraction and less safe than some alternatives.
Operations can benefit from modern display technology, which are based on decades of experience with user interfaces. If everything is running smoothly, displays should be non-eye-catching, with only high priority situations highlighted as required. Training is easier too with an easy-to-understand view of operations. Even people who do not have control room experience should be able to understand basic displays.
For example, if you wear a heart-rate monitor during exercise and it tells you that you have a heart rate of 136, which probably means nothing by itself. But, if you can place the heart rate in the context of normal heart rate ranges for an average person your age, then you can decide whether you are exercising too strenuously.
Moving toward innovation in the control room, while making the most of data already available, is especially important with the "great crew change" on the horizon. With much of the industry’s workforce expected to retire within the next five years, companies must find a way to attract and retain young employees with technology. The younger generation has grown up with technology and are attracted to new ways of exploring it, but need tools to present information in a simplistic, easy-to-understand format.
In the attempt to enhance safety in the face of automated alarm controller overload, an environment has been created that is rife with distractions and potentially confusing displays. In the short term, the focus must be on maximization of existing data sets and the streamlining of control room technologies. It’s important in attracting and training a new generation of employees. Finally, pipeline enterprises will move past control room regulations to create an environment that is safer and ultimately more productive.
Lars Larsson is a senior product manager at Schneider Electric. He has more than 22 years’ experience in the oil & gas industry.
Collin Heggerud is a director of product management, SCADA, with Schneider Electric. He has been involved in technology development for the oil & gas industry for more than 20 years.
For more information, please search at Oil & Gas Engineering, Control Engineering, and IIoT for Engineers for editorial content on SCADA, IIoT, and control room industry standards.