Intelligent Dashboards Reap Millions in Energy Savings

Real-time analytics, diagnostics and decision support pays off for Saudi Aramco Abqaiq Plants

By Adel O. BenDuheash, Samy Achour

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Saudi Aramco Abqaiq Plants is the company's largest oil processing and crude stabilization facility. It is the main oil processing center for Arabian Extra Light and Arabian Light crude oils, with a capacity of more than 7 million bpd. The facility has three main processing operations: oil, natural gas liquid (NGL) and utilities.

Abqaiq oil facilities receive sour crude oil from gas-oil separation plants (GOSPs), process it into sweet crude oil, then transport it to Ras Tanura and Jubail on the east coast, Yanbu' on the west coast and to the Bapco refinery in Bahrain. Offgases from the spheroids and stabilizer columns that are part of the conversion process are sent to Abqaiq NGL facilities for further processing.

Central to Saudi Aramco's ambitions to be the world's leading integrated energy and chemicals company is unlocking the potential of its workforce talent not only to maintain its global reputation as a safe, reliable and environmentally friendly producer, but also to gain recognition as an energy-efficient operator. To this end, the Saudi Aramco Abqaiq Plants teamed up with Integration Objects to engineer and build a state-of-the-art solution that empowers users to:

  • Monitor the entire plant energy consumption from a site-wide perspective, down to the equipment level;
  • Automatically detect the plant state and operating modes, and adjust energy consumption targets accordingly and in real time;
  • Identify energy performance gaps early;
  • Isolate the root causes behind performance gaps using automatic root cause analysis and identification;
  • Take corrective actions while enforcing best practices.

As a result of the deployed application, Abqaiq Plants estimated a potential energy savings in excess of tens of millions of dollars per year.

Historically, once a deviation was detected, the burden of finding the root cause was on plant personnel, requiring lengthy and repetitive brainstorming meetings.

Business Case Is Simple
Historically, Abqaiq Plants, like many operating facilities, adopted a standard KPI management system that monitored energy consumption. Such standard systems performed basic KPI calculations against fixed targets.

Once a deviation was detected, the burden of finding the root cause was on the plant personnel, requiring lengthy and repetitive brainstorming meetings involving different experts and divisions to diagnose the issue. Intensive analysis of behavior patterns and dynamic process trends were required.

Using the conventional system, Abqaiq Plants faced the following challenges:

  • The need for increased accuracy and performance insight for better decisions.
  • False warnings about energy overconsumption, due to using fixed targets instead of dynamic ones that account for the changing behavior of plant processes characterized by different operating modes, products, feedstock and equipment availability.
  • The cycle time to identify the real root cause was too long—meanwhile, the performance gap persists. 
  • KPI calculations were not always accurate because of some instrument failures.

Also Read: Software Suite Combines GE Historian, Data Analysis Solutions

The Solution Is Sophisticated
To overcome these challenges and accomplish the objective of eliminating energy consumption performance gaps, Saudi Aramco Abqaiq Plants selected Integration Objects' KnowledgeNet platform. Energy consumption is calculated and monitored for 24 production units, 57 non-production units and 237 pieces of critical equipment, representing the main energy consumers.

The system (Figure 1) collects plant data from an OSIsoft PI historian and then uses computing, rules, fault propagation and workflow engines to identify the cause of the performance gaps and empower end users with recommended corrective actions.

The system keeps a history of all computed KPIs, root cause identification and recommended corrective actions in a database. The results are then published in web dashboards for user access. The application included:

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