Chevron Launching Predictive Maintenance to Cut Costs & Improve Operations

By Tim Shea

Category:
Industry Trends

ARC takes every opportunity to blog about examples of leading oil & gas companies that are embarking on their journey towards digital transformation and operational excellence. We are encouraged and excited when companies engage in strong technology partnerships that enable them to breakdown operational silos and harness the power of digital technologies to improve operational performance.  One of the lowest “hanging fruit” in terms of opportunities to leverage the benefits of digital transformation lies in predictive maintenance.

Predictive Maintenance empowered by cloud computing and data analytics

According to a recent article in the Wall Street Journal, Chevron has launched an effort to predict maintenance problems in its oil fields and refineries, a capability that many companies have been working for years to cultivate and is just now gathering momentum. Advances in the functionality and economics of sensors, data analytics and cloud computing are behind the rise of so-called predictive analytics, which Chevron executives say could lead to savings of millions of dollars annually.

Working with Internet of Things services from Microsoft Corp., Chevron aims to enable thousands of pieces of equipment with sensors by 2024 to predict exactly when equipment will need to be serviced.  “In the past, we had to figure out how equipment was performing,” said Chief Information Officer Bill Braun in an email. “In the future, the equipment will tell us how it’s performing. This represents a big shift.”

Microsoft is Chevron’s cloud supplier of record

In 2017, Chevron signed a seven-year deal to make Microsoft’s Azure its primary cloud supplier. The partnership will give Chevron’s engineers access to data in one cloud repository instead of in different silos within the organization, said Mr. Braun. That means it’ll be easier to gain insights from a wider set of data including information from sensors connected to equipment in the field.

In recent years, advancements have been made in the quality and affordability of sensors, as well as the cloud-based platforms required to gather and analyze data being streamed from devices in the field. It’s also become easier and quicker to outfit equipment with wireless sensors, whereas in the past, sensors typically required weeks-worth of wiring and installation.  Chevron expects to outfit oil equipment with sensors for predictive maintenance by 2019 in a wide-scale pilot program, with full adoption for many of the machines expected by 2024.

Over the past six months, it has worked on a small experiment connecting additional sensors to a few heat exchangers, which are widely used in processing oil and gas. Heat exchangers, which range in size from large trucks to small buildings, are similar to radiators that cool down car engines, and an unplanned outage could take days to resolve, translating to significant financial losses, said Deon Rae, head of Chevron’s Industrial Internet of Things Center of Excellence.

Sensors are “tip of the spear” for successful digitization

In the past, two sensors on the heat exchanger would collect information such as temperature of the cooling fluid and the oil flowing through the heat exchanger. But with limited sensor data, Chevron could only know about the current and past state of the machine.  In the experiment, four wireless sensors were put in strategic places along the machine, which captured a wider dataset, including information about temperatures and oil flow. With the additional data and Microsoft’s cloud-based predictive analytics applications, Chevron’s data scientists can predict when the heat exchanger will become dirty and need cleaning, Mr. Rae said.

predictive maintenance of heat exchangers saves money
Heat exchangers at Chevrons El Segundo, CA refinery  Photo: Chevron Corp.

 

There are 5,000 heat exchangers across the company’s oil and gas operations worldwide, Mr. Rae said. Over the next few years, sensors and data could be used to consistently monitor the health of the machines in real-time, helping data analysts better predict when it’s necessary to service each of them. That would reduce equipment downtime and unnecessary repairs and the savings could be in the millions of dollars.

Digital transformation should be all encompassing for maximum success

By 2024, Chevron aims to have sensors connected to much of the critical equipment that could significantly disrupt oil and gas operations and create lost profit opportunities if they ever broke down, he said. Such equipment includes compressors that are used to reduce the volume of gas by increasing pressure, and pumps used to move liquids.

ARC has been researching and writing for years now about how rotating equipment such as pumps, compressors and turbines are excellent opportunities for oil & gas companies (as well as many other industries) to reap the benefits of deploying IIoT-enabled solutions such as smart sensors, advanced analytics, machine learning, AR/VR, and digital twins, among others to digitally transform their operations, work processes and even their organizational cultures in order to be better positioned for the 21st century and beyond.  ARC encourages other owner-operators and independent E&P firms to follow the success of digital transformation initiatives of companies such as Chevron and others since the adage of “no one in the oil & gas industry wants to be first, but sure as heck no one wants to be last” on the journey of digital transformation has never been truer than today.

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