(109b) Harnessing Cognitive AI Technology in Refining to Enhance Operator Decisions

This talk will explore a case study on how one of the largest refiners in the US is leading the way to implement Cognitive AI technologies that digitize refinery campaign processes from planning to operator action. We’ll explain how this technology is helping operators to choose a judgment about what action to take at any given time, leading to better coordination and higher refinery margin through intermediate upgrades, product giveaway, and unit optimization.

Digital technologies and AI are becoming crucial for refiners to improve margins and reduce costs. There is a desire to move quickly so that you can be the company that achieves higher profitability before it becomes the standard. Yet we are observing inefficiency and resistance to digital adoption. Resistance and inefficiency persist at the business level from uncertainly in how to define the most impactful use case, and at a personnel level from a lack of trust in novel digital technologies. In this talk, we’ll discuss how operations teams can begin building trust in AI technologies and share a roadmap of how a refinery launched a major initiative to optimize refinery processes and improve profitability by digitizing the refinery operating plan and leveraging best practices and knowledge to enhance operator decision making abilities.

Commercial optimization of a refinery is a unique exercise in many respects, providing both challenge and opportunity. These include crude slates that change according to market demand, variability in feedstock quality, and the continually changing operating capability of equipment from degradation and many other factors. What makes one refinery perform better than its competitors is often its ability to execute a set of objectives consistently while navigating through this uncertainty. According to Accenture, 61% of refiners believe process optimization technologies are a primary benefit driver to production planning and execution. Refinery campaigns are fundamental to improving margins but using a traditional problem-solving workflow between engineers and operators can be ineffective resulting in a very transactional execution process, relying heavily on individual interpretation of the guidance. The burden is on the operator to fully understand context, leading to inconsistencies over time and between different teams.

To close the talk, we’ll highlight primary benefits from Cognitive AI technologies that are being used in refining today, including providing context to operators, quantifying decision confidence, and allowing for accelerated improvement across campaign plans, ultimately closing the profitability gap.

3 main takeaways:

1. How refiners can build trust in novel digital technologies including artificial intelligence and define the more impactful use cases for their refinery.
2. How one of the largest refineries in the US implemented Cognitive AI technologies to optimize refinery processes and improve profitability by digitizing refinery campaign processes from planning to action in operations.
3. New insights into how Cognitive AI technologies are helping operators to make a judgment about what action to take at any given time, leading to better coordination and helping refineries to better capture the full refinery margin.