Emerson Deploys AI-Driven Optimization Solution for Aramco Refining Operations

AI-Driven Optimization Enhances Refinery Planning

Emerson has announced the successful deployment of its AI-driven optimization solution for Saudi Aramco, marking a significant advancement in the latter’s refining operations. This collaboration commenced with the integration of Emerson’s Aspen Hybrid Models into Aramco’s existing refinery planning framework. The deployment has resulted in the creation of one of the world’s largest multi-site, multi-period optimization models, designed to enhance operational efficiency across Aramco’s global refinery network.

By leveraging a combination of first-principles models and deep domain expertise, Aspen Hybrid Models are engineered to capture complex nonlinear relationships in yield and quality responses. This sophisticated approach has already yielded remarkable results, achieving prediction accuracy of up to 98.5% in key refinery units, which is a significant improvement over traditional models.

The deployment of these hybrid AI models has been particularly impactful in Continuous Catalyst Regeneration (CCR) and Platformer Units. These models facilitate more precise feedstock blending, thereby minimizing discrepancies between planning and actual execution. This accuracy is crucial for improving margin forecasting across Aramco’s extensive refining operations, ultimately leading to more profitable outcomes.

Future Expansion and Strategic Goals

Current initiatives are focused on extending the hybrid modeling approach to hydrocracker units within Aramco’s assets. This expansion is anticipated to further enhance the accuracy of modeling efforts and demonstrate the scalability and robustness of the AI-driven optimization strategy across the enterprise. Ahmad Alkudmani, director of the global optimizer department at Aramco, emphasized the importance of this deployment as a milestone in Aramco’s AI strategy, reinforcing the company’s commitment to innovative technologies for refining optimization.

Aramco aims to achieve several key benefits through the implementation of Aspen Hybrid Models, including enhanced yield and quality prediction accuracy, optimized feedstock blending, and reduced gaps between planning and execution. By automating model updates and minimizing manual tuning requirements, Aramco is positioned to improve operational efficiency significantly. The scalable nature of these models ensures their applicability across a wide range of refinery operations globally.

Claudio Fayad, chief technology officer of Emerson’s Aspen Technology business, remarked on Aramco’s leadership in operational excellence through digital innovation. He noted that the deployment of AI-driven Aspen Hybrid Models not only optimizes complex planning workflows but also exemplifies the value of integrating advanced AI with deep domain expertise.

Frequently Asked Questions

What is the significance of Emerson’s AI-driven optimization solution?

It enhances yield and quality prediction accuracy for Aramco’s refining operations, achieving up to 98.5% accuracy.

How does the Aspen Hybrid Model work?

It combines first-principles models with industrial AI to capture nonlinear relationships in refinery operations.

What are the expected benefits for Aramco from this deployment?

Key benefits include improved yield and quality predictions, optimized feedstock blending, and reduced planning-execution gaps.

Which units are currently using the Aspen Hybrid Models?

The models are currently implemented in Continuous Catalyst Regeneration (CCR) and Platformer Units.

What future plans does Aramco have for these AI models?

Aramco plans to expand the hybrid modeling approach to hydrocracker units to further enhance operational efficiency.