Saudi ArabiaEnergy and utilities2020 – ongoingSaudi Aramco
Machine learning to optimise boiler fuel use at Khurais
Aramco said its Khurais boiler optimisation system contributed to an 8% reduction in carbon dioxide emissions
Problem
Khurais sought to reduce fuel consumption and greenhouse gas emissions from its oil-producing operations. Boiler fuel use was a specific target for improvement.
Approach
The Khurais team developed its own boiler fuel optimisation system using predictive and prescriptive machine learning. Aramco reported annual fuel gas savings and said the application contributed to an 8% reduction in carbon dioxide emissions.
Results
Takeaway
The boiler application had a reported emissions benefit distinct from the field's wider digital programme. Aramco did not disclose the measurement baseline or the volume of fuel saved.
Categories
- Size
- Large enterprise
- Industry
- Energy and utilities
- Business function
- Production and quality
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and MLOptimization
- Adoption
- Built in-house
- Goal
- Cost savings
- Evidence
- Company's own claim
Sources
Source summaries
Aramco described an internally developed machine-learning system for Khurais boilers. It reported fuel savings and a contribution to an 8% emissions reduction without specifying the comparison period.
Full details are in the original sources.
