Why AI Now?
Energy — its sources, consumption patterns and economic and ecological impact — has become one of the defining issues of our time. The industry faces financial and market pressure to operate profitably, and societal and regulatory pressure to do so at minimal risk to the environment. Sometimes those initiatives feel as if they’re competing against each other. The good news is the unprecedented volumes of data to feed analytics, from equipment in the field, the plant, transmission infrastructure, homes and businesses. With AI, energy companies can improve every aspect of today’s value chains, while also innovating with renewables to set the stage for tomorrow’s markets.
From exploration and discovery to generation and delivery, RapidMiner can help the energy industry deliver more for less, in faster timescales, while reducing environmental impact.
Energy Industry Use Cases
Drive Revenue
- Analyze upstream energy assets and processes to boost E&P success and efficiency
- Forecast production and demand to handle spikes while also avoiding idle capacity
- Shift refinery optimization to real-time to quickly adapt to production, market and supply conditions
Cut Costs
- Optimize asset utilization to get maximum output from capital investments
- Apply predictive maintenance to midstream infrastructure to minimize loss during transportation
- Analyze and streamline every process in the value chain to minimize costs
Avoid Risks
- Profile EH&S risks and prescribe environmental protection measures
- Improve energy trading & risk management with smarter analysis
- Ensure pipeline integrity by integrating predictions of asset vulnerabilities with exposures
- Detect theft proactively with smart meter data analysis
Highlighted RapidMiner Impact
An oil & gas company used predictive analysis on soil samples to determine the best drilling locations.
An oil driller used predictive analytics to reduce unplanned downtime of its wells by combining real time well performance with historical incidents.
A petroleum refinery business shifted to real-time, continuous optimization and quality control and increased its throughput and yield at much lower cost.
An extraction company applied predictive maintenance to its complex oil rig equipment, decreasing downtime without incurring higher costs.
An energy production facility analyzed accident rates, identified the root causes of safety issues and took steps to create a safer workplace.
An oil pipeline operator applied predictive maintenance by using non-destructive model simulation to determine where leaks are likely to occur, and reduced loss during transmission.
A diversified energy company used text analysis of news articles to predict regulatory sentiment in real-time and created a more proactive and effective government relations strategy.
What Our Customers Say
“RapidMiner makes it [too] easy! RapidMiner is always listening to their clients and making massive changes to increase production and efficiencies.”
– Enterprise Business Architect in the Energy & Utilities Industry