Oil spills are dangerous. They hurt the environment, animal life and ecosystems every time they unfold. In some instances, like the 2010 BP incident, oil spills can be deadly. However, with progress and innovation in the technology world, artificial intelligence (AI) can now help predict and prevent these spills.
Though the world of oil drilling and processing is difficult, AI pairs well with new technology like Internet of Things (IoT) sensors and big data. Putting them all together creates a more cost-effective oil operation that protects the environment and workers from accidents.
Learning From Data
The BP oil spill passed the 10-year mark this year. It has left behind a legacy of destruction and harm. However, it’s also important for industry workers to learn from what happened. Many sources attribute the Deepwater Horizon incident to a failure of the blowout protector, which led to a surge of gas and an explosion.
For oil rigs in the present day, newer technology can handle data better than a decade ago. It’s now important to understand what the data says and use it in proactive ways. For instance, if the AI-based system reports an error with a part or machine, workers can respond instantly. Using data to monitor systems in real-time will be what ultimately keeps the rig safe.
AI is powerful. It uses machine learning ” essentially advanced pattern recognition ” to understand how a system should be working. As AI “learn” more patterns and collect more data, they can operate for longer without human input and send alerts or notifications when something goes wrong.
For example, oil rigs can hook IoT sensors up to things like the blowout protector. These sensors transmit data that machine learning algorithms then learn from. If there’s any activity that deviates from the regular norms and patterns, then workers know they must act decisively to head off issues before they worsen.
Predictive Maintenance
AI is powerful and vast. It goes beyond prevention in-the-moment and reaches the level of accurate prediction. Instead of rushing to address issues or errors, workers can use AI, IoT and data together to understand how to prevent obstacles before they even occur.
The same data learning and pattern recognition principles apply. IoT sensors transmit data from anything they’re connected to. The machine learning software then processes this data and figures out how each part, machine and system should be operating. Then, it can watch out for a lack of production or efficiency.
If a part shows a deviation from its normal patterns for prolonged periods of time, it could mean it’s due for updates. Without an AI system in place, workers may not notice this. If it leads to an issue, the effects could be devastating. Instead, AI monitors it all in real-time.
Thus, AI uses analytics from the sensors to predict maintenance needs. Workers can repair or replace whatever isn’t functioning before a potentially dangerous or profit-damaging issue arises.
Automation and Protection
When oil rig workers include AI automation, it goes a lot way. For human and environmental protection, AI can monitor air quality on top of the machinery. It can track weather patterns and alert workers accordingly. Best of all, it can prevent dangerous spills from happening that may harm individuals and the environment.
For instance, oil spills pollute water sources of all different kinds. Societies and cities will then need to focus on ways to protect soil and groundwater from this pollution once it reaches the shore and infiltrates water management.
On the rig, a spill could lead to an explosion, as with Deepwater Horizon, where 11 people lost their lives and 17 people suffered injuries. Artificial intelligence predicts and monitors to limit and even stop these kinds of events in their tracks.
Ultimately, automation reaches its full potential as a way to protect everyone on the rig, as well as ecosystems and nearby population centers.
AI for Oil Exploration and Processing
As AI reaches into industries all across the world, oil rig managers and experts should be actively exploring and integrating this technology. It has the power to reduce errors large and small. However, no matter the size of the obstacles, it all adds up to better protection against oil spills and other dangerous circumstances.
