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Is Cognitive Predictive Maintenance the Key to Saving the Oil and Gas Industries?

While the oil and gas industries generate a lot of revenue between them they are still massively behind when it comes to the upkeep of the facilities.

Most pipelines in use today were built more than 20 years ago. We’re still operating on old technology too, making the pipelines expensive to run and maintain as being so old, they’re more prone to leakages.

As well as the pipelines being outdated, so is the system that’s meant to monitor and operate them.

So when something goes wrong, instead of just a simple fix, a whole workforce is required to remedy the situation.

READ MORE: 10 Applications of Machine Learning in Oil & Gas

READ MORE: How Oil Giants ExxonMobil, Royal Dutch Shell, Sinopec, Total and Gazprom Are Using AI

Despite the massive risk to workers and the environment, oil and gas companies have been reluctant to upgrade their equipment in the past. However, that may be about to change thanks to the rise in data technology, smart sensors, and cognitive predictive maintenance.

The implementation of AI in the oil and gas industries was demonstrated last year when oil producer Gazprom Neft teamed up with IBM.

The newly formed partnership intend to continue to work together to develop strategies that use machine learning, cognitive data analysis, and high-performance computing to optimize certain processes within the field.

With both oil and gas prices at a low, savings need to be made from other areas. The price of oil alone has fallen more than 20% this year which leaves the industry in a precarious situation.

And although it may seem counterproductive to invest in technology in times of strife, it will be much better in the long run. It’s “spending money to make money”, says IBM’s Marceli Bouzein.

These sensors are already being used throughout the industry, with the average offshore production platform housing about 40,000 data tags. But that doesn’t mean to say they’re being put to good use.

The data is taken from expansive well sites, advanced equipment, large pipeline projects, and gas gathering systems and gets fed into an outdated control system, which is not very helpful. Another issue is when data sometimes get stored in unstructured forms and becomes difficult for a computer to decipher.

By investing in cognitive computing, companies will have access to a mountain of data which will enable them to make more informed decisions and save money throughout the business.

Data optimization is the key to improving performance and increasing production. It can also help reduce, improve efficiency and prevent disasters from happening.

Original source E & P

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KC Cheung
KC Cheung has over 18 years experience in the technology industry including media, payments, and software and has a keen interest in artificial intelligence, machine learning, deep learning, neural networks and its applications in business. Over the years he has worked with some of the leading technology companies, building and growing dynamic teams in a fast moving international environment.
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