Home Energy 3 Practical Applications of Deep Learning for Oil and Gas Industry

3 Practical Applications of Deep Learning for Oil and Gas Industry

Deep learning and the Internet of Things (IoT) are two aspects of artificial intelligence (AI) that could potentially revolutionize the oil and gas industries.

Having already made quite a storm in various other industries including consumer electronics, this couldn’t come at a better time for the oil industry as it currently faces dramatic drops in the price of oil.

While there is no doubt several AI practical applications already in place that will indeed help these industries improve the following are three have the potential to make a significant difference across the board.

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

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

1. Rig diagnostic bots

In the same way that bots are being used in customer service departments, field technicians can interact with diagnostic applications through voice controls.

This is made possible through the use of deep learning and natural language processing algorithms and enables remote diagnostics at the touch of a button.

2. Risk detecting deep learning algorithms

It’s very difficult for a human to be able to see in all the nooks and cranny’s of pipelines, so instead, scientists and computer programmers use algorithms to reveal patterns and weaknesses that may have otherwise been left undetected.

Drones are now being used at a number of oil and gas sites to inspect pipelines. They are able to record footage in real-time as they fly through the pipelines trying to detect any cracks or leaks.

Once the drone footage has been received deep learning algorithms set to work finding any pixel signatures that may indicate a crack or leak.

READ MORE: More North Sea Oil Firms Set to Deploy AI Technology

3. Using deep learning algorithms to spot anomalies

Various oil and gas companies have benefited from using sensors attached to equipment such as rack rods or rod pumps in which to gather data.

But, trying to detect anomalies in this way is very difficult. Using deep learning algorithms, experts can see anomalies that conventional methods would have missed and can alert the rig’s command centre in advance.

Through the use of deep learning and IoT, new predicting and monitoring technologies for the oil and gas industries have emerged that could completely transform them.

Being able to predict what’s coming and see beyond what’s currently seen allows companies to deal with potential problems before they happen, saving them time, money, and bad publicity.

A future where we’re surrounded by artificial intelligence incorporating deep learning and IoT is imminent

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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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