Oil and Gas, AI, and the Promise of a Better Tomorrow


The price of oil has fallen over 60% since summer 2014, and anybody reading the news sees it mentioned on a daily basis. With all of the negativity portrayed in the day-to-day headlines, many forget that the oil and gas business is one of the largest, most globally-important industries in the world.

All is not lost. In fact, there is much to gain.

As the Motley Fool has called out, there is a huge amount of opportunity in the oil and gas industry, notably because it has weathered times like this before.

One of the things that happens during downturns is that companies innovate. As we have seen historically, the companies that emerge the strongest during these times are the ones who adopt innovative technologies to promote growth. These companies are now embracing technologies like machine learning and artificial intelligence to optimize operations in all areas—most notably in upstream drilling and downstream production.

To delve further into how they are being used, machine learning algorithms are being fed by downhole (MWD) and surface (EDR) data systems to predict the likelihood of catastrophic or downtime-related events. For example, what if you had the ability to predict events like kicks or a blowout. This would be significant for two unique reasons:

Blowouts are catastrophic, often resulting in the loss of life. Look at how the Deepwater Horizon blowout affected BP operations. On top of the loss of life, BP saw over $42.2 Billion in fines, reparations, and court costs.

Identification of potential blowout conditions long before they occur allows for control system settings to be modified for optimal production. This means that not only is the likelihood of a catastrophic event reduced, the potential for revenue is maximized.

Now how is this done?

One of the unique capabilities that machine learning algorithms bring to the table is the ability to identify how shifting, dynamic conditions result in different events occurring. Instead of just measuring pressure differentials between zones, machine learning algorithms can look at asset operational data, pressures, mud properties, temperature, and any other data to understand exactly what is happening downhole at that specific well. More impressively, these algorithms are able to do this without ever leveraging the physics-based equations that have been the staple of this industry for decades.

All of this data is then analyzed in an automated fashion to understand if the existing conditions could lead to a non-optimal event such as a kick, blowout, or wellhead failure. Because of the algorithm’s innate understanding of what contributes to the likelihood of each event, recommendations can then be fed into the control system to not only minimize the odds of an event occurrence, but also to maximize output.

Machine learning and artificial intelligence are renovating how the oil and gas industry operates on a daily basis—helping to cut costs, optimize efficiency, and in the end push through another downturn.

In summary, while prices will always fluctuate, by capitalizing on innovation the oil and gas industry will continue to thrive. Machine learning and artificial intelligence are renovating how daily operations are improved- helping to cut costs, optimize efficiency, and in the end, push through another downturn.

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