AI and Machine Learning

Three reasons why implementing AI in the oil & gas industry is essential

Artificial intelligence (AI) might not seem critical for the oil & gas industry, but it can improve safety and efficiency for companies on a critical and even basic level.
By Travis Parigi July 8, 2019
Travis Parigi is the founder and chief executive officer at LiquidFrameworks. Courtesy: LiquidFrameworks

The oil & gas industry faces many challenges, such as often working in an unconnected environment and the complex pricing nature of many products. And while some technology in the industry is highly advanced, like the processes they use to drill for oil, some of the more basic technology, like invoicing and scheduling, can be a little dated.

It’s not a market that’s often seen as an artificial intelligence (AI) innovator, but the industry seems eager to adopt new digital technology as they help companies keep costs lower while boosting efficiency. In fact, a Markets and Markets report estimates the value of AI in the oil & gas industry will reach $2.85 billion by 2022. From planning and forecasting to surveying and facility management, AI can help improve the oil & gas industry in ways that it’s never seen before.

Business leaders and marketing teams are often anxious to talk about their company and their products as having AI capabilities. But what does that really mean? Many consumers may be quick to think they’re referring to an actual robot or an autonomous system capable of making decisions on its own. But it’s usually something slightly easier to understand, such as programs that can determine predictive and analytic algorithms and processes that allow for the deployment of those algorithms.

AI really comes down to one thing: data. And most oil & gas companies already have a ton of data from sensors and machines, but they aren’t leveraging it to help them when it comes to things like planning. The more historical data the company has, the more accurate predictions for future performance, especially with the help of algorithms through AI-rooted softwares. Algorithms can be so sophisticated that, in some cases, they can train themselves to guess the best value.

What does this mean specifically for oil & gas companies? Here are three ways AI can be implemented and why it’s needed.

1. Quoting modules. These are necessary for most businesses in the oil & gas industry. When pairing previous data with AI, users are able to access things like historical win rates, a history of quotes, automatic pricing impacts to quotes. Being done through price books or by hand can lead to revenue leakage.

2. Asset management modules. These programs can take data and predict things like the next failure on a piece of equipment. Using data to look at historical averages and curves can predict where the next failure is likely to happen. This allows the team to step in before it happens, saving time, resources, reputation, and most importantly, keeping employees safe. This will have an invaluable positive economic impact on the company.

3. Scheduling. Whiteboards, paper calendars, and Microsoft Excel spreadsheets are pretty common for most oil & gas companies, but they’re inefficient ways of managing crews and scheduling equipment. Utilizing data to look at historical work patterns and job locations, users can auto-schedule equipment and people to the right jobs.

There are many known AI applications and field service software in the industry, and there are more waiting to be discovered. Many leaders in the industry have the budgets and talent necessary to implement AI solutions. They’re already reaping the numerous benefits of AI, and smaller players should follow suit to avoid being left behind. There’s no doubt AI is the future of every industry, and this certainly includes oil and gas. It can be the missing key to unlocking the next productivity revolution.


Travis Parigi
Author Bio: Travis Parigi is the founder and chief executive officer at LiquidFrameworks.