Artificial intelligence (AI) is becoming a big part of our everyday lives, even if most people don't see it. Consider the facial recognition used to tag a photo on social media, the language processing in the mapping feature on your smartphone, or the natural language understanding that digital assistants and smart speakers employ. These achievements, and many, many more, are the product of advancements in AI.

While the tech industry was the early bird to the AI movement, others followed along more slowly. Now it seems that the oil and gas industry may be the next to undergo a transformation.

Companies such as Royal Dutch ShellChevron, General Electric subsidiary Baker Hughes, and Eni have teamed up with NVIDIA Corporation (NVDA -9.46%) to accelerate the adoption of this technology in the oil and gas industry. 

Crude oil refinery and pipeline

Is the oil and gas industry the next to be conquered by AI? Image source: Getty Images.

Finding a needle in a haystack

AI, or more specifically deep learning, uses computer models based on the structure and function of the human brain combined with sophisticated algorithms and reams of data to reproduce our capacity to learn. The system gains the ability to distinguish patterns and discover relationships in the data that might go unnoticed among their human counterparts. This groundbreaking competency to uncover seemingly meaningless connections in the underlying information is at the heart of AI's transformative power.

Drilling for natural resources presents a number of challenges that AI is uniquely suited to address. First and forecast is the massive amounts of information that has to be analyzed at every step of the process. Producing simulations that can predict better drilling locations, sifting through seismic data images and generating 3D maps, geological and geophysical studies, and analyzing inputs to increase the accuracy of predictions regarding the size of reservoirs -- it can all be done more efficiently with AI.

Data, the new oil

NVIDIA realized in the early days of AI adoption that the same massive parallel processing capabilities that make its graphics processing units ideal for rendering images also made them a perfect solution for AI's data processing needs. NVIDIA's DGX Station supercomputer combines this capability with the distinct advantage of being able to process data in remote locations, where reliable internet may not be available. This can be particularly useful when dealing with conditions found on offshore rigs and along distant oil and gas pipelines.

Infographic listing several ways AI can be applied to the oil and gas industry.

NVIDIA is bringing its AI to oil and gas. Image source: NVIDIA.

This technology can be applied to visualize and make determinations from petabytes of well geography data, implement complex algorithms to locate subsurface faults, and use raw seismic data to speed up exploration. 

AI can also automate many of the data-centric processes that are necessary in the industry, such as aggregating and examining production volumes, analyzing sensor data, monitoring flow rates, calculating pump pressures, and evaluating temperature data. Until now, much of this information has been monitored and collected, but not analyzed. Processing this data could provide a wealth of worthwhile and potentially valuable information for the industry.

The average offshore drilling rig generates 50 terabytes of data per year from sensors, 10 terabytes of seismic data per survey, and 1.5 terabytes of pipeline inspection data for every 373 miles of pipe. Using AI, the companies are developing analytics that will result in actionable information. 

NVIDIA DGX Station AI supercomputer.

NVIDIA DGX Station AI supercomputer. Image source: NVIDIA.

A data baron

NVIDIA has made a surprising number of partnerships across a wide variety of industries in its quest to bring AI to the four corners of the world. Those moves have been particularly lucrative for the company. In its most recent quarter, NVIDIA delivered record revenue of $2.9 billion, up 34% year over year, while its net income swelled to $1.12 billion, up 71% over the prior-year quarter. 

Much of these gains were driven by the company's data-center segment, which houses revenue from AI. Those AI-related sales doubled year over year and now account for over 20% of NVIDIA's total revenue.

The continued adoption of AI across a variety of industries will probably continue to bolster the company's results for the foreseeable future.