AI in Oil & Gas Industry

About Artificial Intelligence (AI)

Artificial intelligence is the simulation of human intelligence processes by or with the assistance of computational machines. 

AI applications include, however, are not limited to:

1. Expert Systems: This computer program uses artificial intelligence (AI) technologies to simulate a human’s judgment and behavior or an organization with expertise and experience in a particular field.
2. Natural Language Processing (NLP): This is human language processing by a computer program, and the tasks essentially comprise text translation, sentiment analysis, and speech recognition.
3. Speech Recognition: This technology allows computers and applications to understand human speech data, which enables computers, applications, and software to comprehend and translate human speech data into text for business solutions. 
4. Machine Vision: This gives a machine the ability to see, which is facilitated by the capture and analysis of visual information using a camera, analog-to-digital conversion, and digital signal processing.

In summary, AI does whatever is needed to associate, imitate, predict, complement, and even replace natural human intelligence.

AI in Oil and Gas

Though widely criticized and often blamed for its carbon footprints and global warming impact, the Oil and Gas industry is still a significant player in fulfilling world energy needs (Current demand for fossil fuels – oil, gas, and coal – is 66% of total energy demand, which is two-third of total demand, as reported by IEA World Energy Outlook, 2022). 

AI provides powerful benefits across the entire value chain for energy production’s dynamic and challenging landscape. For oil and gas companies, AI helps assess the value of specific reservoirs, customize drilling and completion plans according to the area’s geology, and assess each well’s risks. For Midstream and Refining, AI helps forecast long-term commodity input and product market price, provides capital planning and risk evaluation for better long-term decisions, optimizes commodity trading and hedging strategies, improves reliability risk modeling for refining and processing assets, maximizes labor productivity and wrench time, enhances asset scheduling for refining and processing operations, and optimizes pipeline scheduling for product flows. In addition, various downstream processes can be optimized to minimize costs and maximize spreads.

References:

Ed Burns, Nicole Laskowski, Linda Tucci, A guide to artificial intelligence in the enterprise, Tech Accelerator, TechTarget, Marc 2023

Anirban Sengupta, Speech Recognition AI: What is it and How Does it Work, Gnani, October 2022

Datarobot.com/solutions/oil-and-gas/

Article: World Energy Needs, Canadian Association of Petroleum Producers