Applications of AI in Oil and Gas Industry

Applications of AI in Oil and Gas Industry

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Artificial Intelligence (AI) has lately been offering innovative solutions to problems in almost every industry. Oil and gas software is most certainly not untouched by AI. AI in the oil and gas industry is projected to reach USD 2.85 billion by 2022.

Therefore, there is a huge scope in the field of Artificial Intelligence. And making a career as an AI Engineer is always a good option. So, to upskill and get certified you should pursue an Artificial Intelligence Online course.

Generally, when people use the term AI, they are referring collaboratively to automation, machine learning, and predictive and analytic algorithms, and not just AI. In the oil and gas industry, AI finds uses in the upstream, midstream as well as downstream components.  Primarily, AI is helping companies reduce costs, introduce greater efficiencies, and increase revenue. Currently, its applications are numerous and only expected to increase in the future. Let’s see some of AIs most common applications in the industry.


Predicting an Oil Well’s Yield:

Using historical data on the yield of an oil field, algorithms can be developed to predict its performance in the future. The greater the amount of data that is available, the more accurate the analysis and prediction. However, handling such vast and unstructured data can be a cumbersome task. This is where AI comes into play. With AI, data has to be simply fed into a computer which automatically trains itself to process swathes of information. Using this data, AI then delivers the most reliable results.

Streamlining Permit and Assessment:

Natural language processing (NLP), a branch of AI, can be deployed to simplify permit applications. NLP helps computers to understand and interpret human language. After some requisite improvement, it can be employed in the critical analysis of oil and gas permit applications, which companies submit to governments. This will also help other stakeholders determine whether a project or plant poses any threat to the vegetation, wildlife or local residents.

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Improved Decision Making:

AI is highly efficient when it comes to managing and processing data.  Not only does it give a way to integrate data across multiple applications, but also offers priceless insights. This gives valuable insights which decision-makers can use to make better, more informed decisions. Clearly, incorporating AI into oil and gas software can completely transform the industry in the future.

Chatbots For Customer Support:

Virtual assistants and ‘chatbots’ are successfully replacing human customer service executives in many sectors, and the oil and gas sector is no exception. An online chat platform is deployed where conversations between the customer and the chatbot take place. Royal Dutch Shell’s virtual assistants named Emma and Ethan are an example. They provide product information to the customers and handle over 100,000 data sheets for 3,000 products, although they are still in pilot mode. Chatbots powered by AI are self-learning and require very little maintenance. The oil and gas industry is fast making inroads in this technology of the future.

Robots For Exploration And Production:

Exploration of hydrocarbons is time-consuming and comes with a multitude of environmental challenges. The need for innovative and environment-friendly technology for exploration has always existed. A few petroleum companies are doing this by investing in robots driven by machine learning. ExxonMobil, for example, has been working towards automating deepwater exploration using robots. One massive benefit of AI robots is that they serve as an alternative to human workers when working conditions are dangerous.

Exploration Aided By Machine Learning:

Geologists read and analyze seismic records and subsurface data for exploration purposes. This analysis is currently done manually and is a tedious job. Moreover, these data charts are stored in different locations (physically) or in different formats (on cloud). With the help of machine learning, these charts can be analyzed by a computer and a summary of the data can be obtained. A virtual assistant can answer questions about the data in natural language, increasing productivity manifold.

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Artificial intelligence is generating a lot of buzz in almost every industry but it isn’t free from drawbacks. Cybersecurity remains a major concern. Another pitfall is that the kind of sophisticated technology required for AI needs a big budget. As a result, only the industry leaders are currently adopting it. Nevertheless, AI has recently shown significant advancement towards being more than just a theory. There is no denying the fact that AI, with its many benefits, is poised to transform the oil and gas industry.

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