Artificial Intelligence in the Oil and Gas Industry
Over the past couple of years, the digital revolution in the oil and gas industry has become the main topic of discussion for specialized media, industry experts, and occasionally large-scale forums.
But is it a revolution, or is it evolutionary development? After all, the use of computer technology, for example, to solve a problem such as reservoir modelling, began back in the 60s of the last century, and in the early 70s, the use of large workstations for processing field data made it possible to increase production by 1%.
In the 90s, the industry, having mastered the creation of computer 3D seismic models, reduced the cost of finding new deposits by an average of 40%, as a result of which the volume of proven reserves increased by 2.5 times.
Now, the global oil and gas industry, as always one of the first to use the latest technical achievements, has taken up the banner of artificial intelligence. The oil and gas industry has changed rapidly in recent years, with new technologies adopted by the sector to meet the challenges of a digital economic landscape, while at the same time trying to fully implement artificial intelligence solutions.
Customer success stories
A workplace hygiene solutions company approached AI Superior with a unique task: to create a system capable of autonomously identifying when an area needed cleaning, reducing the need for
In today’s dynamic real estate market, accurately assessing the price of different zones within a city is essential for real estate professionals. However, this task has traditionally been challenging
AI Superior, in collaboration with an Ophthalmology Centre, has developed an advanced deep learning model to estimate the volume of fat and muscle in human eyes using CT and
AI Superior has developed an innovative solution for an insurance company that was seeking to provide usage-based insurance to their customers. Leveraging deep learning algorithms, AI Superior has created
AI Superior has designed an innovative solution for municipalities to rapidly detect and localise graffiti in their cities, using state-of-the-art deep learning algorithms. This real-time, high-accuracy graffiti detection system
AI Superior, in collaboration with international humanitarian NGO World Vision, undertook a compelling project to investigate the potential correlation between land degradation and conflicts in selected countries. By analysing
Our Project Approach
The AI project lifecycle has been adopted from an existing standard used in software development. Also, the approach takes into account the scientific challenges inherent in machine learning projects involving software development processes. The approach aims to ensure the quality of development. Each phase has its own goals and quality assurance criteria that must be met before the next stage can be initiated.
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