The implementation of digital technologies in the oil and gas industry is becoming increasingly plausible across all operational segments, including upstream (exploration and production), midstream (transportation and storage), and downstream (refining and selling).
Along with an increasing demand for oil and gas, the discovery of new oil fields is becoming a high priority for companies around the world. When it comes to the upstream segment, companies are demanding processes and operations to be more efficient and optimised to stay ahead of competitors, and digitalisation has come a long way to enable this.
Since large oil and gas companies often operate remotely and out of several different locations globally, quick access to data records has become a vital part of business processes. In order to be properly utilised, these data records are digitised and assessed to identify issues. To take this to the next level, artificial intelligence (AI) tools can help oil and gas companies automate the analysis.
Companies utilising AI is by no means a new occurrence. Total, for example, started applying artificial intelligence to characterise oil and gas fields using machine learning algorithms as early as in the 1990s.
But in recent years, the application of AI has both been expanded and innovated. In 2013, Total used machine learning algorithms to implement predictive maintenance for turbines, pumps and compressors at its industrial facilities, thus generating savings of several hundred million dollars. Last year, Total and Google Cloud signed an agreement to jointly develop AI solutions applied to subsurface data analysis for oil and gas exploration and production. The AI programs will make it possible to interpret subsurface images, notably from seismic studies (using computer vision technology) and automate the analysis of technical documents (using natural language processing technology).
These programs will allow Total’s geologists, geophysicists, reservoir and geo-information engineers to explore and assess oil and gas fields faster and more effectively.
Marie-Noëlle Semeria, Senior Vice President, Group CTO at Total said applying AI in the oil and gas industry is a promising avenue to optimise performance, particularly in subsurface data interpretation.
“This builds on the strategy being developed at Total, where AI is already used, for example, in predictive maintenance at facilities.”
AI, in combination with robotics is also advancing at great speed. The Massachusetts Institute of Technology (MIT) is working with Exxon Mobil to create self-learning, submersible robots for ocean exploration. The robots’ software, their ‘intelligence’, will allow them to operate autonomously in conditions as harsh as any on Mars and to change their mission parameters on their own volition to explore strange anomalies.
MIT professor Brian Williams Williams said the goal is to have the submersibles embody the reasoning of the scientists that program them. “You want the explorer to do the science without the scientist there. They need to be able to analyse data, keep themselves out of harm’s way and determine novel solutions in novel situations that go beyond basic mission programming. They need to have some common sense and the ability to learn from their mistakes.”
Lori Summa, Exxon Mobil’s former primary investigator on the MIT submersible robot project said that for Exxon Mobil, the robots can help safeguard the ecosystems, as well as detect and analyse naturally seeping hydrocarbons, which could be an indicator for where best to find energy resources.
“We’re curious about new innovations that can push the envelope of energy research to meet the challenges of the future.”
