Choosing where to drill an oil well can require months of geological analysis and involve costly decisions. Now, artificial intelligence could reduce some of that planning work to just 45 minutes, while helping energy companies anticipate drilling problems before they occur, according to Dennis Jol, CEO of UAE-based energy technology company AIQ, Qazinform News Agency reports.
In an exclusive interview, Jol explained how AI could reshape the oil and gas industry, why mistakes made by intelligent systems can have serious consequences and what his company is already doing in Kazakhstan. AIQ applies artificial intelligence to reservoir analysis and production optimization.
How can these technologies specifically improve drilling operations in Kazakhstan, from selecting drilling locations to reducing nonproductive time and the risk of costly failures? When ChatGPT hallucinates, it’s cute. But in our operations in the industrial sector, hallucination could be catastrophic.
So in everything that we do, we always keep humans in the loop. One of the four main domains that we operate within is subsurface. What AI can do for the subsurface is look at seismic interpretation, field development planning and all the different workflows involved.
What used to take months and years to do, we can now do in 45 minutes. It helps us make decisions about where to drill. Drilling holes in the ground is a very capital-intensive operation. AI can drive efficiencies, whether that’s predicting stuck pipe or predicting and simulating rig moves.
Any way that we can reduce the costs of an already capital-intensive operation would be beneficial. The next area is production optimization. Once we find where the reserves are, we drill and produce. AI helps us produce within our systems in the most efficient manner.
The last area is the facilities themselves, making sure they are up and running and operating efficiently. That is what we try to achieve with AI at AIQ for our customers. AIQ has stated that its AR360 solution can deliver a 75% productivity gain in reservoir model reviews.
We also created Energy AI, one of the largest first-of-its-kind agentic platforms. We took 1.1 million documents, including structured and unstructured data, and used that information for validation across 42 workflows and existing tools, bringing everything together to make decisions faster.