White Whale announced today its AI Analytics platform, DeepSea, will be deployed across additional Husky Energy thermal bitumen projects in Saskatchewan.

“Reducing our steam-to-oil ratios lowers our energy and air emissions intensity, including GHGs, while reducing operating costs and water use”

The announcement follows a year-long pilot with the goal of improving steam-to-oil ratio (SOR) and optimizing production for Husky’s thermal bitumen projects in Saskatchewan. White Whale’s technology was successfully tested and validated at three Husky projects, Sandall, Edam East and Edam West. Husky plans to roll out the AI solution to monitor and optimize its remaining thermal projects using the DeepSea platform.

“Reducing our steam-to-oil ratios lowers our energy and air emissions intensity, including GHGs, while reducing operating costs and water use,” said Glen McCrimmon, Husky’s Chief of Innovation. “With the implementation of DeepSea, steam use is down 10%, and we have seen these results sustained over a year, which gave us a lot of confidence to expand our use of White Whale’s technology.”

The DeepSea AI-based solution is able to achieve these benefits by optimizing steam distribution and pump control across the entire field rather than a single or subset of wells. The system ingests billions of data points from downhole and surface sensors to determine each well’s sensitivity, then ciphers through millions of possible scenarios to find the global optimal solution.

“Solving for the global solution turned out to be an extremely difficult task even for experienced engineers, this is because the number of combinations scales exponentially with the number of wells,” explains Peter Guo, Head of Algorithms at White Whale. “Being built on distributed compute engines, DeepSea is able to get the run-time down from hours to minutes.”