Aker BP was awarded the Exploration Innovation Prize for the development of machine learning models for use in exploration work. The company’s exploration department is already using the solution, often referred to as the ‘exploration robot.’
The machine learning models that have been developed can assist geologists and geophysicists in reconstructing missing well logs, making lithology predictions, calculating shale content, and mapping potential undiscovered reservoir areas. The solution can also provide an impartial assessment of log quality.
The prize is presented by Geopublishing and is awarded during the NCS Exploration Conference.
The jury was impressed that the team has succeeded in creating a tool that is actually used and streamlines daily work.
Peder Aursand, Value Stream Manager and data scientist at Aker BP, presented the ‘exploration robot’ during the conference. He highlights three factors that have been crucial to their success.
“Firstly, we have focused on making the models work for the exploration team, not the other way around. Secondly, we have included explanations and quantification of inherent uncertainty as standard in the models. And we have made the models available in tools and software that the exploration team is already familiar with and uses daily,” says Aursand.
He received the award along with several representatives from the team that developed the exploration robot. In addition to Aursand, the team consists of Tanya Kontsedal, Kjetil Westeng, Yann Van Crombrugge, Christian Lehre, Martine Dyring Hansen, Peyman Rasouli, and Etienne Sylvain Peysson.
Read the article online at: https://www.oilfieldtechnology.com/exploration/21092023/aker-bp-awarded-exploration-innovation-prize-for-its-exploration-robot/