DNV GL has secured a contract with OG21 (The Research Council of Norway) to identify how machine learning solutions can add value to the Norwegian petroleum industry. The study will assess how big the opportunity related to machine learning on the Norwegian Continental Shelf (NCS) is in terms of increased volumes, reduced costs and reduced environmental footprint.
Furthermore, it will evaluate what measures the Norwegian oil and gas industry need to take to develop and adopt machine learning faster to realize the identified high value opportunities it can provide. Ultimately, the study will demonstrate the importance of machine learning to maintain the competitiveness of the NCS.
Machine learning is a branch of artificial intelligence that combines informatics, mathematics and calculation-oriented statistics. Machine learning involves techniques that help users handle large amounts of data intelligently. Using designs and algorithms, computers become able to learn from, and develop behaviour based on, empirical data. Examples of how this can be used in the oil and gas industry could include enabling technologies for unmanned platforms, condition-based maintenance and field model optimization.
The study covers the full upstream oil and gas value chain from:
- Exploration and improved recovery
- Completion and intervention
- Processing and transport
- Energy efficiency and environment.
AGR will support DNV GL with their subject matter expertize within exploration and improved recovery. The project was kicked off in Q1 2020 and will continue with the submission of a final report to the OG21 in Q4 2020.