At the Pipeline Technology Conference in April 2024, Nigel Curson presented a technical paper that explored a novel use of machine learning to optimise oilfield water flood systems, identifying constraints and quantifying performance improvements with high accuracy, surpassing traditional methods.

The paper provide insights into a pioneering method for optimising oilfield water flood systems using machine learning, overcoming challenges of internal constraints and imperfect data and showcases how supervised learning algorithms accurately quantify performance improvements, offering insights into practical implementation and future optimisation strategies in the oil and gas industry.

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