Smart Optimization of Proactive Control of Petroleum Reservoir

Artificial Intelligence plays an increasingly important role in many industrial applications as it has great potential for solving complex engineering problems. One of such is the optimization petroleum reservoirs production. It crucial to produce hydrocarbons efficiently their geological resources are limited. From economic point view, hydrocarbon well control factor affects whole market. The solution proposed this paper based on state-of-the-art artificial intelligence methods, optimal control, and decision tree theory. idea apply a novel temporal clustering algorithm utilizing autoencoder dimensionality reduction layer cluster assignment, wells into groups depending production situation that occurs vicinity well, which allows reacting proactively. Then belonging specific determined using auto-adaptive whose parameters optimized sequential model-based configuration method. Optimization translates directly several benefits: operation costs, increase effectiveness overall income without any extra expenditure only changed.
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