Importance

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Abstract

A method and a system for predicting well production of a reservoir using machine learning models and algorithms is disclosed. The method includes obtaining a training data set for training a machine learning (ML) model and selecting an artificial neural network model structure, the model structure including a number of layers and a number of nodes of each layer. Further, the method includes generating a plurality of individually trained ML models and calculating a model performance of each trained model by evaluating a difference between a model prediction and a well performance data. The plurality of top-ranked individually trained ML models is constrained using one or multiple known physical rules. A plurality of individual predicted well production data is generated using the geological, the completion, and the petrophysical data of interest and a final predicted well production data is generating based on the plurality of individual predicted well production data.

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First Claim