公开(公告)号：US20240403775A1

公开(公告)日：2024-12-05

申请号：US18325777

申请日：2023-05-30

Applicant: ARAMCO SERVICES COMPANY

Inventor： Jilin Zhang ,  Hui-Hai Liu ,  Feng Liang ,  Moemen Abdelrahman

IPC: G06Q10/0637 ,  G06Q50/02

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.