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Artificial Neural Network Modeling for the Prediction of Oil Production

机译:预测产量的人工神经网络建模

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摘要

Numerical simulations and decline curve analysis are classic tools used for predicting reservoir performance. Numerical simulations are a very complex tool, offering a nonunique solution with a high degree of uncertainty. Decline curve analysis does not take into account opening or closing intervals and variable injection rates. In this study, the authors designed a feedforward backpropagation neural network model as an alternative technique for predicting oil reservoir production performance. Real historical production data obtained from a Libyan oil field was used to train the network. This training network can serve as a practical reservoir production management tool.
机译:数值模拟和下降曲线分析是用于预测油藏动态的经典工具。数值模拟是一个非常复杂的工具,提供了具有高度不确定性的非唯一解决方案。下降曲线分析未考虑打开或关闭间隔以及可变的注入速率。在这项研究中,作者设计了前馈反向传播神经网络模型,作为预测油藏生产性能的替代技术。从利比亚油田获得的真实历史生产数据用于训练网络。该培训网络可以用作实用的油藏生产管理工具。

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