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Updated: Jul 22, 2025

In Situ Visualization of the Phase Behavior of Oil Samples Under Refinery Process Conditions
11:20

In Situ Visualization of the Phase Behavior of Oil Samples Under Refinery Process Conditions

Published on: February 21, 2017

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一种强化学习方法,用于最佳控制油井产量,使用切割的油井组样本

Yangyang Ding1, Xiang Wang1, Xiaopeng Cao2

  • 1School of Petroleum and Natural Gas Engineering, Changzhou University, No. 1 Middle Penghu Road, Wujin District, Changzhou, Jiangsu, China.

Heliyon
|July 24, 2023
PubMed
概括

本研究介绍了用于油井生产控制的个性化强化学习 (RL),使用深度Q网络 (DQN) 和软行为者-关键 (SAC) 算法. 这些方法有效地从油库数据中学习,优于传统方法的最佳石油开采策略.

关键词:
一般化能力的能力.图像增强 图像增强 图像增强最佳的控制控制是最好的控制.生产优化生产优化强化学习是一种强化学习.

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