使用动量方法加速组合优化.
Mathias M Nilsen1,2, Andreas S Stordal3,4, Rolf J Lorentzen3
1NORCE Norwegian Research Centre, Energy & Technology, Bergen, 5838, Norway. mani@norceresearch.no.
Scientific reports
|October 25, 2024
概括
动量方法加快石油储量优化,减少模拟需求. 这些技术提高了净当前价值,使它们对复杂的动态问题有效.
科学领域:
- 石油工程是石油工程中的一个.
- 优化方法 优化方法
- 机器学习 机器学习
背景情况:
- 动量梯度下降方法在机器学习中被广泛使用.
- 它们对耗时的动态问题 (如石油储备管理) 的应用并未得到充分理解.
研究的目的:
- 为了研究各种动量方法的性能,与集成梯度近似相结合,以加速优化.
- 在石油储库生产优化背景下评估这些方法.
主要方法:
- 对四种不同的动量方法进行了广泛的测试.
- 在确定性和稳健的设置下对水库试验案例的应用.
- 利用梯度的整体近似来进行优化.
主要成果:
- 势头策略在数值实验中表现得更好.
- 与标准方法相比,实现了更高的平均净现值.
- 为了达到最佳解决方案,需要进行更少的模拟.
结论:
- 动量方法是有效的加快石油储量优化.
- 这些方法为提高水库管理的效率和经济成果提供了有希望的方法.
- 这些发现表明动量技术在复杂的动态优化问题中具有更广泛的适用性.
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