预测地质聚合物可抽取性和为井区隔离设置时间 - 使用机器学习和基于统计的模型
Anis Hoayek1, Mahmoud Khalifeh2, Hassan Hamie3
1Mines Saint-Etienne, Universite Clermont Auvergne, CNRS, UMR 6158 LIMOS, Institut Henri Fayol, F- 42023, Saint-Etienne, France.
Heliyon
|July 31, 2023
概括
地质聚合物显示出作为石油和天然气井凝固中波特兰水泥的可持续替代品的希望. 决策树模型准确地预测了地质聚合物的抽取能力,在有限的数据中最大限度地降低了运营风险.
科学领域:
- 材料科学 材料科学 材料科学
- 化学工程是化学工程的重要组成部分.
- 石油工程是石油工程中的一个.
背景情况:
- 地质聚合物和活性材料正在成为波特兰水泥的可持续替代品.
- 它们在石油和天然气井凝固中用于区域隔离的应用正在调查中.
- 有限的实验室规模的研究存在,需要更广泛应用的预测模型.
研究的目的:
- 为了解决在各种条件下理解地质聚合物行为方面的差距.
- 将各种预测模型应用于有限的实验数据,以准确地预测抽气能力.
- 为了验证这些模型在地质聚合物应用中的通用性.
主要方法:
- 使用二进制/多门分类模型 (物流/试验,决策树,随机森林,SVM).
- 使用回归和连续模型 (多线性回归,神经网络).
- 专注于预测关键的地质聚合物属性:可性.
主要成果:
- 决策树模型展示了一个简单的,直观的理解地质聚合物的行为.
- 使用决策树模型,可以准确地预测地质聚合物抽取能力.
- 发现,具有高运营风险的不准确预测的概率非常低.
结论:
- 使用机器学习模型,特别是决策树,可以可靠地预测地质聚合物抽取能力.
- 决策树模型为评估地质聚合物适用于井水凝固提供了一个实用的工具.
- 进一步的研究应该集中在模型的概括和验证,使用广泛的现场数据.
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