使用机器学习方法的石油成熟田的地热潜力:厄瓜多尔亚马逊地区
Franklin Gómez1,2, Marianna Vadászi1
1Faculty of Earth Science and Engineering, University of Miskolc, Egyetemváros, Miskolc, 3515, Hungary.
Heliyon
|February 19, 2025
概括
这项研究量化了厄瓜多尔的地热能源潜力.
科学领域:
- 地热能源工程 地热能源工程
- 石油储备管理管理 石油储备管理
- 机器学习应用 机器学习应用
背景情况:
- 结合石油生产和地热能源开采的多代化系统正在引起全球的兴趣.
- 成熟的石油储量为开发二次能源资源提供了机会.
- 厄瓜多尔亚马逊地区的萨沙田作为研究区域.
研究的目的:
- 使用机器学习量化成熟的石油储库中的潜在地热能产量.
- 在地热模拟中比较不同的透性计算算法.
- 评估水库的长期地热能源潜力.
主要方法:
- 用于地热模拟的机器学习方法.
- 对比Kozeny-Carman与主要组件分析 (PCA) 与K-最近邻居 (KNN) 进行透性计算.
- 粒子集群优化 (PSO) 用于将历史数据与水生产目标函数相匹配.
- 卷度和蒙特卡洛方法用于未来三种情景下的潜在量化.
主要成果:
- 通过使用Kozeny-Carman与PCA实现了优异的历史数据匹配.
- 模拟的水产量 (2.757亿平方米) 与历史数据 (2.625亿平方米) 非常接近,误差为5.02%.
- 一个特定的水库区域显示出最多6.5MWt的潜力,预计到2040年平均产能为0.66MWt.
结论:
- 与PCA结合的Kozeny-Carman方程为地热水库模拟提供了一种可靠的方法.
- 地热能源的提取在成熟的油田中是可行的,提供了可行的多代系统.
- 该研究展示了评估和量化现有石油基础设施的地热潜力的实用方法.
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