一种地质受约束的混合堆叠组合方法,使用井日志来预测大陆页岩水库中的TOC
Yizhou Lu1,2, Feng Tian3,4, Haixin Zhang5
1School of Computer & Information Technology, Northeast Petroleum University, Daqing, 163318, China.
Scientific reports
|February 14, 2026
概括
本研究引入了一种新的混合组合方法,用于估计大陆页岩油库中总有机碳 (TOC). 这种先进的技术使用井日志数据准确预测石油潜力,这对于非传统石油勘探至关重要.
科学领域:
- 石油地质科学 石油地质科学
- 机器学习应用在水库工程中的应用
- 非传统资源评估 非传统资源评估
背景情况:
- 大陆页岩油是全球重要的非常规石油资源.
- 准确的储量评估,特别是总有机碳 (TOC) 估计,对于评估石油潜力至关重要.
- 传统的井日志为水库表征提供了必不可少的数据.
研究的目的:
- 开发和验证一种混合组合方法,用于在大陆页岩水库中准确的TOC预测.
- 整合多样化的井日志数据和先进的机器学习技术,以改进水库评估.
- 通过使用专门的模块,应对不统一的时间步骤数据的挑战.
主要方法:
- 一种混合堆叠组合模型,集成了极端梯度提升 (XGBoost),随机森林 (RF),最小平方支向量回归 (LS-SVR) 和改进的门式反复单元 (IGRU).
- 使用的功能包括石质学,水库层先验,连续石质学数字化,井日志响应,时间参数复杂值重叠卷积架构 (TP-CVOCA) 属性和主要组件分析 (PCA).
- 采用启发式优化来进行特征选择/超参数调整和规则化混合 (RegMix) 来进行数据增强;IGRU和TP-CVOCA处理了非统一的时间步骤.
主要成果:
- 拟议的混合方法实现了高预测准确度.
- 在井内TOC预测中获得了0.8184 ± 0.0301的R2.
- 在交叉井TOC预测中获得了0.7132 ± 0.0590的R2,表现出强大的性能.
结论:
- 开发的混合组合方法为大陆页岩油库的TOC估计提供了显著的进步.
- 多种数据源和先进算法的集成提高了水库评估的可靠性.
- 这种方法为优化非传统油田的勘探和开发策略提供了有价值的工具.
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