在煤样本中预测绝对透性的新模型:对注射压力和核磁共振数据应用修改后的Purcell模型
Yanhai Chang1,2, Kun Zhang1, Yipeng Zhang3
1State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Anhui University of Science and Technology, Huainan 232001, China.
ACS omega
|June 16, 2023
概括
这项研究通过专注于透孔,提高了煤炭透性的预测. 一个修改后的Purcell模型和一个新的基于NMR的模型提高了现场应用的准确性.
科学领域:
- 地质科学 地质科学
- 石油工程是石油工程中的一个.
- 材料科学 是一种材料科学.
背景情况:
- 岩石透性对于地下应用至关重要.
- 来自注射孔径测量 (MIP) 和核磁共振 (NMR) 的孔径特性用于估计透性.
- 煤炭的透性比砂岩的透性更少被研究.
研究的目的:
- 对煤炭进行全面研究和改进透性预测模型.
- 研究不同孔隙类型 (透与吸附) 对煤炭透性的贡献.
- 从孔状性质来估计煤炭透性的改进模型的开发.
主要方法:
- 在煤样 (0.0031.26 mD) 上对各种透性模型进行了全面的研究.
- 修改了Purcell模型,以特别考虑煤炭中的透孔.
- 开发了一种新模型,将修改后的Purcell模型应用于NMR数据.
主要成果:
- 透孔占煤炭透性的主导地位;吸附孔的贡献微不足道.
- 现有的模型 (Pittman,Swanson,Purcell,SDR) 对于预测煤的透性是不够的.
- 修改后的珀塞尔模型提高了预测能力 (增加了R2,减少了~50%的误差).
- 一个新的基于NMR的模型实现了对切片的高预测能力 (~0.1 mD),从而实现了现场估计.
结论:
- 一个经过修改的Purcell模型通过关注透孔,准确地预测煤炭的透性.
- 一个基于NMR的新型模型提供了一种使用煤炭切片的新方法来估计田间的透性.
- 这些进展提高了对煤层透性的理解和预测.
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