通过先进的人工智能方法,在煤密沙基异质地质构造中评估水库岩石类型
Umar Ashraf1,2, Wanzhong Shi3,4, Hucai Zhang5
1Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650500, Yunnan, China.
Scientific reports
|March 7, 2024
概括
这项研究使用先进的井日志分析来识别煤层,将其与紧密的沙子和页岩区分开来. 这些发现有助于煤床甲勘探和未来的采矿,通过表征水库岩石类型和煤炭质量.
科学领域:
- 地质科学是地球科学.
- 石油工程是石油工程中的一个.
- 数据科学数据科学数据科学
背景情况:
- 煤层识别对于煤床甲的勘探和开发至关重要.
- 传统的井日志往往面临着难以准确地区分煤炭与其他石质结构,如紧密的沙子和页岩.
- 复杂的地质构造需要先进的分析技术来准确地表征水库.
研究的目的:
- 开发和验证一种可靠的方法来识别使用传统井日志的煤层.
- 在复杂的地质环境中,将煤炭与紧的沙子和页岩区分开来.
- 为了确定储层岩石类型 (RRT) 并确定潜在的含气区.
主要方法:
- 利用了先进的技术,包括量子-量子图,自组织地图 (SOM),k-平均集群和t分布式随机邻居嵌入 (t-SNE).
- 在三个井 (X4,X5,X6) 进行了定性日志曲线评估.
- 分析了声学 (AC),中子孔径 (CNL),密度 (DEN),光电和电阻日志.
主要成果:
- 马射线和电阻日志在煤炭识别中被证明是不可靠的.
- 煤层表现出明显的日志反应:高的AC和CNL,低的DEN,低的光电和低的孔隙性与紧密的沙子和页岩相比.
- 狭窄的沙子形成显示孔径值在5-10%之间.
- SOM和聚类确定了狭窄的沙子的优质RRT,而页岩和煤炭集群表明RRT很差.
- t-SNE精确地区分了煤炭,并用CNL和DEN图表揭示了研究区域的低级煤.
结论:
- 综合井日志分析策略有效地区分了复杂构成的煤炭与紧密的沙子和页岩.
- 该方法提供了关于储岩类型和煤炭质量的关键见解,有助于煤床甲勘探.
- 这种方法提供了一个有价值的工具,用于了解未来的采矿业务的煤密砂.
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